id	sid	tid	token	lemma	pos
esrj-95748	1	1	factors	factor	NOUN
esrj-95748	1	2	affecting	affect	VERB
esrj-95748	1	3	topographic	topographic	ADJ
esrj-95748	1	4	thresholds	threshold	NOUN
esrj-95748	1	5	in	in	ADP
esrj-95748	1	6	gully	gully	ADJ
esrj-95748	1	7	erosion	erosion	NOUN
esrj-95748	1	8	occurrence	occurrence	NOUN
esrj-95748	1	9	and	and	CCONJ
esrj-95748	1	10	its	its	PRON
esrj-95748	1	11	management	management	NOUN
esrj-95748	1	12	using	use	VERB
esrj-95748	1	13	predictive	predictive	ADJ
esrj-95748	1	14	machine	machine	NOUN
esrj-95748	1	15	learning	learning	NOUN
esrj-95748	1	16	models	model	NOUN
esrj-95748	1	17	mahdieh	mahdieh	PROPN
esrj-95748	1	18	valipour	valipour	ADJ
esrj-95748	1	19	,	,	PUNCT
esrj-95748	1	20	neda	neda	PROPN
esrj-95748	1	21	mohseni	mohseni	NOUN
esrj-95748	1	22	*	*	PROPN
esrj-95748	1	23	,	,	PUNCT
esrj-95748	1	24	seyed	seyed	PROPN
esrj-95748	1	25	reza	reza	PROPN
esrj-95748	1	26	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	1	27	department	department	PROPN
esrj-95748	1	28	of	of	ADP
esrj-95748	1	29	geography	geography	NOUN
esrj-95748	1	30	,	,	PUNCT
esrj-95748	1	31	ferdowsi	ferdowsi	NOUN
esrj-95748	1	32	university	university	PROPN
esrj-95748	1	33	of	of	ADP
esrj-95748	1	34	mashhad	mashhad	PROPN
esrj-95748	1	35	,	,	PUNCT
esrj-95748	1	36	mashhad	mashhad	PROPN
esrj-95748	1	37	,	,	PUNCT
esrj-95748	1	38	iran	iran	PROPN
esrj-95748	1	39	*	*	PUNCT
esrj-95748	1	40	corresponding	correspond	VERB
esrj-95748	1	41	author	author	NOUN
esrj-95748	1	42	:	:	PUNCT
esrj-95748	1	43	nedamohseni@um.ac.ir	nedamohseni@um.ac.ir	ADJ
esrj-95748	1	44	keywords	keyword	NOUN
esrj-95748	1	45	:	:	PUNCT
esrj-95748	1	46	boosted	boost	VERB
esrj-95748	1	47	regression	regression	NOUN
esrj-95748	1	48	tree	tree	NOUN
esrj-95748	1	49	;	;	PUNCT
esrj-95748	1	50	erosion	erosion	NOUN
esrj-95748	1	51	;	;	PUNCT
esrj-95748	1	52	prediction	prediction	NOUN
esrj-95748	1	53	;	;	PUNCT
esrj-95748	1	54	reliability	reliability	NOUN
esrj-95748	1	55	;	;	PUNCT
esrj-95748	1	56	support	support	NOUN
esrj-95748	1	57	vector	vector	NOUN
esrj-95748	1	58	machine	machine	NOUN
esrj-95748	1	59	;	;	PUNCT
esrj-95748	1	60	palabras	palabra	NOUN
esrj-95748	1	61	clave	clave	NOUN
esrj-95748	1	62	:	:	PUNCT
esrj-95748	1	63	árbol	árbol	PROPN
esrj-95748	1	64	de	de	PROPN
esrj-95748	1	65	regresión	regresión	NOUN
esrj-95748	1	66	optimizado	optimizado	NOUN
esrj-95748	1	67	;	;	PUNCT
esrj-95748	1	68	erosión	erosión	NOUN
esrj-95748	1	69	;	;	PUNCT
esrj-95748	1	70	predición	predición	NOUN
esrj-95748	1	71	;	;	PUNCT
esrj-95748	1	72	confiabilidad	confiabilidad	PROPN
esrj-95748	1	73	;	;	PUNCT
esrj-95748	1	74	máquinas	máquinas	PROPN
esrj-95748	1	75	de	de	PROPN
esrj-95748	1	76	vectores	vectores	PROPN
esrj-95748	1	77	de	de	PROPN
esrj-95748	1	78	soporte	soporte	NOUN
esrj-95748	1	79	;	;	PUNCT
esrj-95748	1	80	issn	issn	PROPN
esrj-95748	1	81	1794	1794	NUM
esrj-95748	1	82	-	-	SYM
esrj-95748	1	83	6190	6190	NUM
esrj-95748	1	84	e	e	NOUN
esrj-95748	1	85	-	-	NOUN
esrj-95748	1	86	issn	issn	PROPN
esrj-95748	1	87	2339	2339	NUM
esrj-95748	1	88	-	-	SYM
esrj-95748	1	89	3459	3459	NUM
esrj-95748	1	90	https://doi.org/10.15446/esrj.v25n4.95748	https://doi.org/10.15446/esrj.v25n4.95748	X
esrj-95748	1	91	earth	earth	PROPN
esrj-95748	1	92	sciences	sciences	PROPN
esrj-95748	1	93	research	research	PROPN
esrj-95748	1	94	journal	journal	PROPN
esrj-95748	1	95	earth	earth	PROPN
esrj-95748	1	96	sci	sci	PROPN
esrj-95748	1	97	.	.	PUNCT
esrj-95748	2	1	res	res	PROPN
esrj-95748	2	2	.	.	PUNCT
esrj-95748	3	1	j.	j.	PROPN
esrj-95748	3	2	vol	vol	PROPN
esrj-95748	3	3	.	.	PROPN
esrj-95748	4	1	25	25	NUM
esrj-95748	4	2	,	,	PUNCT
esrj-95748	4	3	no	no	INTJ
esrj-95748	4	4	.	.	NOUN
esrj-95748	4	5	4	4	NUM
esrj-95748	4	6	(	(	PUNCT
esrj-95748	4	7	december	december	PROPN
esrj-95748	4	8	,	,	PUNCT
esrj-95748	4	9	2021	2021	NUM
esrj-95748	4	10	):	):	PUNCT
esrj-95748	4	11	423	423	NUM
esrj-95748	4	12	-	-	SYM
esrj-95748	4	13	432	432	NUM
esrj-95748	4	14	g	g	NOUN
esrj-95748	4	15	eo	eo	INTJ
esrj-95748	4	16	lo	lo	PROPN
esrj-95748	4	17	g	g	PROPN
esrj-95748	4	18	y	y	PROPN
esrj-95748	4	19	record	record	NOUN
esrj-95748	4	20	manuscript	manuscript	NOUN
esrj-95748	4	21	received	receive	VERB
esrj-95748	4	22	:	:	PUNCT
esrj-95748	4	23	13/05/2021	13/05/2021	NUM
esrj-95748	4	24	accepted	accept	VERB
esrj-95748	4	25	for	for	ADP
esrj-95748	4	26	publication	publication	NOUN
esrj-95748	4	27	:	:	PUNCT
esrj-95748	4	28	03/11/2021	03/11/2021	NUM
esrj-95748	4	29	abstract	abstract	ADJ
esrj-95748	4	30	soil	soil	NOUN
esrj-95748	4	31	degradation	degradation	NOUN
esrj-95748	4	32	induced	induce	VERB
esrj-95748	4	33	by	by	ADP
esrj-95748	4	34	gully	gully	ADJ
esrj-95748	4	35	erosion	erosion	NOUN
esrj-95748	4	36	represents	represent	VERB
esrj-95748	4	37	a	a	DET
esrj-95748	4	38	worldwide	worldwide	ADJ
esrj-95748	4	39	problem	problem	NOUN
esrj-95748	4	40	in	in	ADP
esrj-95748	4	41	the	the	DET
esrj-95748	4	42	many	many	ADJ
esrj-95748	4	43	arid	arid	NOUN
esrj-95748	4	44	and	and	CCONJ
esrj-95748	4	45	semi	semi	ADJ
esrj-95748	4	46	-	-	ADJ
esrj-95748	4	47	arid	arid	ADJ
esrj-95748	4	48	countries	country	NOUN
esrj-95748	4	49	,	,	PUNCT
esrj-95748	4	50	such	such	ADJ
esrj-95748	4	51	as	as	ADP
esrj-95748	4	52	iran	iran	PROPN
esrj-95748	4	53	.	.	PUNCT
esrj-95748	5	1	this	this	DET
esrj-95748	5	2	study	study	NOUN
esrj-95748	5	3	assessed	assess	VERB
esrj-95748	5	4	:	:	PUNCT
esrj-95748	5	5	(	(	PUNCT
esrj-95748	5	6	1	1	X
esrj-95748	5	7	)	)	PUNCT
esrj-95748	5	8	the	the	DET
esrj-95748	5	9	importance	importance	NOUN
esrj-95748	5	10	of	of	ADP
esrj-95748	5	11	variables	variable	NOUN
esrj-95748	5	12	that	that	PRON
esrj-95748	5	13	control	control	VERB
esrj-95748	5	14	gully	gully	NOUN
esrj-95748	5	15	erosion	erosion	NOUN
esrj-95748	5	16	using	use	VERB
esrj-95748	5	17	the	the	DET
esrj-95748	5	18	boruta	boruta	NOUN
esrj-95748	5	19	algorithm	algorithm	NOUN
esrj-95748	5	20	,	,	PUNCT
esrj-95748	5	21	(	(	PUNCT
esrj-95748	5	22	2	2	X
esrj-95748	5	23	)	)	PUNCT
esrj-95748	5	24	the	the	DET
esrj-95748	5	25	relationship	relationship	NOUN
esrj-95748	5	26	among	among	ADP
esrj-95748	5	27	causative	causative	ADJ
esrj-95748	5	28	variables	variable	NOUN
esrj-95748	5	29	and	and	CCONJ
esrj-95748	5	30	gullied	gully	VERB
esrj-95748	5	31	locations	location	NOUN
esrj-95748	5	32	using	use	VERB
esrj-95748	5	33	the	the	DET
esrj-95748	5	34	evidential	evidential	ADJ
esrj-95748	5	35	belief	belief	NOUN
esrj-95748	5	36	function	function	NOUN
esrj-95748	5	37	model	model	NOUN
esrj-95748	5	38	(	(	PUNCT
esrj-95748	5	39	ebf	ebf	NOUN
esrj-95748	5	40	)	)	PUNCT
esrj-95748	5	41	,	,	PUNCT
esrj-95748	5	42	and	and	CCONJ
esrj-95748	5	43	(	(	PUNCT
esrj-95748	5	44	3	3	X
esrj-95748	5	45	)	)	PUNCT
esrj-95748	5	46	gully	gully	NOUN
esrj-95748	5	47	erosion	erosion	NOUN
esrj-95748	5	48	development	development	NOUN
esrj-95748	5	49	using	use	VERB
esrj-95748	5	50	the	the	DET
esrj-95748	5	51	algorithms	algorithm	NOUN
esrj-95748	5	52	of	of	ADP
esrj-95748	5	53	boosted	boost	VERB
esrj-95748	5	54	regression	regression	NOUN
esrj-95748	5	55	tree	tree	NOUN
esrj-95748	5	56	(	(	PUNCT
esrj-95748	5	57	brt	brt	PROPN
esrj-95748	5	58	)	)	PUNCT
esrj-95748	5	59	and	and	CCONJ
esrj-95748	5	60	support	support	VERB
esrj-95748	5	61	vector	vector	NOUN
esrj-95748	5	62	machine	machine	NOUN
esrj-95748	5	63	(	(	PUNCT
esrj-95748	5	64	svm	svm	PROPN
esrj-95748	5	65	)	)	PUNCT
esrj-95748	5	66	.	.	PUNCT
esrj-95748	6	1	based	base	VERB
esrj-95748	6	2	on	on	ADP
esrj-95748	6	3	the	the	DET
esrj-95748	6	4	results	result	NOUN
esrj-95748	6	5	of	of	ADP
esrj-95748	6	6	the	the	DET
esrj-95748	6	7	boruta	boruta	NOUN
esrj-95748	6	8	algorithm	algorithm	NOUN
esrj-95748	6	9	,	,	PUNCT
esrj-95748	6	10	slope	slope	NOUN
esrj-95748	6	11	,	,	PUNCT
esrj-95748	6	12	land	land	NOUN
esrj-95748	6	13	use	use	NOUN
esrj-95748	6	14	,	,	PUNCT
esrj-95748	6	15	lithology	lithology	NOUN
esrj-95748	6	16	,	,	PUNCT
esrj-95748	6	17	plan	plan	NOUN
esrj-95748	6	18	curvature	curvature	NOUN
esrj-95748	6	19	,	,	PUNCT
esrj-95748	6	20	and	and	CCONJ
esrj-95748	6	21	elevation	elevation	NOUN
esrj-95748	6	22	were	be	AUX
esrj-95748	6	23	the	the	DET
esrj-95748	6	24	most	most	ADV
esrj-95748	6	25	important	important	ADJ
esrj-95748	6	26	factors	factor	NOUN
esrj-95748	6	27	controlling	control	VERB
esrj-95748	6	28	gully	gully	ADJ
esrj-95748	6	29	erosion	erosion	NOUN
esrj-95748	6	30	.	.	PUNCT
esrj-95748	7	1	the	the	DET
esrj-95748	7	2	results	result	NOUN
esrj-95748	7	3	of	of	ADP
esrj-95748	7	4	the	the	DET
esrj-95748	7	5	ebf	ebf	NOUN
esrj-95748	7	6	model	model	NOUN
esrj-95748	7	7	showed	show	VERB
esrj-95748	7	8	the	the	DET
esrj-95748	7	9	predominance	predominance	NOUN
esrj-95748	7	10	of	of	ADP
esrj-95748	7	11	gully	gully	ADJ
esrj-95748	7	12	erosion	erosion	NOUN
esrj-95748	7	13	on	on	ADP
esrj-95748	7	14	rangeland	rangeland	NOUN
esrj-95748	7	15	and	and	CCONJ
esrj-95748	7	16	loess	loess	NOUN
esrj-95748	7	17	-	-	PUNCT
esrj-95748	7	18	marl	marl	NOUN
esrj-95748	7	19	deposition	deposition	NOUN
esrj-95748	7	20	.	.	PUNCT
esrj-95748	8	1	the	the	DET
esrj-95748	8	2	predominance	predominance	NOUN
esrj-95748	8	3	of	of	ADP
esrj-95748	8	4	gullied	gully	VERB
esrj-95748	8	5	locations	location	NOUN
esrj-95748	8	6	on	on	ADP
esrj-95748	8	7	the	the	DET
esrj-95748	8	8	concave	concave	ADJ
esrj-95748	8	9	positions	position	NOUN
esrj-95748	8	10	,	,	PUNCT
esrj-95748	8	11	with	with	ADP
esrj-95748	8	12	the	the	DET
esrj-95748	8	13	slope	slope	NOUN
esrj-95748	8	14	of	of	ADP
esrj-95748	8	15	5	5	NUM
esrj-95748	8	16	°	°	NOUN
esrj-95748	8	17	–20	–20	NOUN
esrj-95748	8	18	°	°	NOUN
esrj-95748	8	19	in	in	ADP
esrj-95748	8	20	the	the	DET
esrj-95748	8	21	vicinity	vicinity	NOUN
esrj-95748	8	22	of	of	ADP
esrj-95748	8	23	drainage	drainage	NOUN
esrj-95748	8	24	lines	line	NOUN
esrj-95748	8	25	,	,	PUNCT
esrj-95748	8	26	illustrates	illustrate	VERB
esrj-95748	8	27	a	a	DET
esrj-95748	8	28	preferential	preferential	ADJ
esrj-95748	8	29	topographic	topographic	NOUN
esrj-95748	8	30	zone	zone	NOUN
esrj-95748	8	31	and	and	CCONJ
esrj-95748	8	32	,	,	PUNCT
esrj-95748	8	33	therefore	therefore	ADV
esrj-95748	8	34	,	,	PUNCT
esrj-95748	8	35	a	a	DET
esrj-95748	8	36	terrain	terrain	NOUN
esrj-95748	8	37	threshold	threshold	NOUN
esrj-95748	8	38	for	for	ADP
esrj-95748	8	39	gullying	gullye	VERB
esrj-95748	8	40	.	.	PUNCT
esrj-95748	9	1	the	the	DET
esrj-95748	9	2	correlation	correlation	NOUN
esrj-95748	9	3	of	of	ADP
esrj-95748	9	4	gullied	gully	VERB
esrj-95748	9	5	locations	location	NOUN
esrj-95748	9	6	with	with	ADP
esrj-95748	9	7	rangelands	rangeland	NOUN
esrj-95748	9	8	and	and	CCONJ
esrj-95748	9	9	weak	weak	ADJ
esrj-95748	9	10	soils	soil	NOUN
esrj-95748	9	11	in	in	ADP
esrj-95748	9	12	concave	concave	ADJ
esrj-95748	9	13	positions	position	NOUN
esrj-95748	9	14	demonstrates	demonstrate	VERB
esrj-95748	9	15	that	that	SCONJ
esrj-95748	9	16	the	the	DET
esrj-95748	9	17	interactions	interaction	NOUN
esrj-95748	9	18	among	among	ADP
esrj-95748	9	19	soil	soil	NOUN
esrj-95748	9	20	characteristics	characteristic	NOUN
esrj-95748	9	21	,	,	PUNCT
esrj-95748	9	22	topography	topography	NOUN
esrj-95748	9	23	,	,	PUNCT
esrj-95748	9	24	and	and	CCONJ
esrj-95748	9	25	land	land	NOUN
esrj-95748	9	26	use	use	NOUN
esrj-95748	9	27	stimulate	stimulate	VERB
esrj-95748	9	28	a	a	DET
esrj-95748	9	29	low	low	ADJ
esrj-95748	9	30	topographic	topographic	ADJ
esrj-95748	9	31	threshold	threshold	NOUN
esrj-95748	9	32	for	for	ADP
esrj-95748	9	33	gullies	gully	NOUN
esrj-95748	9	34	development	development	NOUN
esrj-95748	9	35	.	.	PUNCT
esrj-95748	10	1	these	these	DET
esrj-95748	10	2	relationships	relationship	NOUN
esrj-95748	10	3	are	be	AUX
esrj-95748	10	4	consistent	consistent	ADJ
esrj-95748	10	5	with	with	ADP
esrj-95748	10	6	the	the	DET
esrj-95748	10	7	threshold	threshold	NOUN
esrj-95748	10	8	concept	concept	NOUN
esrj-95748	10	9	that	that	SCONJ
esrj-95748	10	10	a	a	DET
esrj-95748	10	11	given	give	VERB
esrj-95748	10	12	soil	soil	NOUN
esrj-95748	10	13	,	,	PUNCT
esrj-95748	10	14	land	land	NOUN
esrj-95748	10	15	use	use	NOUN
esrj-95748	10	16	,	,	PUNCT
esrj-95748	10	17	and	and	CCONJ
esrj-95748	10	18	climate	climate	NOUN
esrj-95748	10	19	within	within	ADP
esrj-95748	10	20	a	a	DET
esrj-95748	10	21	given	give	VERB
esrj-95748	10	22	landscape	landscape	NOUN
esrj-95748	10	23	encourage	encourage	VERB
esrj-95748	10	24	a	a	DET
esrj-95748	10	25	given	give	VERB
esrj-95748	10	26	drainage	drainage	NOUN
esrj-95748	10	27	area	area	NOUN
esrj-95748	10	28	and	and	CCONJ
esrj-95748	10	29	a	a	DET
esrj-95748	10	30	critical	critical	ADJ
esrj-95748	10	31	soil	soil	NOUN
esrj-95748	10	32	surface	surface	NOUN
esrj-95748	10	33	slope	slope	NOUN
esrj-95748	10	34	that	that	PRON
esrj-95748	10	35	are	be	AUX
esrj-95748	10	36	necessary	necessary	ADJ
esrj-95748	10	37	for	for	ADP
esrj-95748	10	38	gully	gully	ADJ
esrj-95748	10	39	incision	incision	NOUN
esrj-95748	10	40	.	.	PUNCT
esrj-95748	11	1	furthermore	furthermore	ADV
esrj-95748	11	2	,	,	PUNCT
esrj-95748	11	3	the	the	DET
esrj-95748	11	4	brf	brf	NOUN
esrj-95748	11	5	-	-	PUNCT
esrj-95748	11	6	svm	svm	PROPN
esrj-95748	11	7	had	have	VERB
esrj-95748	11	8	the	the	DET
esrj-95748	11	9	highest	high	ADJ
esrj-95748	11	10	efficiency	efficiency	NOUN
esrj-95748	11	11	and	and	CCONJ
esrj-95748	11	12	the	the	DET
esrj-95748	11	13	lowest	low	ADJ
esrj-95748	11	14	root	root	NOUN
esrj-95748	11	15	mean	mean	ADJ
esrj-95748	11	16	square	square	NOUN
esrj-95748	11	17	error	error	NOUN
esrj-95748	11	18	,	,	PUNCT
esrj-95748	11	19	followed	follow	VERB
esrj-95748	11	20	by	by	ADP
esrj-95748	11	21	brt	brt	PROPN
esrj-95748	11	22	for	for	ADP
esrj-95748	11	23	predicting	predict	VERB
esrj-95748	11	24	gully	gully	NOUN
esrj-95748	11	25	development	development	NOUN
esrj-95748	11	26	,	,	PUNCT
esrj-95748	11	27	compared	compare	VERB
esrj-95748	11	28	with	with	ADP
esrj-95748	11	29	ln	ln	ADJ
esrj-95748	11	30	-	-	PUNCT
esrj-95748	11	31	svm	svm	ADJ
esrj-95748	11	32	algorithm	algorithm	NOUN
esrj-95748	11	33	.	.	PUNCT
esrj-95748	12	1	the	the	DET
esrj-95748	12	2	application	application	NOUN
esrj-95748	12	3	of	of	ADP
esrj-95748	12	4	two	two	NUM
esrj-95748	12	5	machine	machine	NOUN
esrj-95748	12	6	learning	learn	VERB
esrj-95748	12	7	methods	method	NOUN
esrj-95748	12	8	for	for	ADP
esrj-95748	12	9	predicting	predict	VERB
esrj-95748	12	10	the	the	DET
esrj-95748	12	11	gully	gully	ADJ
esrj-95748	12	12	head	head	NOUN
esrj-95748	12	13	cut	cut	VERB
esrj-95748	12	14	susceptibility	susceptibility	NOUN
esrj-95748	12	15	in	in	ADP
esrj-95748	12	16	northern	northern	ADJ
esrj-95748	12	17	iran	iran	PROPN
esrj-95748	12	18	showed	show	VERB
esrj-95748	12	19	that	that	SCONJ
esrj-95748	12	20	the	the	DET
esrj-95748	12	21	maps	map	NOUN
esrj-95748	12	22	generated	generate	VERB
esrj-95748	12	23	by	by	ADP
esrj-95748	12	24	these	these	DET
esrj-95748	12	25	algorithms	algorithm	NOUN
esrj-95748	12	26	could	could	AUX
esrj-95748	12	27	provide	provide	VERB
esrj-95748	12	28	an	an	DET
esrj-95748	12	29	appropriate	appropriate	ADJ
esrj-95748	12	30	strategy	strategy	NOUN
esrj-95748	12	31	for	for	ADP
esrj-95748	12	32	geo	geo	PROPN
esrj-95748	12	33	-	-	PUNCT
esrj-95748	12	34	conservation	conservation	NOUN
esrj-95748	12	35	and	and	CCONJ
esrj-95748	12	36	restoration	restoration	NOUN
esrj-95748	12	37	efforts	effort	NOUN
esrj-95748	12	38	in	in	ADP
esrj-95748	12	39	gullying	gullye	VERB
esrj-95748	12	40	-	-	PUNCT
esrj-95748	12	41	prone	prone	ADJ
esrj-95748	12	42	areas	area	NOUN
esrj-95748	12	43	.	.	PUNCT
esrj-95748	13	1	factores	factores	PROPN
esrj-95748	13	2	que	que	PROPN
esrj-95748	13	3	afectan	afectan	PROPN
esrj-95748	13	4	los	los	PROPN
esrj-95748	13	5	umbrales	umbrales	PROPN
esrj-95748	13	6	topográficos	topográficos	PROPN
esrj-95748	13	7	en	en	X
esrj-95748	13	8	la	la	PROPN
esrj-95748	13	9	ocurrencia	ocurrencia	PROPN
esrj-95748	13	10	de	de	ADP
esrj-95748	13	11	erosión	erosión	PROPN
esrj-95748	13	12	y	y	PROPN
esrj-95748	13	13	su	su	PROPN
esrj-95748	13	14	manejo	manejo	PROPN
esrj-95748	13	15	a	a	DET
esrj-95748	13	16	través	través	PROPN
esrj-95748	13	17	de	de	X
esrj-95748	13	18	modelos	modelos	PROPN
esrj-95748	13	19	predictivos	predictivos	PROPN
esrj-95748	13	20	de	de	PROPN
esrj-95748	13	21	aprendizaje	aprendizaje	PROPN
esrj-95748	13	22	automático	automático	NOUN
esrj-95748	13	23	resumen	resuman	NOUN
esrj-95748	13	24	la	la	DET
esrj-95748	13	25	degradación	degradación	PROPN
esrj-95748	13	26	del	del	PROPN
esrj-95748	13	27	suelo	suelo	PROPN
esrj-95748	13	28	por	por	PROPN
esrj-95748	13	29	erosión	erosión	NOUN
esrj-95748	13	30	representa	representa	PROPN
esrj-95748	13	31	un	un	PROPN
esrj-95748	13	32	problema	problema	PROPN
esrj-95748	13	33	generalizado	generalizado	PROPN
esrj-95748	13	34	para	para	PROPN
esrj-95748	13	35	aquellos	aquellos	PROPN
esrj-95748	13	36	países	paíse	VERB
esrj-95748	13	37	con	con	PROPN
esrj-95748	13	38	suelos	suelos	PROPN
esrj-95748	13	39	áridos	áridos	PROPN
esrj-95748	13	40	y	y	PROPN
esrj-95748	13	41	semiáridos	semiárido	VERB
esrj-95748	13	42	como	como	PROPN
esrj-95748	13	43	iran	iran	PROPN
esrj-95748	13	44	.	.	PUNCT
esrj-95748	14	1	en	en	X
esrj-95748	14	2	este	este	PROPN
esrj-95748	14	3	estudio	estudio	PROPN
esrj-95748	14	4	se	se	X
esrj-95748	14	5	miden	miden	PROPN
esrj-95748	14	6	los	los	PROPN
esrj-95748	14	7	siguientes	siguiente	VERB
esrj-95748	14	8	aspectos	aspecto	NOUN
esrj-95748	14	9	:	:	PUNCT
esrj-95748	14	10	1	1	X
esrj-95748	14	11	.	.	X
esrj-95748	14	12	la	la	PROPN
esrj-95748	14	13	importancia	importancia	PROPN
esrj-95748	14	14	de	de	ADP
esrj-95748	14	15	las	las	PROPN
esrj-95748	14	16	variables	variables	PROPN
esrj-95748	14	17	que	que	PROPN
esrj-95748	14	18	controlan	controlan	NOUN
esrj-95748	14	19	la	la	PROPN
esrj-95748	14	20	erosión	erosión	PROPN
esrj-95748	14	21	a	a	DET
esrj-95748	14	22	través	través	NOUN
esrj-95748	14	23	del	del	X
esrj-95748	14	24	algoritmo	algoritmo	PROPN
esrj-95748	14	25	de	de	PROPN
esrj-95748	14	26	boruta	boruta	PROPN
esrj-95748	14	27	;	;	PUNCT
esrj-95748	14	28	2	2	X
esrj-95748	14	29	.	.	X
esrj-95748	14	30	la	la	PROPN
esrj-95748	14	31	relación	relación	PROPN
esrj-95748	14	32	entre	entre	PROPN
esrj-95748	14	33	causales	causales	PROPN
esrj-95748	14	34	y	y	PROPN
esrj-95748	14	35	los	los	PROPN
esrj-95748	14	36	lugares	lugares	PROPN
esrj-95748	14	37	erosionados	erosionado	NOUN
esrj-95748	14	38	a	a	DET
esrj-95748	14	39	través	través	PROPN
esrj-95748	14	40	del	del	PROPN
esrj-95748	14	41	modelo	modelo	PROPN
esrj-95748	14	42	de	de	PROPN
esrj-95748	14	43	confianza	confianza	PROPN
esrj-95748	14	44	(	(	PUNCT
esrj-95748	14	45	ebf	ebf	PROPN
esrj-95748	14	46	,	,	PUNCT
esrj-95748	14	47	del	del	PROPN
esrj-95748	14	48	inglés	inglés	X
esrj-95748	14	49	evidential	evidential	ADJ
esrj-95748	14	50	belief	belief	NOUN
esrj-95748	14	51	function	function	NOUN
esrj-95748	14	52	model	model	NOUN
esrj-95748	14	53	)	)	PUNCT
esrj-95748	14	54	,	,	PUNCT
esrj-95748	14	55	y	y	PROPN
esrj-95748	14	56	3	3	NUM
esrj-95748	14	57	.	.	PUNCT
esrj-95748	14	58	desarrollo	desarrollo	PROPN
esrj-95748	14	59	de	de	PROPN
esrj-95748	14	60	la	la	PROPN
esrj-95748	14	61	erosión	erosión	PROPN
esrj-95748	14	62	a	a	PRON
esrj-95748	14	63	través	través	X
esrj-95748	14	64	de	de	X
esrj-95748	14	65	los	los	PROPN
esrj-95748	14	66	algoritmos	algoritmos	PROPN
esrj-95748	14	67	árboles	árboles	PROPN
esrj-95748	14	68	de	de	PROPN
esrj-95748	14	69	regresión	regresión	PROPN
esrj-95748	14	70	potenciado	potenciado	NOUN
esrj-95748	14	71	(	(	PUNCT
esrj-95748	14	72	brt	brt	PROPN
esrj-95748	14	73	,	,	PUNCT
esrj-95748	14	74	boosted	boost	VERB
esrj-95748	14	75	regression	regression	NOUN
esrj-95748	14	76	tree	tree	NOUN
esrj-95748	14	77	)	)	PUNCT
esrj-95748	14	78	y	y	PROPN
esrj-95748	14	79	máquinas	máquinas	PROPN
esrj-95748	14	80	de	de	PROPN
esrj-95748	14	81	vectores	vectores	PROPN
esrj-95748	14	82	de	de	PROPN
esrj-95748	14	83	soporte	soporte	X
esrj-95748	14	84	(	(	PUNCT
esrj-95748	14	85	svm	svm	PROPN
esrj-95748	14	86	,	,	PUNCT
esrj-95748	14	87	support	support	NOUN
esrj-95748	14	88	vector	vector	NOUN
esrj-95748	14	89	machine	machine	NOUN
esrj-95748	14	90	)	)	PUNCT
esrj-95748	14	91	.	.	PUNCT
esrj-95748	15	1	con	con	PROPN
esrj-95748	15	2	base	base	PROPN
esrj-95748	15	3	en	en	ADP
esrj-95748	15	4	los	los	PROPN
esrj-95748	15	5	resultados	resultados	PROPN
esrj-95748	15	6	del	del	PROPN
esrj-95748	15	7	algoritmo	algoritmo	PROPN
esrj-95748	15	8	de	de	PROPN
esrj-95748	15	9	boruta	boruta	PROPN
esrj-95748	15	10	,	,	PUNCT
esrj-95748	15	11	la	la	PROPN
esrj-95748	15	12	inclinación	inclinación	PROPN
esrj-95748	15	13	,	,	PUNCT
esrj-95748	15	14	el	el	PROPN
esrj-95748	15	15	uso	uso	PROPN
esrj-95748	15	16	del	del	PROPN
esrj-95748	15	17	suelo	suelo	NOUN
esrj-95748	15	18	,	,	PUNCT
esrj-95748	15	19	la	la	PROPN
esrj-95748	15	20	litología	litología	NOUN
esrj-95748	15	21	,	,	PUNCT
esrj-95748	15	22	la	la	PROPN
esrj-95748	15	23	curvatura	curvatura	PROPN
esrj-95748	15	24	y	y	PROPN
esrj-95748	15	25	la	la	PROPN
esrj-95748	15	26	elevación	elevación	PROPN
esrj-95748	15	27	son	son	PROPN
esrj-95748	15	28	los	los	PROPN
esrj-95748	15	29	factores	factores	PROPN
esrj-95748	15	30	más	más	PROPN
esrj-95748	15	31	importantes	importante	NOUN
esrj-95748	15	32	en	en	ADP
esrj-95748	15	33	el	el	PROPN
esrj-95748	15	34	control	control	PROPN
esrj-95748	15	35	de	de	PROPN
esrj-95748	15	36	la	la	PROPN
esrj-95748	15	37	erosión	erosión	NOUN
esrj-95748	15	38	.	.	PUNCT
esrj-95748	16	1	los	los	PROPN
esrj-95748	16	2	resultados	resultado	VERB
esrj-95748	16	3	del	del	PROPN
esrj-95748	16	4	modelo	modelo	PROPN
esrj-95748	16	5	de	de	PROPN
esrj-95748	16	6	confianza	confianza	PROPN
esrj-95748	16	7	muestran	muestran	NOUN
esrj-95748	16	8	la	la	X
esrj-95748	16	9	predominancia	predominancia	PROPN
esrj-95748	16	10	de	de	X
esrj-95748	16	11	la	la	X
esrj-95748	16	12	erosión	erosión	PROPN
esrj-95748	16	13	en	en	X
esrj-95748	16	14	los	los	PROPN
esrj-95748	16	15	pastizales	pastizales	PROPN
esrj-95748	16	16	y	y	PROPN
esrj-95748	16	17	en	en	PROPN
esrj-95748	16	18	las	las	PROPN
esrj-95748	16	19	deposiciones	deposiciones	PROPN
esrj-95748	16	20	de	de	PROPN
esrj-95748	16	21	marga	marga	PROPN
esrj-95748	16	22	de	de	PROPN
esrj-95748	16	23	loess	loess	PROPN
esrj-95748	16	24	.	.	PUNCT
esrj-95748	17	1	la	la	PROPN
esrj-95748	17	2	predominancia	predominancia	PROPN
esrj-95748	17	3	de	de	ADP
esrj-95748	17	4	lugares	lugare	NOUN
esrj-95748	17	5	erosionados	erosionado	NOUN
esrj-95748	17	6	en	en	ADP
esrj-95748	17	7	puntos	puntos	PROPN
esrj-95748	17	8	cóncavos	cóncavos	PROPN
esrj-95748	17	9	,	,	PUNCT
esrj-95748	17	10	con	con	PROPN
esrj-95748	17	11	una	una	X
esrj-95748	17	12	pendiente	pendiente	PROPN
esrj-95748	17	13	de	de	X
esrj-95748	17	14	entre	entre	PROPN
esrj-95748	17	15	5	5	NUM
esrj-95748	17	16	y	y	PROPN
esrj-95748	17	17	20	20	NUM
esrj-95748	17	18	grados	grado	NOUN
esrj-95748	17	19	junto	junto	VERB
esrj-95748	17	20	a	a	DET
esrj-95748	17	21	líneas	línea	NOUN
esrj-95748	17	22	de	de	X
esrj-95748	17	23	drenaje	drenaje	NOUN
esrj-95748	17	24	,	,	PUNCT
esrj-95748	17	25	ejemplifica	ejemplifica	PROPN
esrj-95748	18	1	una	una	PROPN
esrj-95748	18	2	zona	zona	PROPN
esrj-95748	18	3	topográfica	topográfica	PROPN
esrj-95748	18	4	preferencial	preferencial	PROPN
esrj-95748	18	5	y	y	PROPN
esrj-95748	18	6	,	,	PUNCT
esrj-95748	18	7	además	además	PROPN
esrj-95748	18	8	,	,	PUNCT
esrj-95748	18	9	un	un	PROPN
esrj-95748	18	10	umbral	umbral	PROPN
esrj-95748	18	11	en	en	PROPN
esrj-95748	18	12	el	el	PROPN
esrj-95748	18	13	terreno	terreno	PROPN
esrj-95748	18	14	para	para	PROPN
esrj-95748	18	15	la	la	PROPN
esrj-95748	18	16	erosión	erosión	NOUN
esrj-95748	18	17	.	.	PUNCT
esrj-95748	19	1	la	la	DET
esrj-95748	19	2	correlación	correlación	PROPN
esrj-95748	19	3	de	de	PROPN
esrj-95748	19	4	zonas	zonas	PROPN
esrj-95748	19	5	erosionadas	erosionadas	ADP
esrj-95748	19	6	con	con	PROPN
esrj-95748	19	7	pastizales	pastizales	PROPN
esrj-95748	19	8	y	y	PROPN
esrj-95748	19	9	suelos	suelos	PROPN
esrj-95748	19	10	débiles	débiles	PROPN
esrj-95748	19	11	en	en	ADP
esrj-95748	19	12	posiciones	posiciones	PROPN
esrj-95748	19	13	cóncavas	cóncavas	PROPN
esrj-95748	19	14	demuestra	demuestra	PROPN
esrj-95748	19	15	que	que	PROPN
esrj-95748	19	16	las	las	PROPN
esrj-95748	19	17	interacciones	interacciones	PROPN
esrj-95748	19	18	entre	entre	PROPN
esrj-95748	19	19	las	las	PROPN
esrj-95748	19	20	características	características	PROPN
esrj-95748	19	21	del	del	PROPN
esrj-95748	19	22	suelo	suelo	NOUN
esrj-95748	19	23	,	,	PUNCT
esrj-95748	19	24	la	la	PROPN
esrj-95748	19	25	topografía	topografía	PROPN
esrj-95748	19	26	,	,	PUNCT
esrj-95748	19	27	y	y	PROPN
esrj-95748	19	28	el	el	PROPN
esrj-95748	19	29	estudio	estudio	PROPN
esrj-95748	19	30	del	del	PROPN
esrj-95748	19	31	suelo	suelo	PROPN
esrj-95748	19	32	estimulan	estimulan	PROPN
esrj-95748	19	33	un	un	PROPN
esrj-95748	19	34	umbral	umbral	PROPN
esrj-95748	19	35	bajo	bajo	PROPN
esrj-95748	19	36	para	para	PROPN
esrj-95748	19	37	el	el	PROPN
esrj-95748	19	38	desarrollo	desarrollo	PROPN
esrj-95748	19	39	de	de	PROPN
esrj-95748	19	40	la	la	PROPN
esrj-95748	19	41	erosión	erosión	NOUN
esrj-95748	19	42	.	.	PUNCT
esrj-95748	20	1	estas	estas	PROPN
esrj-95748	20	2	relaciones	relaciones	PROPN
esrj-95748	20	3	se	se	PROPN
esrj-95748	20	4	enmarcan	enmarcan	PROPN
esrj-95748	20	5	en	en	PROPN
esrj-95748	20	6	el	el	PROPN
esrj-95748	20	7	concepto	concepto	PROPN
esrj-95748	20	8	de	de	PROPN
esrj-95748	20	9	que	que	PROPN
esrj-95748	20	10	ante	ante	PROPN
esrj-95748	20	11	un	un	PROPN
esrj-95748	20	12	tipo	tipo	PROPN
esrj-95748	20	13	de	de	X
esrj-95748	20	14	suelo	suelo	PROPN
esrj-95748	20	15	dado	dado	NOUN
esrj-95748	20	16	,	,	PUNCT
esrj-95748	20	17	el	el	PROPN
esrj-95748	20	18	uso	uso	PROPN
esrj-95748	20	19	que	que	PROPN
esrj-95748	20	20	se	se	X
esrj-95748	20	21	le	le	AUX
esrj-95748	20	22	brinde	brinde	PROPN
esrj-95748	20	23	y	y	PROPN
esrj-95748	20	24	el	el	PROPN
esrj-95748	20	25	clima	clima	PROPN
esrj-95748	20	26	en	en	PROPN
esrj-95748	20	27	un	un	PROPN
esrj-95748	20	28	paisaje	paisaje	PROPN
esrj-95748	20	29	específico	específico	PROPN
esrj-95748	20	30	se	se	PROPN
esrj-95748	20	31	crea	crea	PROPN
esrj-95748	20	32	una	una	PROPN
esrj-95748	20	33	área	área	PROPN
esrj-95748	20	34	de	de	PROPN
esrj-95748	20	35	drenaje	drenaje	PROPN
esrj-95748	20	36	y	y	PROPN
esrj-95748	20	37	una	una	PROPN
esrj-95748	20	38	pendiente	pendiente	PROPN
esrj-95748	20	39	con	con	PROPN
esrj-95748	20	40	superficie	superficie	PROPN
esrj-95748	20	41	de	de	X
esrj-95748	20	42	suelo	suelo	NOUN
esrj-95748	20	43	crítico	crítico	NOUN
esrj-95748	20	44	,	,	PUNCT
esrj-95748	20	45	necesarios	necesarios	X
esrj-95748	20	46	para	para	PROPN
esrj-95748	20	47	un	un	PROPN
esrj-95748	20	48	corte	corte	PROPN
esrj-95748	20	49	erosionado	erosionado	PROPN
esrj-95748	20	50	.	.	PUNCT
esrj-95748	21	1	además	además	PROPN
esrj-95748	21	2	,	,	PUNCT
esrj-95748	21	3	los	los	PROPN
esrj-95748	21	4	algoritmos	algoritmos	PROPN
esrj-95748	21	5	brf	brf	PROPN
esrj-95748	21	6	-	-	PUNCT
esrj-95748	21	7	svm	svm	PROPN
esrj-95748	21	8	tuvieron	tuvieron	PROPN
esrj-95748	21	9	la	la	PROPN
esrj-95748	21	10	mayor	mayor	PROPN
esrj-95748	21	11	eficiencia	eficiencia	PROPN
esrj-95748	21	12	y	y	PROPN
esrj-95748	21	13	el	el	PROPN
esrj-95748	21	14	menor	menor	PROPN
esrj-95748	21	15	error	error	NOUN
esrj-95748	21	16	cuadrático	cuadrático	NOUN
esrj-95748	21	17	medio	medio	NOUN
esrj-95748	21	18	,	,	PUNCT
esrj-95748	21	19	seguido	seguido	NOUN
esrj-95748	21	20	por	por	PROPN
esrj-95748	21	21	el	el	PROPN
esrj-95748	21	22	brt	brt	PROPN
esrj-95748	21	23	en	en	PROPN
esrj-95748	21	24	la	la	PROPN
esrj-95748	21	25	predicción	predicción	PROPN
esrj-95748	21	26	del	del	PROPN
esrj-95748	21	27	desarrollo	desarrollo	PROPN
esrj-95748	21	28	de	de	PROPN
esrj-95748	21	29	erosión	erosión	PROPN
esrj-95748	21	30	frente	frente	PROPN
esrj-95748	21	31	al	al	PROPN
esrj-95748	21	32	algortimo	algortimo	VERB
esrj-95748	21	33	ln	ln	ADJ
esrj-95748	21	34	-	-	PUNCT
esrj-95748	21	35	svm	svm	ADJ
esrj-95748	21	36	.	.	PUNCT
esrj-95748	21	37	la	la	PROPN
esrj-95748	21	38	aplicación	aplicación	PROPN
esrj-95748	21	39	de	de	PROPN
esrj-95748	21	40	dos	dos	PROPN
esrj-95748	21	41	métodos	métodos	PROPN
esrj-95748	21	42	de	de	PROPN
esrj-95748	21	43	aprendizaje	aprendizaje	PROPN
esrj-95748	21	44	automático	automático	PROPN
esrj-95748	21	45	para	para	PROPN
esrj-95748	21	46	para	para	PROPN
esrj-95748	21	47	predecir	predecir	PROPN
esrj-95748	21	48	la	la	PRON
esrj-95748	21	49	susceptibilidad	susceptibilidad	PROPN
esrj-95748	21	50	de	de	PROPN
esrj-95748	21	51	corte	corte	PROPN
esrj-95748	21	52	en	en	PROPN
esrj-95748	21	53	el	el	PROPN
esrj-95748	21	54	norte	norte	PROPN
esrj-95748	21	55	de	de	PROPN
esrj-95748	21	56	irán	irán	PROPN
esrj-95748	21	57	muestra	muestra	ADJ
esrj-95748	21	58	que	que	X
esrj-95748	21	59	los	los	PROPN
esrj-95748	21	60	mapas	mapas	PROPN
esrj-95748	21	61	generados	generados	PROPN
esrj-95748	21	62	por	por	VERB
esrj-95748	21	63	estos	estos	PROPN
esrj-95748	21	64	algortimos	algortimos	PROPN
esrj-95748	21	65	pueden	pueden	PROPN
esrj-95748	21	66	proveer	proveer	PROPN
esrj-95748	21	67	una	una	PROPN
esrj-95748	21	68	estrategia	estrategia	PROPN
esrj-95748	21	69	apropiada	apropiada	PROPN
esrj-95748	21	70	para	para	PROPN
esrj-95748	22	1	la	la	PROPN
esrj-95748	22	2	geoconservación	geoconservación	PROPN
esrj-95748	22	3	y	y	PROPN
esrj-95748	22	4	los	los	PROPN
esrj-95748	22	5	esfuerzos	esfuerzos	PROPN
esrj-95748	22	6	de	de	PROPN
esrj-95748	22	7	restauración	restauración	PROPN
esrj-95748	22	8	en	en	PROPN
esrj-95748	22	9	zonas	zona	NOUN
esrj-95748	22	10	propensas	propensa	NOUN
esrj-95748	22	11	a	a	DET
esrj-95748	22	12	la	la	PROPN
esrj-95748	22	13	erosión	erosión	NOUN
esrj-95748	22	14	.	.	PUNCT
esrj-95748	23	1	how	how	SCONJ
esrj-95748	23	2	to	to	PART
esrj-95748	23	3	cite	cite	VERB
esrj-95748	23	4	item	item	NOUN
esrj-95748	23	5	:	:	PUNCT
esrj-95748	23	6	valipour	valipour	ADJ
esrj-95748	23	7	,	,	PUNCT
esrj-95748	23	8	m.	m.	NOUN
esrj-95748	23	9	,	,	PUNCT
esrj-95748	23	10	mohseni	mohseni	NOUN
esrj-95748	23	11	,	,	PUNCT
esrj-95748	23	12	n.	n.	NOUN
esrj-95748	23	13	,	,	PUNCT
esrj-95748	23	14	&	&	CCONJ
esrj-95748	23	15	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	23	16	,	,	PUNCT
esrj-95748	23	17	s.	s.	PROPN
esrj-95748	23	18	r.	r.	PROPN
esrj-95748	23	19	(	(	PUNCT
esrj-95748	23	20	2021	2021	NUM
esrj-95748	23	21	)	)	PUNCT
esrj-95748	23	22	.	.	PUNCT
esrj-95748	24	1	factors	factor	NOUN
esrj-95748	24	2	affecting	affect	VERB
esrj-95748	24	3	topographic	topographic	ADJ
esrj-95748	24	4	thresholds	threshold	NOUN
esrj-95748	24	5	in	in	ADP
esrj-95748	24	6	gully	gully	ADJ
esrj-95748	24	7	erosion	erosion	NOUN
esrj-95748	24	8	occurrence	occurrence	NOUN
esrj-95748	24	9	and	and	CCONJ
esrj-95748	24	10	its	its	PRON
esrj-95748	24	11	management	management	NOUN
esrj-95748	24	12	using	use	VERB
esrj-95748	24	13	predictive	predictive	ADJ
esrj-95748	24	14	machine	machine	NOUN
esrj-95748	24	15	learning	learning	NOUN
esrj-95748	24	16	models	model	NOUN
esrj-95748	24	17	.	.	PUNCT
esrj-95748	25	1	earth	earth	NOUN
esrj-95748	25	2	sciences	sciences	PROPN
esrj-95748	25	3	research	research	PROPN
esrj-95748	25	4	journal	journal	NOUN
esrj-95748	25	5	,	,	PUNCT
esrj-95748	25	6	25(4	25(4	PROPN
esrj-95748	25	7	)	)	PUNCT
esrj-95748	25	8	,	,	PUNCT
esrj-95748	25	9	423	423	NUM
esrj-95748	25	10	-	-	SYM
esrj-95748	25	11	432	432	NUM
esrj-95748	25	12	.	.	PUNCT
esrj-95748	26	1	https://doi.org/10.15446/esrj	https://doi.org/10.15446/esrj	NOUN
esrj-95748	26	2	.	.	PUNCT
esrj-95748	27	1	v25n4.95748	v25n4.95748	PROPN
esrj-95748	28	1	mailto:nedamohseni@um.ac.ir	mailto:nedamohseni@um.ac.ir	VERB
esrj-95748	28	2	https://doi.org/10.15446/esrj.v25n1.74167	https://doi.org/10.15446/esrj.v25n1.74167	ADV
esrj-95748	28	3	https://doi.org/10.15446/esrj.v25n4.95748	https://doi.org/10.15446/esrj.v25n4.95748	X
esrj-95748	28	4	https://doi.org/10.15446/esrj.v25n4.95748	https://doi.org/10.15446/esrj.v25n4.95748	X
esrj-95748	28	5	424	424	NUM
esrj-95748	28	6	mahdieh	mahdieh	PROPN
esrj-95748	28	7	valipour	valipour	NOUN
esrj-95748	28	8	,	,	PUNCT
esrj-95748	28	9	neda	neda	PROPN
esrj-95748	28	10	mohseni	mohseni	NOUN
esrj-95748	28	11	,	,	PUNCT
esrj-95748	28	12	seyed	seyed	PROPN
esrj-95748	28	13	reza	reza	PROPN
esrj-95748	28	14	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	28	15	introduction	introduction	NOUN
esrj-95748	28	16	detachment	detachment	NOUN
esrj-95748	28	17	and	and	CCONJ
esrj-95748	28	18	transportation	transportation	NOUN
esrj-95748	28	19	of	of	ADP
esrj-95748	28	20	soil	soil	NOUN
esrj-95748	28	21	particles	particle	NOUN
esrj-95748	28	22	by	by	ADP
esrj-95748	28	23	overland	overland	NOUN
esrj-95748	28	24	flow	flow	NOUN
esrj-95748	28	25	are	be	AUX
esrj-95748	28	26	the	the	DET
esrj-95748	28	27	most	most	ADV
esrj-95748	28	28	important	important	ADJ
esrj-95748	28	29	causes	cause	NOUN
esrj-95748	28	30	of	of	ADP
esrj-95748	28	31	land	land	NOUN
esrj-95748	28	32	degradation	degradation	NOUN
esrj-95748	28	33	in	in	ADP
esrj-95748	28	34	water	water	NOUN
esrj-95748	28	35	erosion	erosion	NOUN
esrj-95748	28	36	-	-	PUNCT
esrj-95748	28	37	prone	prone	ADJ
esrj-95748	28	38	environments	environment	NOUN
esrj-95748	28	39	(	(	PUNCT
esrj-95748	28	40	ollobarren	ollobarren	PROPN
esrj-95748	28	41	et	et	PROPN
esrj-95748	28	42	al	al	PROPN
esrj-95748	28	43	.	.	PROPN
esrj-95748	28	44	,	,	PUNCT
esrj-95748	28	45	2016	2016	NUM
esrj-95748	28	46	)	)	PUNCT
esrj-95748	28	47	.	.	PUNCT
esrj-95748	29	1	different	different	ADJ
esrj-95748	29	2	stages	stage	NOUN
esrj-95748	29	3	of	of	ADP
esrj-95748	29	4	linear	linear	ADJ
esrj-95748	29	5	erosion	erosion	NOUN
esrj-95748	29	6	development	development	NOUN
esrj-95748	29	7	,	,	PUNCT
esrj-95748	29	8	such	such	ADJ
esrj-95748	29	9	as	as	ADP
esrj-95748	29	10	rilling	rille	VERB
esrj-95748	29	11	and	and	CCONJ
esrj-95748	29	12	gullying	gullying	NOUN
esrj-95748	29	13	,	,	PUNCT
esrj-95748	29	14	irreversibly	irreversibly	ADV
esrj-95748	29	15	affect	affect	VERB
esrj-95748	29	16	the	the	DET
esrj-95748	29	17	health	health	NOUN
esrj-95748	29	18	and	and	CCONJ
esrj-95748	29	19	resilience	resilience	NOUN
esrj-95748	29	20	of	of	ADP
esrj-95748	29	21	soil	soil	NOUN
esrj-95748	29	22	systems	system	NOUN
esrj-95748	29	23	(	(	PUNCT
esrj-95748	29	24	su	su	PROPN
esrj-95748	29	25	et	et	PROPN
esrj-95748	29	26	al	al	PROPN
esrj-95748	29	27	.	.	PROPN
esrj-95748	29	28	,	,	PUNCT
esrj-95748	29	29	2010	2010	NUM
esrj-95748	29	30	;	;	PUNCT
esrj-95748	29	31	chaplot	chaplot	NOUN
esrj-95748	29	32	et	et	PROPN
esrj-95748	29	33	al	al	PROPN
esrj-95748	29	34	.	.	PROPN
esrj-95748	29	35	,	,	PUNCT
esrj-95748	29	36	2005	2005	NUM
esrj-95748	29	37	)	)	PUNCT
esrj-95748	29	38	.	.	PUNCT
esrj-95748	30	1	gullies	gully	NOUN
esrj-95748	30	2	are	be	AUX
esrj-95748	30	3	defined	define	VERB
esrj-95748	30	4	as	as	ADP
esrj-95748	30	5	deep	deep	ADJ
esrj-95748	30	6	channels	channel	NOUN
esrj-95748	30	7	formed	form	VERB
esrj-95748	30	8	by	by	ADP
esrj-95748	30	9	accumulated	accumulate	VERB
esrj-95748	30	10	overland	overland	NOUN
esrj-95748	30	11	flows	flow	VERB
esrj-95748	30	12	that	that	SCONJ
esrj-95748	30	13	multiple	multiple	ADJ
esrj-95748	30	14	mechanisms	mechanism	NOUN
esrj-95748	30	15	,	,	PUNCT
esrj-95748	30	16	such	such	ADJ
esrj-95748	30	17	as	as	ADP
esrj-95748	30	18	cutting	cutting	NOUN
esrj-95748	30	19	,	,	PUNCT
esrj-95748	30	20	penetration	penetration	NOUN
esrj-95748	30	21	,	,	PUNCT
esrj-95748	30	22	and	and	CCONJ
esrj-95748	30	23	tension	tension	NOUN
esrj-95748	30	24	gap	gap	NOUN
esrj-95748	30	25	progression	progression	NOUN
esrj-95748	30	26	,	,	PUNCT
esrj-95748	30	27	encourage	encourage	VERB
esrj-95748	30	28	their	their	PRON
esrj-95748	30	29	development	development	NOUN
esrj-95748	30	30	.	.	PUNCT
esrj-95748	31	1	these	these	DET
esrj-95748	31	2	erosional	erosional	ADJ
esrj-95748	31	3	landforms	landform	NOUN
esrj-95748	31	4	commonly	commonly	ADV
esrj-95748	31	5	develop	develop	VERB
esrj-95748	31	6	on	on	ADP
esrj-95748	31	7	hillslope	hillslope	NOUN
esrj-95748	31	8	due	due	ADP
esrj-95748	31	9	to	to	ADP
esrj-95748	31	10	the	the	DET
esrj-95748	31	11	simultaneous	simultaneous	ADJ
esrj-95748	31	12	effects	effect	NOUN
esrj-95748	31	13	of	of	ADP
esrj-95748	31	14	multiple	multiple	ADJ
esrj-95748	31	15	geo	geo	PROPN
esrj-95748	31	16	-	-	PUNCT
esrj-95748	31	17	environmental	environmental	ADJ
esrj-95748	31	18	variables	variable	NOUN
esrj-95748	31	19	,	,	PUNCT
esrj-95748	31	20	including	include	VERB
esrj-95748	31	21	land	land	NOUN
esrj-95748	31	22	cover	cover	NOUN
esrj-95748	31	23	,	,	PUNCT
esrj-95748	31	24	land	land	NOUN
esrj-95748	31	25	use	use	NOUN
esrj-95748	31	26	,	,	PUNCT
esrj-95748	31	27	lithology	lithology	NOUN
esrj-95748	31	28	,	,	PUNCT
esrj-95748	31	29	topography	topography	NOUN
esrj-95748	31	30	,	,	PUNCT
esrj-95748	31	31	soil	soil	NOUN
esrj-95748	31	32	type	type	NOUN
esrj-95748	31	33	,	,	PUNCT
esrj-95748	31	34	and	and	CCONJ
esrj-95748	31	35	climate	climate	NOUN
esrj-95748	31	36	(	(	PUNCT
esrj-95748	31	37	gayen	gayen	NOUN
esrj-95748	31	38	et	et	PROPN
esrj-95748	31	39	al	al	PROPN
esrj-95748	31	40	.	.	PROPN
esrj-95748	31	41	,	,	PUNCT
esrj-95748	31	42	2019	2019	NUM
esrj-95748	31	43	)	)	PUNCT
esrj-95748	31	44	.	.	PUNCT
esrj-95748	32	1	soil	soil	NOUN
esrj-95748	32	2	degradation	degradation	NOUN
esrj-95748	32	3	induced	induce	VERB
esrj-95748	32	4	by	by	ADP
esrj-95748	32	5	water	water	NOUN
esrj-95748	32	6	erosion	erosion	NOUN
esrj-95748	32	7	is	be	AUX
esrj-95748	32	8	the	the	DET
esrj-95748	32	9	most	most	ADV
esrj-95748	32	10	critical	critical	ADJ
esrj-95748	32	11	challenge	challenge	NOUN
esrj-95748	32	12	faced	face	VERB
esrj-95748	32	13	by	by	ADP
esrj-95748	32	14	many	many	ADJ
esrj-95748	32	15	of	of	ADP
esrj-95748	32	16	the	the	DET
esrj-95748	32	17	world	world	NOUN
esrj-95748	32	18	’s	’s	PART
esrj-95748	32	19	dryland	dryland	NOUN
esrj-95748	32	20	regions	region	NOUN
esrj-95748	32	21	,	,	PUNCT
esrj-95748	32	22	such	such	ADJ
esrj-95748	32	23	as	as	ADP
esrj-95748	32	24	iran	iran	PROPN
esrj-95748	32	25	.	.	PUNCT
esrj-95748	33	1	iran	iran	PROPN
esrj-95748	33	2	is	be	AUX
esrj-95748	33	3	recognized	recognize	VERB
esrj-95748	33	4	as	as	ADP
esrj-95748	33	5	the	the	DET
esrj-95748	33	6	second	second	ADJ
esrj-95748	33	7	in	in	ADP
esrj-95748	33	8	the	the	DET
esrj-95748	33	9	world	world	NOUN
esrj-95748	33	10	in	in	ADP
esrj-95748	33	11	terms	term	NOUN
esrj-95748	33	12	of	of	ADP
esrj-95748	33	13	soil	soil	NOUN
esrj-95748	33	14	erosion	erosion	NOUN
esrj-95748	33	15	where	where	SCONJ
esrj-95748	33	16	approximately	approximately	ADV
esrj-95748	33	17	2.5	2.5	NUM
esrj-95748	33	18	billion	billion	NUM
esrj-95748	33	19	tons	ton	NOUN
esrj-95748	33	20	of	of	ADP
esrj-95748	33	21	fertile	fertile	ADJ
esrj-95748	33	22	lands	land	NOUN
esrj-95748	33	23	are	be	AUX
esrj-95748	33	24	lost	lose	VERB
esrj-95748	33	25	per	per	ADP
esrj-95748	33	26	year	year	NOUN
esrj-95748	33	27	.	.	PUNCT
esrj-95748	34	1	gully	gully	ADJ
esrj-95748	34	2	erosion	erosion	NOUN
esrj-95748	34	3	can	can	AUX
esrj-95748	34	4	stimulate	stimulate	VERB
esrj-95748	34	5	multiple	multiple	ADJ
esrj-95748	34	6	environmental	environmental	ADJ
esrj-95748	34	7	hazards	hazard	NOUN
esrj-95748	34	8	,	,	PUNCT
esrj-95748	34	9	such	such	ADJ
esrj-95748	34	10	as	as	ADP
esrj-95748	34	11	desertification	desertification	NOUN
esrj-95748	34	12	,	,	PUNCT
esrj-95748	34	13	increasing	increase	VERB
esrj-95748	34	14	sediment	sediment	NOUN
esrj-95748	34	15	load	load	NOUN
esrj-95748	34	16	in	in	ADP
esrj-95748	34	17	rivers	river	NOUN
esrj-95748	34	18	and	and	CCONJ
esrj-95748	34	19	reservoirs	reservoir	NOUN
esrj-95748	34	20	,	,	PUNCT
esrj-95748	34	21	flood	flood	NOUN
esrj-95748	34	22	,	,	PUNCT
esrj-95748	34	23	and	and	CCONJ
esrj-95748	34	24	soil	soil	NOUN
esrj-95748	34	25	productivity	productivity	NOUN
esrj-95748	34	26	loss	loss	NOUN
esrj-95748	34	27	(	(	PUNCT
esrj-95748	34	28	fox	fox	PROPN
esrj-95748	34	29	et	et	PROPN
esrj-95748	34	30	al	al	PROPN
esrj-95748	34	31	.	.	PROPN
esrj-95748	34	32	,	,	PUNCT
esrj-95748	34	33	2016	2016	NUM
esrj-95748	34	34	;	;	PUNCT
esrj-95748	34	35	ekholm	ekholm	NOUN
esrj-95748	34	36	and	and	CCONJ
esrj-95748	34	37	lehtoranta	lehtoranta	ADJ
esrj-95748	34	38	,	,	PUNCT
esrj-95748	34	39	2012	2012	NUM
esrj-95748	34	40	)	)	PUNCT
esrj-95748	34	41	.	.	PUNCT
esrj-95748	35	1	although	although	SCONJ
esrj-95748	35	2	this	this	DET
esrj-95748	35	3	hazard	hazard	NOUN
esrj-95748	35	4	occurs	occur	VERB
esrj-95748	35	5	on	on	ADP
esrj-95748	35	6	a	a	DET
esrj-95748	35	7	small	small	ADJ
esrj-95748	35	8	scale	scale	NOUN
esrj-95748	35	9	,	,	PUNCT
esrj-95748	35	10	its	its	PRON
esrj-95748	35	11	consequences	consequence	NOUN
esrj-95748	35	12	will	will	AUX
esrj-95748	35	13	have	have	VERB
esrj-95748	35	14	a	a	DET
esrj-95748	35	15	substantial	substantial	ADJ
esrj-95748	35	16	impact	impact	NOUN
esrj-95748	35	17	on	on	ADP
esrj-95748	35	18	global	global	ADJ
esrj-95748	35	19	scales	scale	NOUN
esrj-95748	35	20	.	.	PUNCT
esrj-95748	36	1	for	for	ADP
esrj-95748	36	2	example	example	NOUN
esrj-95748	36	3	,	,	PUNCT
esrj-95748	36	4	gully	gully	NOUN
esrj-95748	36	5	erosion	erosion	NOUN
esrj-95748	36	6	with	with	ADP
esrj-95748	36	7	disturbing	disturb	VERB
esrj-95748	36	8	the	the	DET
esrj-95748	36	9	condition	condition	NOUN
esrj-95748	36	10	of	of	ADP
esrj-95748	36	11	sequestration	sequestration	NOUN
esrj-95748	36	12	and	and	CCONJ
esrj-95748	36	13	decomposition	decomposition	NOUN
esrj-95748	36	14	of	of	ADP
esrj-95748	36	15	soil	soil	NOUN
esrj-95748	36	16	organic	organic	ADJ
esrj-95748	36	17	carbon	carbon	NOUN
esrj-95748	36	18	encourages	encourage	VERB
esrj-95748	36	19	instability	instability	NOUN
esrj-95748	36	20	in	in	ADP
esrj-95748	36	21	the	the	DET
esrj-95748	36	22	atmospheric	atmospheric	ADJ
esrj-95748	36	23	carbon	carbon	NOUN
esrj-95748	36	24	dioxide	dioxide	NOUN
esrj-95748	36	25	concentrations	concentration	NOUN
esrj-95748	36	26	and	and	CCONJ
esrj-95748	36	27	influences	influence	VERB
esrj-95748	36	28	climate	climate	NOUN
esrj-95748	36	29	change	change	NOUN
esrj-95748	36	30	(	(	PUNCT
esrj-95748	36	31	xiao	xiao	PROPN
esrj-95748	36	32	et	et	PROPN
esrj-95748	36	33	al	al	PROPN
esrj-95748	36	34	.	.	PROPN
esrj-95748	36	35	,	,	PUNCT
esrj-95748	36	36	2017	2017	NUM
esrj-95748	36	37	;	;	PUNCT
esrj-95748	36	38	yigini	yigini	NOUN
esrj-95748	36	39	and	and	CCONJ
esrj-95748	36	40	panagos	panago	NOUN
esrj-95748	36	41	,	,	PUNCT
esrj-95748	36	42	2016	2016	NUM
esrj-95748	36	43	)	)	PUNCT
esrj-95748	36	44	.	.	PUNCT
esrj-95748	37	1	to	to	PART
esrj-95748	37	2	minimize	minimize	VERB
esrj-95748	37	3	this	this	DET
esrj-95748	37	4	hazard	hazard	NOUN
esrj-95748	37	5	and	and	CCONJ
esrj-95748	37	6	the	the	DET
esrj-95748	37	7	related	relate	VERB
esrj-95748	37	8	environmental	environmental	ADJ
esrj-95748	37	9	problems	problem	NOUN
esrj-95748	37	10	,	,	PUNCT
esrj-95748	37	11	it	it	PRON
esrj-95748	37	12	is	be	AUX
esrj-95748	37	13	necessary	necessary	ADJ
esrj-95748	37	14	to	to	PART
esrj-95748	37	15	understand	understand	VERB
esrj-95748	37	16	mechanisms	mechanism	NOUN
esrj-95748	37	17	controlling	control	VERB
esrj-95748	37	18	gully	gully	ADJ
esrj-95748	37	19	development	development	NOUN
esrj-95748	37	20	.	.	PUNCT
esrj-95748	38	1	furthermore	furthermore	ADV
esrj-95748	38	2	,	,	PUNCT
esrj-95748	38	3	determining	determine	VERB
esrj-95748	38	4	the	the	DET
esrj-95748	38	5	magnitude	magnitude	NOUN
esrj-95748	38	6	and	and	CCONJ
esrj-95748	38	7	spatial	spatial	ADJ
esrj-95748	38	8	distribution	distribution	NOUN
esrj-95748	38	9	of	of	ADP
esrj-95748	38	10	erosion	erosion	NOUN
esrj-95748	38	11	susceptibility	susceptibility	NOUN
esrj-95748	38	12	zones	zone	NOUN
esrj-95748	38	13	can	can	AUX
esrj-95748	38	14	help	help	VERB
esrj-95748	38	15	to	to	PART
esrj-95748	38	16	implement	implement	VERB
esrj-95748	38	17	geo	geo	PROPN
esrj-95748	38	18	-	-	PUNCT
esrj-95748	38	19	conservation	conservation	NOUN
esrj-95748	38	20	and	and	CCONJ
esrj-95748	38	21	management	management	NOUN
esrj-95748	38	22	efforts	effort	NOUN
esrj-95748	38	23	for	for	ADP
esrj-95748	38	24	mitigating	mitigate	VERB
esrj-95748	38	25	disasters	disaster	NOUN
esrj-95748	38	26	associated	associate	VERB
esrj-95748	38	27	with	with	ADP
esrj-95748	38	28	this	this	DET
esrj-95748	38	29	hazard	hazard	NOUN
esrj-95748	38	30	.	.	PUNCT
esrj-95748	39	1	the	the	DET
esrj-95748	39	2	gully	gully	PROPN
esrj-95748	39	3	erosion	erosion	NOUN
esrj-95748	39	4	susceptibility	susceptibility	NOUN
esrj-95748	39	5	assessment	assessment	NOUN
esrj-95748	39	6	is	be	AUX
esrj-95748	39	7	the	the	DET
esrj-95748	39	8	first	first	ADJ
esrj-95748	39	9	step	step	NOUN
esrj-95748	39	10	towards	towards	ADP
esrj-95748	39	11	geoconservation	geoconservation	NOUN
esrj-95748	39	12	and	and	CCONJ
esrj-95748	39	13	restoration	restoration	NOUN
esrj-95748	39	14	efforts	effort	NOUN
esrj-95748	39	15	in	in	ADP
esrj-95748	39	16	gully	gully	NOUN
esrj-95748	39	17	-	-	PUNCT
esrj-95748	39	18	prone	prone	ADJ
esrj-95748	39	19	areas	area	NOUN
esrj-95748	39	20	(	(	PUNCT
esrj-95748	39	21	conoscenti	conoscenti	VERB
esrj-95748	39	22	et	et	PROPN
esrj-95748	39	23	al	al	PROPN
esrj-95748	39	24	.	.	PROPN
esrj-95748	39	25	,	,	PUNCT
esrj-95748	39	26	2014	2014	NUM
esrj-95748	39	27	)	)	PUNCT
esrj-95748	39	28	.	.	PUNCT
esrj-95748	40	1	multiple	multiple	ADJ
esrj-95748	40	2	quantitative	quantitative	ADJ
esrj-95748	40	3	and	and	CCONJ
esrj-95748	40	4	qualitative	qualitative	ADJ
esrj-95748	40	5	models	model	NOUN
esrj-95748	40	6	have	have	AUX
esrj-95748	40	7	been	be	AUX
esrj-95748	40	8	proposed	propose	VERB
esrj-95748	40	9	to	to	PART
esrj-95748	40	10	estimate	estimate	VERB
esrj-95748	40	11	this	this	DET
esrj-95748	40	12	hazard	hazard	NOUN
esrj-95748	40	13	,	,	PUNCT
esrj-95748	40	14	such	such	ADJ
esrj-95748	40	15	as	as	ADP
esrj-95748	40	16	the	the	DET
esrj-95748	40	17	limburg	limburg	PROPN
esrj-95748	40	18	soil	soil	NOUN
esrj-95748	40	19	erosion	erosion	NOUN
esrj-95748	40	20	model	model	NOUN
esrj-95748	40	21	,	,	PUNCT
esrj-95748	40	22	universal	universal	ADJ
esrj-95748	40	23	soil	soil	NOUN
esrj-95748	40	24	loss	loss	NOUN
esrj-95748	40	25	equation	equation	NOUN
esrj-95748	40	26	,	,	PUNCT
esrj-95748	40	27	european	european	ADJ
esrj-95748	40	28	soil	soil	NOUN
esrj-95748	40	29	erosion	erosion	NOUN
esrj-95748	40	30	model	model	NOUN
esrj-95748	40	31	,	,	PUNCT
esrj-95748	40	32	chemical	chemical	NOUN
esrj-95748	40	33	runoff	runoff	NOUN
esrj-95748	40	34	and	and	CCONJ
esrj-95748	40	35	erosion	erosion	NOUN
esrj-95748	40	36	for	for	ADP
esrj-95748	40	37	agricultural	agricultural	ADJ
esrj-95748	40	38	management	management	NOUN
esrj-95748	40	39	system	system	NOUN
esrj-95748	40	40	,	,	PUNCT
esrj-95748	40	41	water	water	NOUN
esrj-95748	40	42	erosion	erosion	NOUN
esrj-95748	40	43	prediction	prediction	NOUN
esrj-95748	40	44	project	project	NOUN
esrj-95748	40	45	model	model	NOUN
esrj-95748	40	46	,	,	PUNCT
esrj-95748	40	47	bivariate	bivariate	ADJ
esrj-95748	40	48	statistical	statistical	ADJ
esrj-95748	40	49	models	model	NOUN
esrj-95748	40	50	,	,	PUNCT
esrj-95748	40	51	and	and	CCONJ
esrj-95748	40	52	logistic	logistic	ADJ
esrj-95748	40	53	regression	regression	NOUN
esrj-95748	40	54	.	.	PUNCT
esrj-95748	41	1	these	these	DET
esrj-95748	41	2	models	model	NOUN
esrj-95748	41	3	could	could	AUX
esrj-95748	41	4	not	not	PART
esrj-95748	41	5	consider	consider	VERB
esrj-95748	41	6	the	the	DET
esrj-95748	41	7	interactions	interaction	NOUN
esrj-95748	41	8	among	among	ADP
esrj-95748	41	9	factors	factor	NOUN
esrj-95748	41	10	controlling	control	VERB
esrj-95748	41	11	gully	gully	ADJ
esrj-95748	41	12	erosion	erosion	NOUN
esrj-95748	41	13	,	,	PUNCT
esrj-95748	41	14	such	such	ADJ
esrj-95748	41	15	as	as	ADP
esrj-95748	41	16	topographic	topographic	ADJ
esrj-95748	41	17	variables	variable	NOUN
esrj-95748	41	18	,	,	PUNCT
esrj-95748	41	19	geo	geo	PROPN
esrj-95748	41	20	-	-	PUNCT
esrj-95748	41	21	environmental	environmental	ADJ
esrj-95748	41	22	factors	factor	NOUN
esrj-95748	41	23	,	,	PUNCT
esrj-95748	41	24	soil	soil	NOUN
esrj-95748	41	25	conditions	condition	NOUN
esrj-95748	41	26	,	,	PUNCT
esrj-95748	41	27	land	land	NOUN
esrj-95748	41	28	use/	use/	ADJ
esrj-95748	41	29	cover	cover	NOUN
esrj-95748	41	30	,	,	PUNCT
esrj-95748	41	31	sediment	sediment	NOUN
esrj-95748	41	32	yield	yield	NOUN
esrj-95748	41	33	,	,	PUNCT
esrj-95748	41	34	and	and	CCONJ
esrj-95748	41	35	climatic	climatic	ADJ
esrj-95748	41	36	indices	index	NOUN
esrj-95748	41	37	.	.	PUNCT
esrj-95748	42	1	compared	compare	VERB
esrj-95748	42	2	to	to	PART
esrj-95748	42	3	bivariate	bivariate	VERB
esrj-95748	42	4	and	and	CCONJ
esrj-95748	42	5	logistic	logistic	ADJ
esrj-95748	42	6	regression	regression	NOUN
esrj-95748	42	7	models	model	NOUN
esrj-95748	42	8	,	,	PUNCT
esrj-95748	42	9	machine	machine	NOUN
esrj-95748	42	10	learning	learning	NOUN
esrj-95748	42	11	algorithms	algorithm	NOUN
esrj-95748	42	12	are	be	AUX
esrj-95748	42	13	the	the	DET
esrj-95748	42	14	ideal	ideal	ADJ
esrj-95748	42	15	models	model	NOUN
esrj-95748	42	16	to	to	PART
esrj-95748	42	17	assess	assess	VERB
esrj-95748	42	18	erosion	erosion	NOUN
esrj-95748	42	19	susceptibility	susceptibility	NOUN
esrj-95748	42	20	,	,	PUNCT
esrj-95748	42	21	which	which	PRON
esrj-95748	42	22	efficiently	efficiently	ADV
esrj-95748	42	23	predict	predict	VERB
esrj-95748	42	24	the	the	DET
esrj-95748	42	25	probability	probability	NOUN
esrj-95748	42	26	of	of	ADP
esrj-95748	42	27	gullying	gullye	VERB
esrj-95748	42	28	with	with	ADP
esrj-95748	42	29	high	high	ADJ
esrj-95748	42	30	accuracy	accuracy	NOUN
esrj-95748	42	31	(	(	PUNCT
esrj-95748	42	32	micheletti	micheletti	PROPN
esrj-95748	42	33	et	et	PROPN
esrj-95748	42	34	al	al	PROPN
esrj-95748	42	35	.	.	PROPN
esrj-95748	42	36	,	,	PUNCT
esrj-95748	42	37	2014	2014	NUM
esrj-95748	42	38	)	)	PUNCT
esrj-95748	42	39	.	.	PUNCT
esrj-95748	43	1	to	to	ADP
esrj-95748	43	2	date	date	NOUN
esrj-95748	43	3	,	,	PUNCT
esrj-95748	43	4	some	some	DET
esrj-95748	43	5	studies	study	NOUN
esrj-95748	43	6	have	have	AUX
esrj-95748	43	7	predicted	predict	VERB
esrj-95748	43	8	potential	potential	ADJ
esrj-95748	43	9	erosion	erosion	NOUN
esrj-95748	43	10	-	-	PUNCT
esrj-95748	43	11	prone	prone	ADJ
esrj-95748	43	12	areas	area	NOUN
esrj-95748	43	13	in	in	ADP
esrj-95748	43	14	watersheds	watershed	NOUN
esrj-95748	43	15	using	use	VERB
esrj-95748	43	16	these	these	DET
esrj-95748	43	17	models	model	NOUN
esrj-95748	43	18	.	.	PUNCT
esrj-95748	44	1	chen	chen	PROPN
esrj-95748	44	2	et	et	PROPN
esrj-95748	44	3	al	al	PROPN
esrj-95748	44	4	.	.	PROPN
esrj-95748	44	5	,	,	PUNCT
esrj-95748	44	6	(	(	PUNCT
esrj-95748	44	7	2021	2021	NUM
esrj-95748	44	8	)	)	PUNCT
esrj-95748	44	9	predicted	predict	VERB
esrj-95748	44	10	the	the	DET
esrj-95748	44	11	gully	gully	ADJ
esrj-95748	44	12	erosion	erosion	NOUN
esrj-95748	44	13	within	within	ADP
esrj-95748	44	14	a	a	DET
esrj-95748	44	15	watershed	watershed	NOUN
esrj-95748	44	16	located	locate	VERB
esrj-95748	44	17	in	in	ADP
esrj-95748	44	18	iran	iran	PROPN
esrj-95748	44	19	using	use	VERB
esrj-95748	44	20	boosting	boost	VERB
esrj-95748	44	21	ensemble	ensemble	ADJ
esrj-95748	44	22	machine	machine	NOUN
esrj-95748	44	23	learning	learn	VERB
esrj-95748	44	24	algorithms	algorithm	NOUN
esrj-95748	44	25	.	.	PUNCT
esrj-95748	45	1	lei	lei	PROPN
esrj-95748	45	2	et	et	PROPN
esrj-95748	45	3	al	al	PROPN
esrj-95748	45	4	.	.	PROPN
esrj-95748	45	5	,	,	PUNCT
esrj-95748	45	6	(	(	PUNCT
esrj-95748	45	7	2020	2020	NUM
esrj-95748	45	8	)	)	PUNCT
esrj-95748	45	9	evaluated	evaluate	VERB
esrj-95748	45	10	gully	gully	ADJ
esrj-95748	45	11	erosion	erosion	NOUN
esrj-95748	45	12	susceptibility	susceptibility	NOUN
esrj-95748	45	13	in	in	ADP
esrj-95748	45	14	a	a	DET
esrj-95748	45	15	catchment	catchment	NOUN
esrj-95748	45	16	located	locate	VERB
esrj-95748	45	17	in	in	ADP
esrj-95748	45	18	iran	iran	PROPN
esrj-95748	45	19	using	use	VERB
esrj-95748	45	20	four	four	NUM
esrj-95748	45	21	data	datum	NOUN
esrj-95748	45	22	mining	mining	NOUN
esrj-95748	45	23	techniques	technique	NOUN
esrj-95748	45	24	,	,	PUNCT
esrj-95748	45	25	including	include	VERB
esrj-95748	45	26	random	random	ADJ
esrj-95748	45	27	forest	forest	NOUN
esrj-95748	45	28	,	,	PUNCT
esrj-95748	45	29	credal	credal	ADJ
esrj-95748	45	30	decision	decision	NOUN
esrj-95748	45	31	trees	tree	NOUN
esrj-95748	45	32	,	,	PUNCT
esrj-95748	45	33	kernel	kernel	PROPN
esrj-95748	45	34	logistic	logistic	ADJ
esrj-95748	45	35	regression	regression	NOUN
esrj-95748	45	36	,	,	PUNCT
esrj-95748	45	37	and	and	CCONJ
esrj-95748	45	38	best	good	ADJ
esrj-95748	45	39	-	-	PUNCT
esrj-95748	45	40	first	first	ADJ
esrj-95748	45	41	decision	decision	NOUN
esrj-95748	45	42	tree	tree	NOUN
esrj-95748	45	43	.	.	PUNCT
esrj-95748	46	1	arabameri	arabameri	NOUN
esrj-95748	46	2	et	et	PROPN
esrj-95748	46	3	al	al	PROPN
esrj-95748	46	4	.	.	PROPN
esrj-95748	46	5	,	,	PUNCT
esrj-95748	46	6	(	(	PUNCT
esrj-95748	46	7	2020	2020	NUM
esrj-95748	46	8	)	)	PUNCT
esrj-95748	46	9	mapped	map	VERB
esrj-95748	46	10	erosion	erosion	NOUN
esrj-95748	46	11	susceptibility	susceptibility	NOUN
esrj-95748	46	12	by	by	ADP
esrj-95748	46	13	applying	apply	VERB
esrj-95748	46	14	four	four	NUM
esrj-95748	46	15	models	model	NOUN
esrj-95748	46	16	of	of	ADP
esrj-95748	46	17	support	support	NOUN
esrj-95748	46	18	vector	vector	NOUN
esrj-95748	46	19	machine	machine	NOUN
esrj-95748	46	20	,	,	PUNCT
esrj-95748	46	21	artificial	artificial	ADJ
esrj-95748	46	22	neural	neural	ADJ
esrj-95748	46	23	network	network	NOUN
esrj-95748	46	24	,	,	PUNCT
esrj-95748	46	25	general	general	ADJ
esrj-95748	46	26	linear	linear	NOUN
esrj-95748	46	27	,	,	PUNCT
esrj-95748	46	28	and	and	CCONJ
esrj-95748	46	29	maximum	maximum	ADJ
esrj-95748	46	30	entropy	entropy	NOUN
esrj-95748	46	31	in	in	ADP
esrj-95748	46	32	the	the	DET
esrj-95748	46	33	golestan	golestan	PROPN
esrj-95748	46	34	dam	dam	NOUN
esrj-95748	46	35	basin	basin	NOUN
esrj-95748	46	36	,	,	PUNCT
esrj-95748	46	37	iran	iran	PROPN
esrj-95748	46	38	.	.	PUNCT
esrj-95748	47	1	saha	saha	PROPN
esrj-95748	47	2	et	et	PROPN
esrj-95748	47	3	al	al	PROPN
esrj-95748	47	4	.	.	PROPN
esrj-95748	47	5	,	,	PUNCT
esrj-95748	47	6	(	(	PUNCT
esrj-95748	47	7	2020	2020	NUM
esrj-95748	47	8	)	)	PUNCT
esrj-95748	47	9	delineated	delineate	VERB
esrj-95748	47	10	the	the	DET
esrj-95748	47	11	areas	area	NOUN
esrj-95748	47	12	with	with	ADP
esrj-95748	47	13	the	the	DET
esrj-95748	47	14	most	most	ADV
esrj-95748	47	15	severe	severe	ADJ
esrj-95748	47	16	gully	gully	NOUN
esrj-95748	47	17	erosion	erosion	NOUN
esrj-95748	47	18	susceptibility	susceptibility	NOUN
esrj-95748	47	19	using	use	VERB
esrj-95748	47	20	the	the	DET
esrj-95748	47	21	algorithms	algorithm	NOUN
esrj-95748	47	22	of	of	ADP
esrj-95748	47	23	tree	tree	NOUN
esrj-95748	47	24	ensemble	ensemble	ADJ
esrj-95748	47	25	,	,	PUNCT
esrj-95748	47	26	random	random	ADJ
esrj-95748	47	27	forest	forest	NOUN
esrj-95748	47	28	,	,	PUNCT
esrj-95748	47	29	and	and	CCONJ
esrj-95748	47	30	gradient	gradient	NOUN
esrj-95748	47	31	boosted	boost	VERB
esrj-95748	47	32	regression	regression	NOUN
esrj-95748	47	33	tree	tree	NOUN
esrj-95748	47	34	.	.	PUNCT
esrj-95748	48	1	pourghasemi	pourghasemi	PROPN
esrj-95748	48	2	et	et	PROPN
esrj-95748	48	3	al	al	PROPN
esrj-95748	48	4	.	.	PROPN
esrj-95748	48	5	,	,	PUNCT
esrj-95748	48	6	(	(	PUNCT
esrj-95748	48	7	2020	2020	NUM
esrj-95748	48	8	)	)	PUNCT
esrj-95748	48	9	assessed	assess	VERB
esrj-95748	48	10	the	the	DET
esrj-95748	48	11	efficacy	efficacy	NOUN
esrj-95748	48	12	of	of	ADP
esrj-95748	48	13	multiple	multiple	ADJ
esrj-95748	48	14	machine	machine	NOUN
esrj-95748	48	15	learning	learn	VERB
esrj-95748	48	16	algorithms	algorithm	NOUN
esrj-95748	48	17	to	to	PART
esrj-95748	48	18	predict	predict	VERB
esrj-95748	48	19	gully	gully	ADJ
esrj-95748	48	20	erosion	erosion	NOUN
esrj-95748	48	21	occurrence	occurrence	NOUN
esrj-95748	48	22	.	.	PUNCT
esrj-95748	49	1	amiri	amiri	PROPN
esrj-95748	49	2	et	et	PROPN
esrj-95748	49	3	al	al	PROPN
esrj-95748	49	4	.	.	PROPN
esrj-95748	49	5	,	,	PUNCT
esrj-95748	49	6	(	(	PUNCT
esrj-95748	49	7	2019	2019	NUM
esrj-95748	49	8	)	)	PUNCT
esrj-95748	49	9	evaluated	evaluate	VERB
esrj-95748	49	10	the	the	DET
esrj-95748	49	11	importance	importance	NOUN
esrj-95748	49	12	of	of	ADP
esrj-95748	49	13	factors	factor	NOUN
esrj-95748	49	14	controlling	control	VERB
esrj-95748	49	15	gully	gully	ADJ
esrj-95748	49	16	development	development	NOUN
esrj-95748	49	17	within	within	ADP
esrj-95748	49	18	a	a	DET
esrj-95748	49	19	watershed	watershe	VERB
esrj-95748	49	20	and	and	CCONJ
esrj-95748	49	21	mapped	map	VERB
esrj-95748	49	22	its	its	PRON
esrj-95748	49	23	susceptibility	susceptibility	NOUN
esrj-95748	49	24	using	use	VERB
esrj-95748	49	25	machine	machine	NOUN
esrj-95748	49	26	learning	learning	NOUN
esrj-95748	49	27	algorithms	algorithm	NOUN
esrj-95748	49	28	.	.	PUNCT
esrj-95748	50	1	gayen	gayen	NOUN
esrj-95748	50	2	et	et	PROPN
esrj-95748	50	3	al	al	PROPN
esrj-95748	50	4	.	.	PROPN
esrj-95748	50	5	,	,	PUNCT
esrj-95748	50	6	(	(	PUNCT
esrj-95748	50	7	2019	2019	NUM
esrj-95748	50	8	)	)	PUNCT
esrj-95748	50	9	produced	produce	VERB
esrj-95748	50	10	a	a	DET
esrj-95748	50	11	gully	gully	ADJ
esrj-95748	50	12	erosion	erosion	NOUN
esrj-95748	50	13	susceptibility	susceptibility	NOUN
esrj-95748	50	14	map	map	NOUN
esrj-95748	50	15	in	in	ADP
esrj-95748	50	16	the	the	DET
esrj-95748	50	17	pathro	pathro	NOUN
esrj-95748	50	18	catchment	catchment	NOUN
esrj-95748	50	19	,	,	PUNCT
esrj-95748	50	20	india	india	PROPN
esrj-95748	50	21	using	use	VERB
esrj-95748	50	22	different	different	ADJ
esrj-95748	50	23	machine	machine	NOUN
esrj-95748	50	24	learning	learn	VERB
esrj-95748	50	25	algorithms	algorithm	NOUN
esrj-95748	50	26	.	.	PUNCT
esrj-95748	51	1	garosi	garosi	NOUN
esrj-95748	51	2	et	et	PROPN
esrj-95748	51	3	al	al	PROPN
esrj-95748	51	4	.	.	PROPN
esrj-95748	51	5	,	,	PUNCT
esrj-95748	51	6	(	(	PUNCT
esrj-95748	51	7	2019	2019	NUM
esrj-95748	51	8	)	)	PUNCT
esrj-95748	51	9	compared	compare	VERB
esrj-95748	51	10	the	the	DET
esrj-95748	51	11	reliability	reliability	NOUN
esrj-95748	51	12	and	and	CCONJ
esrj-95748	51	13	discrimination	discrimination	NOUN
esrj-95748	51	14	of	of	ADP
esrj-95748	51	15	four	four	NUM
esrj-95748	51	16	machine	machine	NOUN
esrj-95748	51	17	learning	learning	NOUN
esrj-95748	51	18	models	model	NOUN
esrj-95748	51	19	to	to	PART
esrj-95748	51	20	map	map	VERB
esrj-95748	51	21	gully	gully	ADJ
esrj-95748	51	22	erosion	erosion	NOUN
esrj-95748	51	23	susceptibility	susceptibility	NOUN
esrj-95748	51	24	in	in	ADP
esrj-95748	51	25	western	western	ADJ
esrj-95748	51	26	iran	iran	PROPN
esrj-95748	51	27	.	.	PUNCT
esrj-95748	52	1	in	in	ADP
esrj-95748	52	2	the	the	DET
esrj-95748	52	3	present	present	ADJ
esrj-95748	52	4	study	study	NOUN
esrj-95748	52	5	,	,	PUNCT
esrj-95748	52	6	the	the	DET
esrj-95748	52	7	importance	importance	NOUN
esrj-95748	52	8	of	of	ADP
esrj-95748	52	9	conditioning	conditioning	NOUN
esrj-95748	52	10	factors	factor	NOUN
esrj-95748	52	11	in	in	ADP
esrj-95748	52	12	gully	gully	ADJ
esrj-95748	52	13	erosion	erosion	NOUN
esrj-95748	52	14	occurrence	occurrence	NOUN
esrj-95748	52	15	was	be	AUX
esrj-95748	52	16	assessed	assess	VERB
esrj-95748	52	17	using	use	VERB
esrj-95748	52	18	the	the	DET
esrj-95748	52	19	boruta	boruta	NOUN
esrj-95748	52	20	algorithm	algorithm	NOUN
esrj-95748	52	21	,	,	PUNCT
esrj-95748	52	22	as	as	ADP
esrj-95748	52	23	a	a	DET
esrj-95748	52	24	feature	feature	NOUN
esrj-95748	52	25	selection	selection	NOUN
esrj-95748	52	26	algorithm	algorithm	NOUN
esrj-95748	52	27	that	that	PRON
esrj-95748	52	28	acts	act	VERB
esrj-95748	52	29	independently	independently	ADV
esrj-95748	52	30	from	from	ADP
esrj-95748	52	31	the	the	DET
esrj-95748	52	32	predictive	predictive	ADJ
esrj-95748	52	33	models	model	NOUN
esrj-95748	52	34	of	of	ADP
esrj-95748	52	35	gully	gully	ADJ
esrj-95748	52	36	erosion	erosion	NOUN
esrj-95748	52	37	to	to	PART
esrj-95748	52	38	determine	determine	VERB
esrj-95748	52	39	the	the	DET
esrj-95748	52	40	most	most	ADV
esrj-95748	52	41	important	important	ADJ
esrj-95748	52	42	factors	factor	NOUN
esrj-95748	52	43	,	,	PUNCT
esrj-95748	52	44	while	while	SCONJ
esrj-95748	52	45	previous	previous	ADJ
esrj-95748	52	46	studies	study	NOUN
esrj-95748	52	47	selected	select	VERB
esrj-95748	52	48	the	the	DET
esrj-95748	52	49	most	most	ADV
esrj-95748	52	50	important	important	ADJ
esrj-95748	52	51	causative	causative	ADJ
esrj-95748	52	52	factors	factor	NOUN
esrj-95748	52	53	based	base	VERB
esrj-95748	52	54	on	on	ADP
esrj-95748	52	55	the	the	DET
esrj-95748	52	56	derivatives	derivative	NOUN
esrj-95748	52	57	of	of	ADP
esrj-95748	52	58	the	the	DET
esrj-95748	52	59	employed	employ	VERB
esrj-95748	52	60	models	model	NOUN
esrj-95748	52	61	.	.	PUNCT
esrj-95748	53	1	in	in	ADP
esrj-95748	53	2	the	the	DET
esrj-95748	53	3	next	next	ADJ
esrj-95748	53	4	step	step	NOUN
esrj-95748	53	5	,	,	PUNCT
esrj-95748	53	6	the	the	DET
esrj-95748	53	7	evidential	evidential	ADJ
esrj-95748	53	8	belief	belief	NOUN
esrj-95748	53	9	function	function	NOUN
esrj-95748	53	10	model	model	NOUN
esrj-95748	53	11	was	be	AUX
esrj-95748	53	12	employed	employ	VERB
esrj-95748	53	13	to	to	PART
esrj-95748	53	14	evaluate	evaluate	VERB
esrj-95748	53	15	the	the	DET
esrj-95748	53	16	relationship	relationship	NOUN
esrj-95748	53	17	between	between	ADP
esrj-95748	53	18	gullied	gully	VERB
esrj-95748	53	19	locations	location	NOUN
esrj-95748	53	20	and	and	CCONJ
esrj-95748	53	21	conditioning	conditioning	NOUN
esrj-95748	53	22	factors	factor	NOUN
esrj-95748	53	23	.	.	PUNCT
esrj-95748	54	1	finally	finally	ADV
esrj-95748	54	2	,	,	PUNCT
esrj-95748	54	3	considering	consider	VERB
esrj-95748	54	4	the	the	DET
esrj-95748	54	5	importance	importance	NOUN
esrj-95748	54	6	of	of	ADP
esrj-95748	54	7	this	this	DET
esrj-95748	54	8	hazard	hazard	NOUN
esrj-95748	54	9	and	and	CCONJ
esrj-95748	54	10	its	its	PRON
esrj-95748	54	11	global	global	ADJ
esrj-95748	54	12	consequences	consequence	NOUN
esrj-95748	54	13	,	,	PUNCT
esrj-95748	54	14	the	the	DET
esrj-95748	54	15	present	present	ADJ
esrj-95748	54	16	study	study	NOUN
esrj-95748	54	17	employed	employ	VERB
esrj-95748	54	18	predictive	predictive	ADJ
esrj-95748	54	19	machine	machine	NOUN
esrj-95748	54	20	learning	learn	VERB
esrj-95748	54	21	techniques	technique	NOUN
esrj-95748	54	22	,	,	PUNCT
esrj-95748	54	23	including	include	VERB
esrj-95748	54	24	support	support	NOUN
esrj-95748	54	25	vector	vector	NOUN
esrj-95748	54	26	machine	machine	NOUN
esrj-95748	54	27	with	with	ADP
esrj-95748	54	28	two	two	NUM
esrj-95748	54	29	kernel	kernel	NOUN
esrj-95748	54	30	types	type	NOUN
esrj-95748	54	31	and	and	CCONJ
esrj-95748	54	32	boosted	boost	VERB
esrj-95748	54	33	regression	regression	NOUN
esrj-95748	54	34	tree	tree	NOUN
esrj-95748	54	35	for	for	ADP
esrj-95748	54	36	modeling	model	VERB
esrj-95748	54	37	the	the	DET
esrj-95748	54	38	occurrence	occurrence	NOUN
esrj-95748	54	39	of	of	ADP
esrj-95748	54	40	gully	gully	ADJ
esrj-95748	54	41	erosion	erosion	NOUN
esrj-95748	54	42	within	within	ADP
esrj-95748	54	43	a	a	DET
esrj-95748	54	44	prone	prone	ADJ
esrj-95748	54	45	watershed	watershed	NOUN
esrj-95748	54	46	located	locate	VERB
esrj-95748	54	47	in	in	ADP
esrj-95748	54	48	northern	northern	ADJ
esrj-95748	54	49	iran	iran	PROPN
esrj-95748	54	50	.	.	PUNCT
esrj-95748	55	1	finally	finally	ADV
esrj-95748	55	2	,	,	PUNCT
esrj-95748	55	3	the	the	DET
esrj-95748	55	4	predictive	predictive	ADJ
esrj-95748	55	5	performance	performance	NOUN
esrj-95748	55	6	of	of	ADP
esrj-95748	55	7	the	the	DET
esrj-95748	55	8	models	model	NOUN
esrj-95748	55	9	was	be	AUX
esrj-95748	55	10	evaluated	evaluate	VERB
esrj-95748	55	11	in	in	ADP
esrj-95748	55	12	terms	term	NOUN
esrj-95748	55	13	of	of	ADP
esrj-95748	55	14	their	their	PRON
esrj-95748	55	15	discrimination	discrimination	NOUN
esrj-95748	55	16	and	and	CCONJ
esrj-95748	55	17	reliability	reliability	NOUN
esrj-95748	55	18	.	.	PUNCT
esrj-95748	56	1	materials	material	NOUN
esrj-95748	56	2	and	and	CCONJ
esrj-95748	56	3	methods	method	NOUN
esrj-95748	56	4	study	study	NOUN
esrj-95748	56	5	region	region	NOUN
esrj-95748	56	6	the	the	DET
esrj-95748	56	7	present	present	ADJ
esrj-95748	56	8	study	study	NOUN
esrj-95748	56	9	was	be	AUX
esrj-95748	56	10	implemented	implement	VERB
esrj-95748	56	11	on	on	ADP
esrj-95748	56	12	gorganrud	gorganrud	NOUN
esrj-95748	56	13	watershed	watershed	NOUN
esrj-95748	56	14	located	locate	VERB
esrj-95748	56	15	in	in	ADP
esrj-95748	56	16	golestan	golestan	PROPN
esrj-95748	56	17	province	province	NOUN
esrj-95748	56	18	,	,	PUNCT
esrj-95748	56	19	northern	northern	ADJ
esrj-95748	56	20	iran	iran	PROPN
esrj-95748	56	21	(	(	PUNCT
esrj-95748	56	22	37	37	NUM
esrj-95748	56	23	◦	◦	NOUN
esrj-95748	56	24	30′00″	30′00″	NUM
esrj-95748	56	25	to	to	ADP
esrj-95748	56	26	37	37	NUM
esrj-95748	56	27	◦	◦	NOUN
esrj-95748	56	28	50′00″n	50′00″n	NOUN
esrj-95748	56	29	and	and	CCONJ
esrj-95748	56	30	55	55	NUM
esrj-95748	56	31	◦	◦	NOUN
esrj-95748	56	32	31′40″	31′40″	NUM
esrj-95748	56	33	to	to	ADP
esrj-95748	56	34	56	56	NUM
esrj-95748	56	35	◦	◦	NOUN
esrj-95748	56	36	02′10″e	02′10″e	NOUN
esrj-95748	56	37	)	)	PUNCT
esrj-95748	56	38	(	(	PUNCT
esrj-95748	56	39	figure	figure	NOUN
esrj-95748	56	40	1	1	NUM
esrj-95748	56	41	)	)	PUNCT
esrj-95748	56	42	.	.	PUNCT
esrj-95748	57	1	the	the	DET
esrj-95748	57	2	maximum	maximum	ADJ
esrj-95748	57	3	and	and	CCONJ
esrj-95748	57	4	minimum	minimum	ADJ
esrj-95748	57	5	altitude	altitude	NOUN
esrj-95748	57	6	of	of	ADP
esrj-95748	57	7	the	the	DET
esrj-95748	57	8	watershed	watershed	NOUN
esrj-95748	57	9	is	be	AUX
esrj-95748	57	10	2,180	2,180	NUM
esrj-95748	57	11	and	and	CCONJ
esrj-95748	57	12	46	46	NUM
esrj-95748	57	13	meters	meter	NOUN
esrj-95748	57	14	above	above	ADP
esrj-95748	57	15	sea	sea	NOUN
esrj-95748	57	16	level	level	NOUN
esrj-95748	57	17	.	.	PUNCT
esrj-95748	58	1	based	base	VERB
esrj-95748	58	2	on	on	ADP
esrj-95748	58	3	the	the	DET
esrj-95748	58	4	iranian	iranian	ADJ
esrj-95748	58	5	meteorological	meteorological	ADJ
esrj-95748	58	6	organization	organization	NOUN
esrj-95748	58	7	,	,	PUNCT
esrj-95748	58	8	the	the	DET
esrj-95748	58	9	study	study	NOUN
esrj-95748	58	10	area	area	NOUN
esrj-95748	58	11	’s	’s	PART
esrj-95748	58	12	climate	climate	NOUN
esrj-95748	58	13	is	be	AUX
esrj-95748	58	14	semi	semi	ADJ
esrj-95748	58	15	-	-	ADJ
esrj-95748	58	16	arid	arid	ADJ
esrj-95748	58	17	with	with	ADP
esrj-95748	58	18	an	an	DET
esrj-95748	58	19	average	average	ADJ
esrj-95748	58	20	annual	annual	ADJ
esrj-95748	58	21	temperature	temperature	NOUN
esrj-95748	58	22	of	of	ADP
esrj-95748	58	23	18.2	18.2	NUM
esrj-95748	58	24	°	°	NOUN
esrj-95748	58	25	c	c	NOUN
esrj-95748	58	26	and	and	CCONJ
esrj-95748	58	27	385	385	NUM
esrj-95748	58	28	mm	mm	NOUN
esrj-95748	58	29	mean	mean	VERB
esrj-95748	58	30	annual	annual	ADJ
esrj-95748	58	31	precipitation	precipitation	NOUN
esrj-95748	58	32	.	.	PUNCT
esrj-95748	59	1	more	more	ADJ
esrj-95748	59	2	than	than	ADP
esrj-95748	59	3	half	half	NOUN
esrj-95748	59	4	of	of	ADP
esrj-95748	59	5	the	the	DET
esrj-95748	59	6	region	region	NOUN
esrj-95748	59	7	exhibits	exhibit	VERB
esrj-95748	59	8	mountainous	mountainous	ADJ
esrj-95748	59	9	morphology	morphology	NOUN
esrj-95748	59	10	belonging	belong	VERB
esrj-95748	59	11	to	to	ADP
esrj-95748	59	12	the	the	DET
esrj-95748	59	13	alborz	alborz	ADJ
esrj-95748	59	14	mountains	mountain	NOUN
esrj-95748	59	15	,	,	PUNCT
esrj-95748	59	16	with	with	ADP
esrj-95748	59	17	a	a	DET
esrj-95748	59	18	slope	slope	NOUN
esrj-95748	59	19	between	between	ADP
esrj-95748	59	20	0	0	NUM
esrj-95748	59	21	-	-	SYM
esrj-95748	59	22	61	61	NUM
esrj-95748	59	23	°	°	NOUN
esrj-95748	59	24	.	.	PUNCT
esrj-95748	60	1	figure	figure	NOUN
esrj-95748	60	2	4	4	NUM
esrj-95748	60	3	illustrates	illustrate	VERB
esrj-95748	60	4	the	the	DET
esrj-95748	60	5	most	most	ADV
esrj-95748	60	6	important	important	ADJ
esrj-95748	60	7	characteristics	characteristic	NOUN
esrj-95748	60	8	of	of	ADP
esrj-95748	60	9	the	the	DET
esrj-95748	60	10	study	study	NOUN
esrj-95748	60	11	region	region	NOUN
esrj-95748	60	12	in	in	ADP
esrj-95748	60	13	terms	term	NOUN
esrj-95748	60	14	of	of	ADP
esrj-95748	60	15	land	land	NOUN
esrj-95748	60	16	use	use	NOUN
esrj-95748	60	17	/	/	SYM
esrj-95748	60	18	cover	cover	NOUN
esrj-95748	60	19	and	and	CCONJ
esrj-95748	60	20	lithological	lithological	ADJ
esrj-95748	60	21	structure	structure	NOUN
esrj-95748	60	22	.	.	PUNCT
esrj-95748	61	1	rangeland	rangeland	NOUN
esrj-95748	61	2	is	be	AUX
esrj-95748	61	3	the	the	DET
esrj-95748	61	4	dominant	dominant	ADJ
esrj-95748	61	5	pattern	pattern	NOUN
esrj-95748	61	6	of	of	ADP
esrj-95748	61	7	land	land	NOUN
esrj-95748	61	8	use	use	NOUN
esrj-95748	61	9	in	in	ADP
esrj-95748	61	10	the	the	DET
esrj-95748	61	11	study	study	NOUN
esrj-95748	61	12	region	region	NOUN
esrj-95748	61	13	.	.	PUNCT
esrj-95748	62	1	in	in	ADP
esrj-95748	62	2	addition	addition	NOUN
esrj-95748	62	3	,	,	PUNCT
esrj-95748	62	4	loess	loess	NOUN
esrj-95748	62	5	deposits	deposit	NOUN
esrj-95748	62	6	are	be	AUX
esrj-95748	62	7	the	the	DET
esrj-95748	62	8	main	main	ADJ
esrj-95748	62	9	deposits	deposit	NOUN
esrj-95748	62	10	over	over	ADP
esrj-95748	62	11	the	the	DET
esrj-95748	62	12	region	region	NOUN
esrj-95748	62	13	.	.	PUNCT
esrj-95748	63	1	based	base	VERB
esrj-95748	63	2	on	on	ADP
esrj-95748	63	3	the	the	DET
esrj-95748	63	4	soil	soil	NOUN
esrj-95748	63	5	taxonomy	taxonomy	NOUN
esrj-95748	63	6	system	system	NOUN
esrj-95748	63	7	,	,	PUNCT
esrj-95748	63	8	the	the	DET
esrj-95748	63	9	soil	soil	NOUN
esrj-95748	63	10	type	type	NOUN
esrj-95748	63	11	of	of	ADP
esrj-95748	63	12	the	the	DET
esrj-95748	63	13	studied	study	VERB
esrj-95748	63	14	region	region	NOUN
esrj-95748	63	15	is	be	AUX
esrj-95748	63	16	classified	classify	VERB
esrj-95748	63	17	under	under	ADP
esrj-95748	63	18	the	the	DET
esrj-95748	63	19	mollisol	mollisol	NOUN
esrj-95748	63	20	order	order	NOUN
esrj-95748	63	21	.	.	PUNCT
esrj-95748	64	1	these	these	DET
esrj-95748	64	2	factors	factor	NOUN
esrj-95748	64	3	caused	cause	VERB
esrj-95748	64	4	that	that	SCONJ
esrj-95748	64	5	over	over	ADP
esrj-95748	64	6	70	70	NUM
esrj-95748	64	7	%	%	NOUN
esrj-95748	64	8	of	of	ADP
esrj-95748	64	9	the	the	DET
esrj-95748	64	10	region	region	NOUN
esrj-95748	64	11	suffered	suffer	VERB
esrj-95748	64	12	from	from	ADP
esrj-95748	64	13	various	various	ADJ
esrj-95748	64	14	degrees	degree	NOUN
esrj-95748	64	15	of	of	ADP
esrj-95748	64	16	soil	soil	NOUN
esrj-95748	64	17	erosion	erosion	NOUN
esrj-95748	64	18	as	as	ADP
esrj-95748	64	19	multiple	multiple	ADJ
esrj-95748	64	20	rills	rill	NOUN
esrj-95748	64	21	and	and	CCONJ
esrj-95748	64	22	gullies	gully	NOUN
esrj-95748	64	23	.	.	PUNCT
esrj-95748	65	1	mean	mean	VERB
esrj-95748	65	2	annual	annual	ADJ
esrj-95748	65	3	soil	soil	NOUN
esrj-95748	65	4	losses	loss	NOUN
esrj-95748	65	5	caused	cause	VERB
esrj-95748	65	6	by	by	ADP
esrj-95748	65	7	the	the	DET
esrj-95748	65	8	gully	gully	ADJ
esrj-95748	65	9	erosion	erosion	NOUN
esrj-95748	65	10	in	in	ADP
esrj-95748	65	11	the	the	DET
esrj-95748	65	12	region	region	NOUN
esrj-95748	65	13	estimate	estimate	VERB
esrj-95748	65	14	approximately	approximately	ADV
esrj-95748	65	15	160	160	NUM
esrj-95748	65	16	tons	ton	NOUN
esrj-95748	65	17	per	per	ADP
esrj-95748	65	18	hectare	hectare	NOUN
esrj-95748	65	19	.	.	PUNCT
esrj-95748	66	1	the	the	DET
esrj-95748	66	2	watershed	watershed	ADJ
esrj-95748	66	3	area	area	NOUN
esrj-95748	66	4	in	in	ADP
esrj-95748	66	5	the	the	DET
esrj-95748	66	6	upslope	upslope	NOUN
esrj-95748	66	7	parts	part	NOUN
esrj-95748	66	8	of	of	ADP
esrj-95748	66	9	the	the	DET
esrj-95748	66	10	rill	rill	NOUN
esrj-95748	66	11	and	and	CCONJ
esrj-95748	66	12	gully	gully	NOUN
esrj-95748	66	13	sites	site	NOUN
esrj-95748	66	14	is	be	AUX
esrj-95748	66	15	variable	variable	ADJ
esrj-95748	66	16	between	between	ADP
esrj-95748	66	17	2,000	2,000	NUM
esrj-95748	66	18	-	-	SYM
esrj-95748	66	19	43,070	43,070	NUM
esrj-95748	66	20	m2	m2	PROPN
esrj-95748	66	21	.	.	PUNCT
esrj-95748	67	1	this	this	DET
esrj-95748	67	2	condition	condition	NOUN
esrj-95748	67	3	strongly	strongly	ADV
esrj-95748	67	4	affected	affect	VERB
esrj-95748	67	5	the	the	DET
esrj-95748	67	6	rate	rate	NOUN
esrj-95748	67	7	of	of	ADP
esrj-95748	67	8	runoff	runoff	NOUN
esrj-95748	67	9	discharge	discharge	NOUN
esrj-95748	67	10	into	into	ADP
esrj-95748	67	11	rill	rill	NOUN
esrj-95748	67	12	channels	channel	NOUN
esrj-95748	67	13	,	,	PUNCT
esrj-95748	67	14	encouraging	encourage	VERB
esrj-95748	67	15	the	the	DET
esrj-95748	67	16	accelerated	accelerated	ADJ
esrj-95748	67	17	progression	progression	NOUN
esrj-95748	67	18	of	of	ADP
esrj-95748	67	19	the	the	DET
esrj-95748	67	20	channels	channel	NOUN
esrj-95748	67	21	(	(	PUNCT
esrj-95748	67	22	figure	figure	NOUN
esrj-95748	67	23	2	2	NUM
esrj-95748	67	24	)	)	PUNCT
esrj-95748	67	25	.	.	PUNCT
esrj-95748	68	1	figure	figure	NOUN
esrj-95748	68	2	1	1	NUM
esrj-95748	68	3	.	.	PUNCT
esrj-95748	69	1	location	location	NOUN
esrj-95748	69	2	of	of	ADP
esrj-95748	69	3	the	the	DET
esrj-95748	69	4	study	study	NOUN
esrj-95748	69	5	watershed	watershed	NOUN
esrj-95748	69	6	(	(	PUNCT
esrj-95748	69	7	a	a	NOUN
esrj-95748	69	8	)	)	PUNCT
esrj-95748	69	9	and	and	CCONJ
esrj-95748	69	10	gully	gully	NOUN
esrj-95748	69	11	erosion	erosion	NOUN
esrj-95748	69	12	inventory	inventory	NOUN
esrj-95748	69	13	map	map	NOUN
esrj-95748	69	14	(	(	PUNCT
esrj-95748	69	15	b	b	NOUN
esrj-95748	69	16	)	)	PUNCT
esrj-95748	69	17	2.2	2.2	NUM
esrj-95748	69	18	methodology	methodology	NOUN
esrj-95748	69	19	the	the	DET
esrj-95748	69	20	methodology	methodology	NOUN
esrj-95748	69	21	employed	employ	VERB
esrj-95748	69	22	in	in	ADP
esrj-95748	69	23	the	the	DET
esrj-95748	69	24	present	present	ADJ
esrj-95748	69	25	study	study	NOUN
esrj-95748	69	26	includes	include	VERB
esrj-95748	69	27	the	the	DET
esrj-95748	69	28	following	follow	VERB
esrj-95748	69	29	steps	step	NOUN
esrj-95748	69	30	:	:	PUNCT
esrj-95748	69	31	after	after	SCONJ
esrj-95748	69	32	the	the	DET
esrj-95748	69	33	generation	generation	NOUN
esrj-95748	69	34	of	of	ADP
esrj-95748	69	35	the	the	DET
esrj-95748	69	36	gully	gully	NOUN
esrj-95748	69	37	inventory	inventory	NOUN
esrj-95748	69	38	map	map	NOUN
esrj-95748	69	39	,	,	PUNCT
esrj-95748	69	40	information	information	NOUN
esrj-95748	69	41	on	on	ADP
esrj-95748	69	42	twelve	twelve	NUM
esrj-95748	69	43	factors	factor	NOUN
esrj-95748	69	44	controlling	control	VERB
esrj-95748	69	45	gully	gully	ADJ
esrj-95748	69	46	development	development	NOUN
esrj-95748	69	47	was	be	AUX
esrj-95748	69	48	prepared	prepare	VERB
esrj-95748	69	49	.	.	PUNCT
esrj-95748	70	1	in	in	ADP
esrj-95748	70	2	the	the	DET
esrj-95748	70	3	next	next	ADJ
esrj-95748	70	4	step	step	NOUN
esrj-95748	70	5	,	,	PUNCT
esrj-95748	70	6	the	the	DET
esrj-95748	70	7	spatial	spatial	ADJ
esrj-95748	70	8	425factors	425factors	PROPN
esrj-95748	70	9	affecting	affect	VERB
esrj-95748	70	10	topographic	topographic	ADJ
esrj-95748	70	11	thresholds	threshold	NOUN
esrj-95748	70	12	in	in	ADP
esrj-95748	70	13	gully	gully	ADJ
esrj-95748	70	14	erosion	erosion	NOUN
esrj-95748	70	15	occurrence	occurrence	NOUN
esrj-95748	70	16	and	and	CCONJ
esrj-95748	70	17	its	its	PRON
esrj-95748	70	18	management	management	NOUN
esrj-95748	70	19	using	use	VERB
esrj-95748	70	20	predictive	predictive	ADJ
esrj-95748	70	21	machine	machine	NOUN
esrj-95748	70	22	learning	learning	NOUN
esrj-95748	70	23	models	model	NOUN
esrj-95748	70	24	correlation	correlation	NOUN
esrj-95748	70	25	among	among	ADP
esrj-95748	70	26	gullied	gullied	ADJ
esrj-95748	70	27	locations	location	NOUN
esrj-95748	70	28	and	and	CCONJ
esrj-95748	70	29	causative	causative	ADJ
esrj-95748	70	30	variables	variable	NOUN
esrj-95748	70	31	was	be	AUX
esrj-95748	70	32	determined	determine	VERB
esrj-95748	70	33	using	use	VERB
esrj-95748	70	34	the	the	DET
esrj-95748	70	35	evidential	evidential	ADJ
esrj-95748	70	36	belief	belief	NOUN
esrj-95748	70	37	function	function	NOUN
esrj-95748	70	38	algorithm	algorithm	NOUN
esrj-95748	70	39	(	(	PUNCT
esrj-95748	70	40	ebf	ebf	NOUN
esrj-95748	70	41	)	)	PUNCT
esrj-95748	70	42	.	.	PUNCT
esrj-95748	71	1	the	the	DET
esrj-95748	71	2	importance	importance	NOUN
esrj-95748	71	3	of	of	ADP
esrj-95748	71	4	causative	causative	ADJ
esrj-95748	71	5	factors	factor	NOUN
esrj-95748	71	6	was	be	AUX
esrj-95748	71	7	then	then	ADV
esrj-95748	71	8	weighed	weigh	VERB
esrj-95748	71	9	using	use	VERB
esrj-95748	71	10	the	the	DET
esrj-95748	71	11	boruta	boruta	NOUN
esrj-95748	71	12	algorithm	algorithm	NOUN
esrj-95748	71	13	.	.	PUNCT
esrj-95748	72	1	in	in	ADP
esrj-95748	72	2	the	the	DET
esrj-95748	72	3	final	final	ADJ
esrj-95748	72	4	steps	step	NOUN
esrj-95748	72	5	,	,	PUNCT
esrj-95748	72	6	the	the	DET
esrj-95748	72	7	spatial	spatial	ADJ
esrj-95748	72	8	prediction	prediction	NOUN
esrj-95748	72	9	of	of	ADP
esrj-95748	72	10	gully	gully	ADJ
esrj-95748	72	11	erosion	erosion	NOUN
esrj-95748	72	12	susceptibility	susceptibility	NOUN
esrj-95748	72	13	was	be	AUX
esrj-95748	72	14	modeled	model	VERB
esrj-95748	72	15	using	use	VERB
esrj-95748	72	16	the	the	DET
esrj-95748	72	17	support	support	NOUN
esrj-95748	72	18	vector	vector	NOUN
esrj-95748	72	19	machine	machine	NOUN
esrj-95748	72	20	(	(	PUNCT
esrj-95748	72	21	svm	svm	PROPN
esrj-95748	72	22	)	)	PUNCT
esrj-95748	72	23	model	model	NOUN
esrj-95748	72	24	with	with	ADP
esrj-95748	72	25	two	two	NUM
esrj-95748	72	26	kernel	kernel	NOUN
esrj-95748	72	27	types	type	NOUN
esrj-95748	72	28	(	(	PUNCT
esrj-95748	72	29	linear	linear	ADJ
esrj-95748	72	30	kernel	kernel	NOUN
esrj-95748	72	31	and	and	CCONJ
esrj-95748	72	32	radial	radial	ADJ
esrj-95748	72	33	basis	basis	NOUN
esrj-95748	72	34	function	function	NOUN
esrj-95748	72	35	)	)	PUNCT
esrj-95748	72	36	and	and	CCONJ
esrj-95748	72	37	boosted	boost	VERB
esrj-95748	72	38	regression	regression	NOUN
esrj-95748	72	39	tree	tree	NOUN
esrj-95748	72	40	(	(	PUNCT
esrj-95748	72	41	brt	brt	NOUN
esrj-95748	72	42	)	)	PUNCT
esrj-95748	72	43	algorithm	algorithm	NOUN
esrj-95748	72	44	.	.	PUNCT
esrj-95748	73	1	the	the	DET
esrj-95748	73	2	predictive	predictive	ADJ
esrj-95748	73	3	performance	performance	NOUN
esrj-95748	73	4	of	of	ADP
esrj-95748	73	5	models	model	NOUN
esrj-95748	73	6	was	be	AUX
esrj-95748	73	7	discriminated	discriminate	VERB
esrj-95748	73	8	using	use	VERB
esrj-95748	73	9	the	the	DET
esrj-95748	73	10	receiver	receiver	ADJ
esrj-95748	73	11	operating	operate	VERB
esrj-95748	73	12	characteristic	characteristic	ADJ
esrj-95748	73	13	curve	curve	NOUN
esrj-95748	73	14	(	(	PUNCT
esrj-95748	73	15	roc	roc	PROPN
esrj-95748	73	16	)	)	PUNCT
esrj-95748	73	17	and	and	CCONJ
esrj-95748	73	18	the	the	DET
esrj-95748	73	19	area	area	NOUN
esrj-95748	73	20	under	under	ADP
esrj-95748	73	21	the	the	DET
esrj-95748	73	22	curve	curve	NOUN
esrj-95748	73	23	(	(	PUNCT
esrj-95748	73	24	auc	auc	NOUN
esrj-95748	73	25	)	)	PUNCT
esrj-95748	73	26	.	.	PUNCT
esrj-95748	74	1	the	the	DET
esrj-95748	74	2	reliability	reliability	NOUN
esrj-95748	74	3	of	of	ADP
esrj-95748	74	4	model	model	NOUN
esrj-95748	74	5	accuracy	accuracy	NOUN
esrj-95748	74	6	was	be	AUX
esrj-95748	74	7	also	also	ADV
esrj-95748	74	8	evaluated	evaluate	VERB
esrj-95748	74	9	using	use	VERB
esrj-95748	74	10	the	the	DET
esrj-95748	74	11	coefficient	coefficient	NOUN
esrj-95748	74	12	of	of	ADP
esrj-95748	74	13	determination	determination	NOUN
esrj-95748	74	14	(	(	PUNCT
esrj-95748	74	15	r2	r2	PROPN
esrj-95748	74	16	,	,	PUNCT
esrj-95748	74	17	for	for	ADP
esrj-95748	74	18	the	the	DET
esrj-95748	74	19	calibration	calibration	NOUN
esrj-95748	74	20	)	)	PUNCT
esrj-95748	74	21	and	and	CCONJ
esrj-95748	74	22	root	root	NOUN
esrj-95748	74	23	mean	mean	NOUN
esrj-95748	74	24	square	square	ADJ
esrj-95748	74	25	error	error	NOUN
esrj-95748	74	26	(	(	PUNCT
esrj-95748	74	27	rmse	rmse	NOUN
esrj-95748	74	28	)	)	PUNCT
esrj-95748	74	29	.	.	PUNCT
esrj-95748	75	1	gully	gully	PROPN
esrj-95748	75	2	inventory	inventory	NOUN
esrj-95748	75	3	map	map	VERB
esrj-95748	75	4	the	the	DET
esrj-95748	75	5	first	first	ADJ
esrj-95748	75	6	step	step	NOUN
esrj-95748	75	7	for	for	ADP
esrj-95748	75	8	the	the	DET
esrj-95748	75	9	modeling	modeling	NOUN
esrj-95748	75	10	process	process	NOUN
esrj-95748	75	11	is	be	AUX
esrj-95748	75	12	preparing	prepare	VERB
esrj-95748	75	13	the	the	DET
esrj-95748	75	14	gully	gully	ADJ
esrj-95748	75	15	inventory	inventory	NOUN
esrj-95748	75	16	map	map	NOUN
esrj-95748	75	17	,	,	PUNCT
esrj-95748	75	18	exhibiting	exhibit	VERB
esrj-95748	75	19	the	the	DET
esrj-95748	75	20	spatial	spatial	ADJ
esrj-95748	75	21	distribution	distribution	NOUN
esrj-95748	75	22	of	of	ADP
esrj-95748	75	23	gullied	gully	VERB
esrj-95748	75	24	locations	location	NOUN
esrj-95748	75	25	within	within	ADP
esrj-95748	75	26	the	the	DET
esrj-95748	75	27	study	study	NOUN
esrj-95748	75	28	watershed	watershe	VERB
esrj-95748	75	29	.	.	PUNCT
esrj-95748	76	1	considering	consider	VERB
esrj-95748	76	2	the	the	DET
esrj-95748	76	3	present	present	ADJ
esrj-95748	76	4	and	and	CCONJ
esrj-95748	76	5	historical	historical	ADJ
esrj-95748	76	6	distributions	distribution	NOUN
esrj-95748	76	7	of	of	ADP
esrj-95748	76	8	gullies	gully	NOUN
esrj-95748	76	9	,	,	PUNCT
esrj-95748	76	10	the	the	DET
esrj-95748	76	11	future	future	ADJ
esrj-95748	76	12	risk	risk	NOUN
esrj-95748	76	13	of	of	ADP
esrj-95748	76	14	the	the	DET
esrj-95748	76	15	gully	gully	PROPN
esrj-95748	76	16	development	development	NOUN
esrj-95748	76	17	can	can	AUX
esrj-95748	76	18	be	be	AUX
esrj-95748	76	19	predicted	predict	VERB
esrj-95748	76	20	.	.	PUNCT
esrj-95748	77	1	based	base	VERB
esrj-95748	77	2	on	on	ADP
esrj-95748	77	3	data	datum	NOUN
esrj-95748	77	4	taken	take	VERB
esrj-95748	77	5	from	from	ADP
esrj-95748	77	6	the	the	DET
esrj-95748	77	7	natural	natural	ADJ
esrj-95748	77	8	resources	resource	NOUN
esrj-95748	77	9	organization	organization	NOUN
esrj-95748	77	10	of	of	ADP
esrj-95748	77	11	golestan	golestan	PROPN
esrj-95748	77	12	province	province	NOUN
esrj-95748	77	13	,	,	PUNCT
esrj-95748	77	14	gullied	gully	VERB
esrj-95748	77	15	locations	location	NOUN
esrj-95748	77	16	were	be	AUX
esrj-95748	77	17	determined	determine	VERB
esrj-95748	77	18	.	.	PUNCT
esrj-95748	78	1	then	then	ADV
esrj-95748	78	2	,	,	PUNCT
esrj-95748	78	3	these	these	DET
esrj-95748	78	4	data	datum	NOUN
esrj-95748	78	5	were	be	AUX
esrj-95748	78	6	validated	validate	VERB
esrj-95748	78	7	through	through	ADP
esrj-95748	78	8	field	field	NOUN
esrj-95748	78	9	surveys	survey	NOUN
esrj-95748	78	10	and	and	CCONJ
esrj-95748	78	11	google	google	PROPN
esrj-95748	78	12	earth	earth	NOUN
esrj-95748	78	13	images	image	NOUN
esrj-95748	78	14	.	.	PUNCT
esrj-95748	79	1	overall	overall	ADJ
esrj-95748	79	2	,	,	PUNCT
esrj-95748	79	3	1,041	1,041	NUM
esrj-95748	79	4	gullied	gully	VERB
esrj-95748	79	5	areas	area	NOUN
esrj-95748	79	6	were	be	AUX
esrj-95748	79	7	mapped	map	VERB
esrj-95748	79	8	in	in	ADP
esrj-95748	79	9	the	the	DET
esrj-95748	79	10	study	study	NOUN
esrj-95748	79	11	region	region	NOUN
esrj-95748	79	12	.	.	PUNCT
esrj-95748	80	1	to	to	PART
esrj-95748	80	2	split	split	VERB
esrj-95748	80	3	the	the	DET
esrj-95748	80	4	gully	gully	NOUN
esrj-95748	80	5	data	datum	NOUN
esrj-95748	80	6	into	into	ADP
esrj-95748	80	7	two	two	NUM
esrj-95748	80	8	datasets	dataset	NOUN
esrj-95748	80	9	of	of	ADP
esrj-95748	80	10	validation	validation	NOUN
esrj-95748	80	11	(	(	PUNCT
esrj-95748	80	12	30	30	NUM
esrj-95748	80	13	%	%	NOUN
esrj-95748	80	14	)	)	PUNCT
esrj-95748	80	15	and	and	CCONJ
esrj-95748	80	16	train	train	NOUN
esrj-95748	80	17	(	(	PUNCT
esrj-95748	80	18	70	70	NUM
esrj-95748	80	19	%	%	NOUN
esrj-95748	80	20	)	)	PUNCT
esrj-95748	80	21	,	,	PUNCT
esrj-95748	80	22	a	a	DET
esrj-95748	80	23	randomly	randomly	ADV
esrj-95748	80	24	partitioned	partition	VERB
esrj-95748	80	25	algorithm	algorithm	NOUN
esrj-95748	80	26	was	be	AUX
esrj-95748	80	27	employed	employ	VERB
esrj-95748	80	28	using	use	VERB
esrj-95748	80	29	the	the	DET
esrj-95748	80	30	sub	sub	ADJ
esrj-95748	80	31	-	-	ADJ
esrj-95748	80	32	set	set	ADJ
esrj-95748	80	33	features	feature	NOUN
esrj-95748	80	34	tools	tool	NOUN
esrj-95748	80	35	in	in	ADP
esrj-95748	80	36	arcgis	arcgis	PROPN
esrj-95748	80	37	(	(	PUNCT
esrj-95748	80	38	figure	figure	NOUN
esrj-95748	80	39	1b	1b	NUM
esrj-95748	80	40	)	)	PUNCT
esrj-95748	80	41	.	.	PUNCT
esrj-95748	81	1	gully	gully	PROPN
esrj-95748	81	2	conditioning	condition	VERB
esrj-95748	81	3	factors	factor	NOUN
esrj-95748	81	4	gully	gully	ADJ
esrj-95748	81	5	erosion	erosion	NOUN
esrj-95748	81	6	is	be	AUX
esrj-95748	81	7	a	a	DET
esrj-95748	81	8	threshold	threshold	NOUN
esrj-95748	81	9	-	-	PUNCT
esrj-95748	81	10	dependent	dependent	ADJ
esrj-95748	81	11	process	process	NOUN
esrj-95748	81	12	,	,	PUNCT
esrj-95748	81	13	which	which	PRON
esrj-95748	81	14	different	different	ADJ
esrj-95748	81	15	conditioning	conditioning	NOUN
esrj-95748	81	16	factors	factor	NOUN
esrj-95748	81	17	stimulate	stimulate	VERB
esrj-95748	81	18	the	the	DET
esrj-95748	81	19	occurrence	occurrence	NOUN
esrj-95748	81	20	and	and	CCONJ
esrj-95748	81	21	development	development	NOUN
esrj-95748	81	22	of	of	ADP
esrj-95748	81	23	this	this	DET
esrj-95748	81	24	hazard	hazard	NOUN
esrj-95748	81	25	(	(	PUNCT
esrj-95748	81	26	gayen	gayen	NOUN
esrj-95748	81	27	et	et	PROPN
esrj-95748	81	28	al	al	PROPN
esrj-95748	81	29	.	.	PROPN
esrj-95748	81	30	,	,	PUNCT
esrj-95748	81	31	2019	2019	NUM
esrj-95748	81	32	)	)	PUNCT
esrj-95748	81	33	.	.	PUNCT
esrj-95748	82	1	to	to	PART
esrj-95748	82	2	predict	predict	VERB
esrj-95748	82	3	gully	gully	ADJ
esrj-95748	82	4	erosion	erosion	NOUN
esrj-95748	82	5	,	,	PUNCT
esrj-95748	82	6	using	use	VERB
esrj-95748	82	7	different	different	ADJ
esrj-95748	82	8	machine	machine	NOUN
esrj-95748	82	9	learning	learning	NOUN
esrj-95748	82	10	models	model	NOUN
esrj-95748	82	11	,	,	PUNCT
esrj-95748	82	12	the	the	DET
esrj-95748	82	13	identification	identification	NOUN
esrj-95748	82	14	of	of	ADP
esrj-95748	82	15	factors	factor	NOUN
esrj-95748	82	16	affecting	affect	VERB
esrj-95748	82	17	gully	gully	ADJ
esrj-95748	82	18	development	development	NOUN
esrj-95748	82	19	is	be	AUX
esrj-95748	82	20	an	an	DET
esrj-95748	82	21	important	important	ADJ
esrj-95748	82	22	step	step	NOUN
esrj-95748	82	23	.	.	PUNCT
esrj-95748	83	1	based	base	VERB
esrj-95748	83	2	on	on	ADP
esrj-95748	83	3	previous	previous	ADJ
esrj-95748	83	4	studies	study	NOUN
esrj-95748	83	5	(	(	PUNCT
esrj-95748	83	6	zabihi	zabihi	NOUN
esrj-95748	83	7	et	et	PROPN
esrj-95748	83	8	al	al	PROPN
esrj-95748	83	9	.	.	PROPN
esrj-95748	83	10	,	,	PUNCT
esrj-95748	83	11	2018	2018	NUM
esrj-95748	83	12	;	;	PUNCT
esrj-95748	83	13	arabameri	arabameri	PROPN
esrj-95748	83	14	et	et	PROPN
esrj-95748	83	15	al	al	PROPN
esrj-95748	83	16	.	.	PROPN
esrj-95748	83	17	,	,	PUNCT
esrj-95748	83	18	2018	2018	NUM
esrj-95748	83	19	)	)	PUNCT
esrj-95748	83	20	and	and	CCONJ
esrj-95748	83	21	field	field	NOUN
esrj-95748	83	22	survey	survey	NOUN
esrj-95748	83	23	,	,	PUNCT
esrj-95748	83	24	twelve	twelve	NUM
esrj-95748	83	25	conditioning	conditioning	NOUN
esrj-95748	83	26	factors	factor	NOUN
esrj-95748	83	27	were	be	AUX
esrj-95748	83	28	considered	consider	VERB
esrj-95748	83	29	as	as	ADP
esrj-95748	83	30	independent	independent	ADJ
esrj-95748	83	31	variables	variable	NOUN
esrj-95748	83	32	affecting	affect	VERB
esrj-95748	83	33	erosion	erosion	NOUN
esrj-95748	83	34	.	.	PUNCT
esrj-95748	84	1	figure	figure	NOUN
esrj-95748	84	2	2	2	NUM
esrj-95748	84	3	.	.	PUNCT
esrj-95748	84	4	typical	typical	ADJ
esrj-95748	84	5	images	image	NOUN
esrj-95748	84	6	taken	take	VERB
esrj-95748	84	7	from	from	ADP
esrj-95748	84	8	some	some	DET
esrj-95748	84	9	gullies	gully	NOUN
esrj-95748	84	10	within	within	ADP
esrj-95748	84	11	the	the	DET
esrj-95748	84	12	study	study	NOUN
esrj-95748	84	13	region	region	NOUN
esrj-95748	84	14	these	these	DET
esrj-95748	84	15	variables	variable	NOUN
esrj-95748	84	16	included	include	VERB
esrj-95748	84	17	elevation	elevation	NOUN
esrj-95748	84	18	,	,	PUNCT
esrj-95748	84	19	slope	slope	NOUN
esrj-95748	84	20	gradient	gradient	NOUN
esrj-95748	84	21	,	,	PUNCT
esrj-95748	84	22	slope	slope	NOUN
esrj-95748	84	23	aspect	aspect	NOUN
esrj-95748	84	24	,	,	PUNCT
esrj-95748	84	25	topographic	topographic	PROPN
esrj-95748	84	26	wetness	wetness	PROPN
esrj-95748	84	27	index	index	NOUN
esrj-95748	84	28	(	(	PUNCT
esrj-95748	84	29	twi	twi	NOUN
esrj-95748	84	30	)	)	PUNCT
esrj-95748	84	31	,	,	PUNCT
esrj-95748	84	32	stream	stream	NOUN
esrj-95748	84	33	power	power	NOUN
esrj-95748	84	34	index	index	NOUN
esrj-95748	84	35	(	(	PUNCT
esrj-95748	84	36	spi	spi	PROPN
esrj-95748	84	37	)	)	PUNCT
esrj-95748	84	38	,	,	PUNCT
esrj-95748	84	39	plan	plan	NOUN
esrj-95748	84	40	curvature	curvature	NOUN
esrj-95748	84	41	,	,	PUNCT
esrj-95748	84	42	drainage	drainage	NOUN
esrj-95748	84	43	density	density	NOUN
esrj-95748	84	44	,	,	PUNCT
esrj-95748	84	45	distance	distance	NOUN
esrj-95748	84	46	from	from	ADP
esrj-95748	84	47	the	the	DET
esrj-95748	84	48	river	river	NOUN
esrj-95748	84	49	,	,	PUNCT
esrj-95748	84	50	distance	distance	NOUN
esrj-95748	84	51	from	from	ADP
esrj-95748	84	52	the	the	DET
esrj-95748	84	53	road	road	NOUN
esrj-95748	84	54	,	,	PUNCT
esrj-95748	84	55	distance	distance	NOUN
esrj-95748	84	56	from	from	ADP
esrj-95748	84	57	the	the	DET
esrj-95748	84	58	fault	fault	NOUN
esrj-95748	84	59	,	,	PUNCT
esrj-95748	84	60	lithology	lithology	NOUN
esrj-95748	84	61	,	,	PUNCT
esrj-95748	84	62	and	and	CCONJ
esrj-95748	84	63	land	land	NOUN
esrj-95748	84	64	use	use	NOUN
esrj-95748	84	65	/	/	SYM
esrj-95748	84	66	cover	cover	NOUN
esrj-95748	84	67	.	.	PUNCT
esrj-95748	85	1	the	the	DET
esrj-95748	85	2	most	most	ADV
esrj-95748	85	3	important	important	ADJ
esrj-95748	85	4	topographic	topographic	ADJ
esrj-95748	85	5	factors	factor	NOUN
esrj-95748	85	6	that	that	PRON
esrj-95748	85	7	affect	affect	VERB
esrj-95748	85	8	gully	gully	ADJ
esrj-95748	85	9	erosion	erosion	NOUN
esrj-95748	85	10	are	be	AUX
esrj-95748	85	11	the	the	DET
esrj-95748	85	12	elevation	elevation	NOUN
esrj-95748	85	13	and	and	CCONJ
esrj-95748	85	14	slope	slope	NOUN
esrj-95748	85	15	gradient	gradient	NOUN
esrj-95748	85	16	(	(	PUNCT
esrj-95748	85	17	conoscenti	conoscenti	X
esrj-95748	85	18	et	et	PROPN
esrj-95748	85	19	al	al	PROPN
esrj-95748	85	20	.	.	PROPN
esrj-95748	85	21	,	,	PUNCT
esrj-95748	85	22	2014	2014	NUM
esrj-95748	85	23	)	)	PUNCT
esrj-95748	85	24	.	.	PUNCT
esrj-95748	86	1	these	these	DET
esrj-95748	86	2	factors	factor	NOUN
esrj-95748	86	3	significantly	significantly	ADV
esrj-95748	86	4	control	control	VERB
esrj-95748	86	5	vegetation	vegetation	NOUN
esrj-95748	86	6	density	density	NOUN
esrj-95748	86	7	,	,	PUNCT
esrj-95748	86	8	climatic	climatic	ADJ
esrj-95748	86	9	conditions	condition	NOUN
esrj-95748	86	10	,	,	PUNCT
esrj-95748	86	11	surface	surface	NOUN
esrj-95748	86	12	runoff	runoff	NOUN
esrj-95748	86	13	,	,	PUNCT
esrj-95748	86	14	and	and	CCONJ
esrj-95748	86	15	drainage	drainage	NOUN
esrj-95748	86	16	intensity	intensity	NOUN
esrj-95748	86	17	.	.	PUNCT
esrj-95748	87	1	the	the	DET
esrj-95748	87	2	slope	slope	NOUN
esrj-95748	87	3	aspect	aspect	NOUN
esrj-95748	87	4	is	be	AUX
esrj-95748	87	5	another	another	DET
esrj-95748	87	6	factor	factor	NOUN
esrj-95748	87	7	that	that	PRON
esrj-95748	87	8	plays	play	VERB
esrj-95748	87	9	a	a	DET
esrj-95748	87	10	crucial	crucial	ADJ
esrj-95748	87	11	role	role	NOUN
esrj-95748	87	12	in	in	ADP
esrj-95748	87	13	the	the	DET
esrj-95748	87	14	gully	gully	NOUN
esrj-95748	87	15	erosion	erosion	NOUN
esrj-95748	87	16	process	process	NOUN
esrj-95748	87	17	.	.	PUNCT
esrj-95748	88	1	this	this	DET
esrj-95748	88	2	factor	factor	NOUN
esrj-95748	88	3	regulates	regulate	VERB
esrj-95748	88	4	the	the	DET
esrj-95748	88	5	drying	dry	VERB
esrj-95748	88	6	effect	effect	NOUN
esrj-95748	88	7	of	of	ADP
esrj-95748	88	8	winds	wind	NOUN
esrj-95748	88	9	,	,	PUNCT
esrj-95748	88	10	morphological	morphological	ADJ
esrj-95748	88	11	structure	structure	NOUN
esrj-95748	88	12	of	of	ADP
esrj-95748	88	13	the	the	DET
esrj-95748	88	14	watershed	watershed	NOUN
esrj-95748	88	15	,	,	PUNCT
esrj-95748	88	16	and	and	CCONJ
esrj-95748	88	17	rate	rate	NOUN
esrj-95748	88	18	of	of	ADP
esrj-95748	88	19	rainfall	rainfall	NOUN
esrj-95748	88	20	,	,	PUNCT
esrj-95748	88	21	and	and	CCONJ
esrj-95748	88	22	related	related	ADJ
esrj-95748	88	23	runoff	runoff	NOUN
esrj-95748	88	24	,	,	PUNCT
esrj-95748	88	25	which	which	PRON
esrj-95748	88	26	in	in	ADP
esrj-95748	88	27	turn	turn	NOUN
esrj-95748	88	28	,	,	PUNCT
esrj-95748	88	29	influences	influence	VERB
esrj-95748	88	30	the	the	DET
esrj-95748	88	31	occurrence	occurrence	NOUN
esrj-95748	88	32	of	of	ADP
esrj-95748	88	33	gully	gully	ADJ
esrj-95748	88	34	erosion	erosion	NOUN
esrj-95748	88	35	(	(	PUNCT
esrj-95748	88	36	gayen	gayen	NOUN
esrj-95748	88	37	et	et	PROPN
esrj-95748	88	38	al	al	PROPN
esrj-95748	88	39	.	.	PROPN
esrj-95748	88	40	,	,	PUNCT
esrj-95748	88	41	2019	2019	NUM
esrj-95748	88	42	)	)	PUNCT
esrj-95748	88	43	.	.	PUNCT
esrj-95748	89	1	the	the	DET
esrj-95748	89	2	erosive	erosive	ADJ
esrj-95748	89	3	power	power	NOUN
esrj-95748	89	4	of	of	ADP
esrj-95748	89	5	overland	overland	NOUN
esrj-95748	89	6	flows	flow	NOUN
esrj-95748	89	7	can	can	AUX
esrj-95748	89	8	be	be	AUX
esrj-95748	89	9	illustrated	illustrate	VERB
esrj-95748	89	10	by	by	ADP
esrj-95748	89	11	the	the	DET
esrj-95748	89	12	stream	stream	NOUN
esrj-95748	89	13	power	power	NOUN
esrj-95748	89	14	index	index	NOUN
esrj-95748	89	15	(	(	PUNCT
esrj-95748	89	16	eq	eq	NOUN
esrj-95748	89	17	.	.	PROPN
esrj-95748	89	18	1	1	NUM
esrj-95748	89	19	)	)	PUNCT
esrj-95748	89	20	,	,	PUNCT
esrj-95748	89	21	which	which	PRON
esrj-95748	89	22	considers	consider	VERB
esrj-95748	89	23	contributing	contribute	VERB
esrj-95748	89	24	area	area	NOUN
esrj-95748	89	25	and	and	CCONJ
esrj-95748	89	26	slope	slope	NOUN
esrj-95748	89	27	.	.	PUNCT
esrj-95748	90	1	the	the	DET
esrj-95748	90	2	soil	soil	NOUN
esrj-95748	90	3	moisture	moisture	NOUN
esrj-95748	90	4	conditions	condition	NOUN
esrj-95748	90	5	within	within	ADP
esrj-95748	90	6	different	different	ADJ
esrj-95748	90	7	slope	slope	NOUN
esrj-95748	90	8	positions	position	NOUN
esrj-95748	90	9	can	can	AUX
esrj-95748	90	10	be	be	AUX
esrj-95748	90	11	evaluated	evaluate	VERB
esrj-95748	90	12	by	by	ADP
esrj-95748	90	13	topographic	topographic	PROPN
esrj-95748	90	14	wetness	wetness	PROPN
esrj-95748	90	15	index	index	NOUN
esrj-95748	90	16	(	(	PUNCT
esrj-95748	90	17	eq	eq	NOUN
esrj-95748	90	18	.	.	NOUN
esrj-95748	90	19	2	2	NUM
esrj-95748	90	20	)	)	PUNCT
esrj-95748	90	21	.	.	PUNCT
esrj-95748	91	1	change	change	NOUN
esrj-95748	91	2	in	in	ADP
esrj-95748	91	3	this	this	DET
esrj-95748	91	4	index	index	NOUN
esrj-95748	91	5	affects	affect	VERB
esrj-95748	91	6	the	the	DET
esrj-95748	91	7	erosive	erosive	ADJ
esrj-95748	91	8	power	power	NOUN
esrj-95748	91	9	of	of	ADP
esrj-95748	91	10	overland	overland	PROPN
esrj-95748	91	11	flow	flow	NOUN
esrj-95748	91	12	.	.	PUNCT
esrj-95748	92	1	the	the	DET
esrj-95748	92	2	convexity	convexity	NOUN
esrj-95748	92	3	and	and	CCONJ
esrj-95748	92	4	concavity	concavity	NOUN
esrj-95748	92	5	of	of	ADP
esrj-95748	92	6	a	a	DET
esrj-95748	92	7	watershed	watershed	NOUN
esrj-95748	92	8	are	be	AUX
esrj-95748	92	9	determined	determine	VERB
esrj-95748	92	10	by	by	ADP
esrj-95748	92	11	plan	plan	NOUN
esrj-95748	92	12	curvature	curvature	NOUN
esrj-95748	92	13	(	(	PUNCT
esrj-95748	92	14	i.e.	i.e.	X
esrj-95748	92	15	different	different	ADJ
esrj-95748	92	16	watershed	watershe	VERB
esrj-95748	92	17	positions	position	NOUN
esrj-95748	92	18	)	)	PUNCT
esrj-95748	92	19	,	,	PUNCT
esrj-95748	92	20	which	which	PRON
esrj-95748	92	21	influences	influence	VERB
esrj-95748	92	22	gullying	gullye	VERB
esrj-95748	92	23	.	.	PUNCT
esrj-95748	93	1	all	all	DET
esrj-95748	93	2	the	the	DET
esrj-95748	93	3	terrain	terrain	NOUN
esrj-95748	93	4	variables	variable	NOUN
esrj-95748	93	5	were	be	AUX
esrj-95748	93	6	extracted	extract	VERB
esrj-95748	93	7	from	from	ADP
esrj-95748	93	8	the	the	DET
esrj-95748	93	9	20	20	NUM
esrj-95748	93	10	m	m	PROPN
esrj-95748	93	11	aster	aster	NOUN
esrj-95748	93	12	dem	dem	PROPN
esrj-95748	93	13	.	.	PUNCT
esrj-95748	94	1	spi	spi	PROPN
esrj-95748	94	2	and	and	CCONJ
esrj-95748	94	3	twi	twi	PROPN
esrj-95748	94	4	were	be	AUX
esrj-95748	94	5	calculated	calculate	VERB
esrj-95748	94	6	as	as	ADP
esrj-95748	94	7	(	(	PUNCT
esrj-95748	94	8	bell	bell	NOUN
esrj-95748	94	9	et	et	PROPN
esrj-95748	94	10	al	al	PROPN
esrj-95748	94	11	.	.	PROPN
esrj-95748	94	12	,	,	PUNCT
esrj-95748	94	13	1995	1995	NUM
esrj-95748	94	14	;	;	PUNCT
esrj-95748	94	15	moore	moore	PROPN
esrj-95748	94	16	et	et	PROPN
esrj-95748	94	17	al	al	PROPN
esrj-95748	94	18	.	.	PROPN
esrj-95748	94	19	,	,	PUNCT
esrj-95748	94	20	1993	1993	NUM
esrj-95748	94	21	):	):	PUNCT
esrj-95748	94	22	(	(	PUNCT
esrj-95748	94	23	1	1	X
esrj-95748	94	24	)	)	PUNCT
esrj-95748	94	25	(	(	PUNCT
esrj-95748	94	26	2	2	X
esrj-95748	94	27	)	)	PUNCT
esrj-95748	94	28	where	where	SCONJ
esrj-95748	94	29	ac	ac	PROPN
esrj-95748	94	30	is	be	AUX
esrj-95748	94	31	the	the	DET
esrj-95748	94	32	upslope	upslope	NOUN
esrj-95748	94	33	area	area	NOUN
esrj-95748	94	34	that	that	PRON
esrj-95748	94	35	drains	drain	VERB
esrj-95748	94	36	through	through	ADP
esrj-95748	94	37	a	a	DET
esrj-95748	94	38	certain	certain	ADJ
esrj-95748	94	39	point	point	NOUN
esrj-95748	94	40	per	per	ADP
esrj-95748	94	41	unit	unit	NOUN
esrj-95748	94	42	contour	contour	NOUN
esrj-95748	94	43	length	length	NOUN
esrj-95748	94	44	,	,	PUNCT
esrj-95748	94	45	which	which	PRON
esrj-95748	94	46	is	be	AUX
esrj-95748	94	47	equal	equal	ADJ
esrj-95748	94	48	to	to	ADP
esrj-95748	94	49	a	a	DET
esrj-95748	94	50	certain	certain	ADJ
esrj-95748	94	51	grid	grid	NOUN
esrj-95748	94	52	cell	cell	NOUN
esrj-95748	94	53	width	width	NOUN
esrj-95748	94	54	(	(	PUNCT
esrj-95748	94	55	raduła	raduła	PROPN
esrj-95748	94	56	et	et	PROPN
esrj-95748	94	57	al	al	PROPN
esrj-95748	94	58	.	.	PROPN
esrj-95748	94	59	,2018	,2018	PROPN
esrj-95748	94	60	)	)	PUNCT
esrj-95748	94	61	.	.	PUNCT
esrj-95748	95	1	the	the	DET
esrj-95748	95	2	occurrence	occurrence	NOUN
esrj-95748	95	3	of	of	ADP
esrj-95748	95	4	gully	gully	ADJ
esrj-95748	95	5	erosion	erosion	NOUN
esrj-95748	95	6	is	be	AUX
esrj-95748	95	7	most	most	ADV
esrj-95748	95	8	probable	probable	ADJ
esrj-95748	95	9	along	along	ADP
esrj-95748	95	10	the	the	DET
esrj-95748	95	11	fault	fault	NOUN
esrj-95748	95	12	,	,	PUNCT
esrj-95748	95	13	river	river	NOUN
esrj-95748	95	14	,	,	PUNCT
esrj-95748	95	15	and	and	CCONJ
esrj-95748	95	16	road	road	NOUN
esrj-95748	95	17	due	due	ADJ
esrj-95748	95	18	to	to	ADP
esrj-95748	95	19	erosion	erosion	NOUN
esrj-95748	95	20	and	and	CCONJ
esrj-95748	95	21	ground	ground	NOUN
esrj-95748	95	22	instability	instability	NOUN
esrj-95748	95	23	.	.	PUNCT
esrj-95748	96	1	therefore	therefore	ADV
esrj-95748	96	2	,	,	PUNCT
esrj-95748	96	3	the	the	DET
esrj-95748	96	4	maps	map	NOUN
esrj-95748	96	5	of	of	ADP
esrj-95748	96	6	drainage	drainage	NOUN
esrj-95748	96	7	density	density	NOUN
esrj-95748	96	8	,	,	PUNCT
esrj-95748	96	9	distance	distance	NOUN
esrj-95748	96	10	from	from	ADP
esrj-95748	96	11	rivers	river	NOUN
esrj-95748	96	12	,	,	PUNCT
esrj-95748	96	13	faults	fault	NOUN
esrj-95748	96	14	,	,	PUNCT
esrj-95748	96	15	and	and	CCONJ
esrj-95748	96	16	roads	road	NOUN
esrj-95748	96	17	were	be	AUX
esrj-95748	96	18	prepared	prepare	VERB
esrj-95748	96	19	using	use	VERB
esrj-95748	96	20	a	a	DET
esrj-95748	96	21	1:25,000	1:25,000	NUM
esrj-95748	96	22	-	-	PUNCT
esrj-95748	96	23	scale	scale	NOUN
esrj-95748	96	24	topographical	topographical	ADJ
esrj-95748	96	25	map	map	NOUN
esrj-95748	96	26	.	.	PUNCT
esrj-95748	97	1	the	the	DET
esrj-95748	97	2	map	map	NOUN
esrj-95748	97	3	of	of	ADP
esrj-95748	97	4	drainage	drainage	NOUN
esrj-95748	97	5	density	density	NOUN
esrj-95748	97	6	was	be	AUX
esrj-95748	97	7	generated	generate	VERB
esrj-95748	97	8	in	in	ADP
esrj-95748	97	9	arcgis	arcgis	PROPN
esrj-95748	97	10	(	(	PUNCT
esrj-95748	97	11	line	line	NOUN
esrj-95748	97	12	density	density	NOUN
esrj-95748	97	13	tools	tool	NOUN
esrj-95748	97	14	)	)	PUNCT
esrj-95748	97	15	.	.	PUNCT
esrj-95748	98	1	the	the	DET
esrj-95748	98	2	maps	map	NOUN
esrj-95748	98	3	of	of	ADP
esrj-95748	98	4	distance	distance	NOUN
esrj-95748	98	5	from	from	ADP
esrj-95748	98	6	fault	fault	NOUN
esrj-95748	98	7	,	,	PUNCT
esrj-95748	98	8	river	river	NOUN
esrj-95748	98	9	,	,	PUNCT
esrj-95748	98	10	and	and	CCONJ
esrj-95748	98	11	road	road	NOUN
esrj-95748	98	12	were	be	AUX
esrj-95748	98	13	generated	generate	VERB
esrj-95748	98	14	using	use	VERB
esrj-95748	98	15	the	the	DET
esrj-95748	98	16	euclidean	euclidean	ADJ
esrj-95748	98	17	distance	distance	NOUN
esrj-95748	98	18	function	function	NOUN
esrj-95748	98	19	in	in	ADP
esrj-95748	98	20	arcgis	arcgis	PROPN
esrj-95748	98	21	.	.	PUNCT
esrj-95748	99	1	the	the	DET
esrj-95748	99	2	lithology	lithology	NOUN
esrj-95748	99	3	map	map	NOUN
esrj-95748	99	4	was	be	AUX
esrj-95748	99	5	produced	produce	VERB
esrj-95748	99	6	based	base	VERB
esrj-95748	99	7	on	on	ADP
esrj-95748	99	8	the	the	DET
esrj-95748	99	9	geological	geological	ADJ
esrj-95748	99	10	maps	map	NOUN
esrj-95748	99	11	on	on	ADP
esrj-95748	99	12	a	a	DET
esrj-95748	99	13	scale	scale	NOUN
esrj-95748	99	14	of	of	ADP
esrj-95748	99	15	1:50,000	1:50,000	NUM
esrj-95748	99	16	.	.	PUNCT
esrj-95748	100	1	the	the	DET
esrj-95748	100	2	land	land	NOUN
esrj-95748	100	3	use	use	NOUN
esrj-95748	100	4	/	/	SYM
esrj-95748	100	5	cover	cover	NOUN
esrj-95748	100	6	was	be	AUX
esrj-95748	100	7	mapped	map	VERB
esrj-95748	100	8	by	by	ADP
esrj-95748	100	9	using	use	VERB
esrj-95748	100	10	landsat	landsat	PROPN
esrj-95748	100	11	8	8	NUM
esrj-95748	100	12	satellite	satellite	NOUN
esrj-95748	100	13	and	and	CCONJ
esrj-95748	100	14	google	google	PROPN
esrj-95748	100	15	earth	earth	NOUN
esrj-95748	100	16	images	image	NOUN
esrj-95748	100	17	.	.	PUNCT
esrj-95748	101	1	figure	figure	VERB
esrj-95748	101	2	3	3	NUM
esrj-95748	101	3	and	and	CCONJ
esrj-95748	101	4	table	table	NOUN
esrj-95748	101	5	2	2	NUM
esrj-95748	101	6	show	show	VERB
esrj-95748	101	7	the	the	DET
esrj-95748	101	8	classification	classification	NOUN
esrj-95748	101	9	of	of	ADP
esrj-95748	101	10	all	all	DET
esrj-95748	101	11	the	the	DET
esrj-95748	101	12	conditioning	conditioning	NOUN
esrj-95748	101	13	factors	factor	NOUN
esrj-95748	101	14	.	.	PUNCT
esrj-95748	102	1	analysis	analysis	NOUN
esrj-95748	102	2	of	of	ADP
esrj-95748	102	3	multi	multi	NOUN
esrj-95748	102	4	-	-	NOUN
esrj-95748	102	5	collinearity	collinearity	NOUN
esrj-95748	102	6	among	among	ADP
esrj-95748	102	7	independent	independent	ADJ
esrj-95748	102	8	variables	variable	NOUN
esrj-95748	102	9	the	the	DET
esrj-95748	102	10	multi	multi	ADJ
esrj-95748	102	11	-	-	ADJ
esrj-95748	102	12	collinearity	collinearity	ADJ
esrj-95748	102	13	analysis	analysis	NOUN
esrj-95748	102	14	represents	represent	VERB
esrj-95748	102	15	the	the	DET
esrj-95748	102	16	linear	linear	ADJ
esrj-95748	102	17	correlation	correlation	NOUN
esrj-95748	102	18	among	among	ADP
esrj-95748	102	19	the	the	DET
esrj-95748	102	20	measured	measure	VERB
esrj-95748	102	21	independent	independent	ADJ
esrj-95748	102	22	variables	variable	NOUN
esrj-95748	102	23	.	.	PUNCT
esrj-95748	103	1	a	a	DET
esrj-95748	103	2	very	very	ADV
esrj-95748	103	3	high	high	ADJ
esrj-95748	103	4	correlation	correlation	NOUN
esrj-95748	103	5	among	among	ADP
esrj-95748	103	6	factors	factor	NOUN
esrj-95748	103	7	encourages	encourage	VERB
esrj-95748	103	8	multi	multi	ADJ
esrj-95748	103	9	-	-	NOUN
esrj-95748	103	10	collinearity	collinearity	NOUN
esrj-95748	103	11	.	.	PUNCT
esrj-95748	104	1	to	to	PART
esrj-95748	104	2	determine	determine	VERB
esrj-95748	104	3	the	the	DET
esrj-95748	104	4	multi	multi	NOUN
esrj-95748	104	5	-	-	NOUN
esrj-95748	104	6	collinearity	collinearity	NOUN
esrj-95748	104	7	of	of	ADP
esrj-95748	104	8	the	the	DET
esrj-95748	104	9	factors	factor	NOUN
esrj-95748	104	10	,	,	PUNCT
esrj-95748	104	11	the	the	DET
esrj-95748	104	12	variance	variance	NOUN
esrj-95748	104	13	inflation	inflation	NOUN
esrj-95748	104	14	factor	factor	NOUN
esrj-95748	104	15	(	(	PUNCT
esrj-95748	104	16	vif	vif	NOUN
esrj-95748	104	17	)	)	PUNCT
esrj-95748	104	18	and	and	CCONJ
esrj-95748	104	19	tolerance	tolerance	NOUN
esrj-95748	104	20	(	(	PUNCT
esrj-95748	104	21	tol	tol	NOUN
esrj-95748	104	22	)	)	PUNCT
esrj-95748	104	23	were	be	AUX
esrj-95748	104	24	employed	employ	VERB
esrj-95748	104	25	.	.	PUNCT
esrj-95748	105	1	the	the	DET
esrj-95748	105	2	vif	vif	NOUN
esrj-95748	105	3	greater	great	ADJ
esrj-95748	105	4	than	than	ADP
esrj-95748	105	5	5	5	NUM
esrj-95748	105	6	and	and	CCONJ
esrj-95748	105	7	tol	tol	VERB
esrj-95748	105	8	less	less	ADJ
esrj-95748	105	9	than	than	ADP
esrj-95748	105	10	0.2	0.2	NUM
esrj-95748	105	11	represent	represent	VERB
esrj-95748	105	12	a	a	DET
esrj-95748	105	13	high	high	ADJ
esrj-95748	105	14	correlation	correlation	NOUN
esrj-95748	105	15	between	between	ADP
esrj-95748	105	16	the	the	DET
esrj-95748	105	17	variables	variable	NOUN
esrj-95748	105	18	.	.	PUNCT
esrj-95748	106	1	since	since	SCONJ
esrj-95748	106	2	these	these	DET
esrj-95748	106	3	high	high	ADJ
esrj-95748	106	4	correlations	correlation	NOUN
esrj-95748	106	5	reduce	reduce	VERB
esrj-95748	106	6	the	the	DET
esrj-95748	106	7	accuracy	accuracy	NOUN
esrj-95748	106	8	of	of	ADP
esrj-95748	106	9	the	the	DET
esrj-95748	106	10	results	result	NOUN
esrj-95748	106	11	,	,	PUNCT
esrj-95748	106	12	factors	factor	NOUN
esrj-95748	106	13	with	with	ADP
esrj-95748	106	14	this	this	DET
esrj-95748	106	15	characteristic	characteristic	NOUN
esrj-95748	106	16	should	should	AUX
esrj-95748	106	17	be	be	AUX
esrj-95748	106	18	removed	remove	VERB
esrj-95748	106	19	from	from	ADP
esrj-95748	106	20	the	the	DET
esrj-95748	106	21	final	final	ADJ
esrj-95748	106	22	analysis	analysis	NOUN
esrj-95748	106	23	.	.	PUNCT
esrj-95748	107	1	the	the	DET
esrj-95748	107	2	following	follow	VERB
esrj-95748	107	3	equations	equation	NOUN
esrj-95748	107	4	represent	represent	VERB
esrj-95748	107	5	the	the	DET
esrj-95748	107	6	calculation	calculation	NOUN
esrj-95748	107	7	of	of	ADP
esrj-95748	107	8	vif	vif	NOUN
esrj-95748	107	9	and	and	CCONJ
esrj-95748	107	10	tol	tol	NOUN
esrj-95748	107	11	.	.	PUNCT
esrj-95748	108	1	(	(	PUNCT
esrj-95748	108	2	3	3	X
esrj-95748	108	3	)	)	PUNCT
esrj-95748	108	4	(	(	PUNCT
esrj-95748	108	5	4	4	X
esrj-95748	108	6	)	)	PUNCT
esrj-95748	108	7	where	where	SCONJ
esrj-95748	108	8	represents	represent	VERB
esrj-95748	108	9	the	the	DET
esrj-95748	108	10	regression	regression	NOUN
esrj-95748	108	11	value	value	NOUN
esrj-95748	108	12	of	of	ADP
esrj-95748	108	13	j	j	PROPN
esrj-95748	108	14	on	on	ADP
esrj-95748	108	15	other	other	ADJ
esrj-95748	108	16	variables	variable	NOUN
esrj-95748	108	17	.	.	PUNCT
esrj-95748	109	1	assessment	assessment	NOUN
esrj-95748	109	2	of	of	ADP
esrj-95748	109	3	correlation	correlation	NOUN
esrj-95748	109	4	between	between	ADP
esrj-95748	109	5	independent	independent	ADJ
esrj-95748	109	6	variables	variable	NOUN
esrj-95748	109	7	and	and	CCONJ
esrj-95748	109	8	gullied	gully	VERB
esrj-95748	109	9	locations	location	NOUN
esrj-95748	109	10	the	the	DET
esrj-95748	109	11	ebf	ebf	ADJ
esrj-95748	109	12	algorithm	algorithm	NOUN
esrj-95748	109	13	was	be	AUX
esrj-95748	109	14	employed	employ	VERB
esrj-95748	109	15	to	to	PART
esrj-95748	109	16	assess	assess	VERB
esrj-95748	109	17	the	the	DET
esrj-95748	109	18	relationship	relationship	NOUN
esrj-95748	109	19	between	between	ADP
esrj-95748	109	20	the	the	DET
esrj-95748	109	21	independent	independent	ADJ
esrj-95748	109	22	variables	variable	NOUN
esrj-95748	109	23	and	and	CCONJ
esrj-95748	109	24	gullied	gullied	ADJ
esrj-95748	109	25	locations	location	NOUN
esrj-95748	109	26	.	.	PUNCT
esrj-95748	110	1	this	this	DET
esrj-95748	110	2	algorithm	algorithm	NOUN
esrj-95748	110	3	is	be	AUX
esrj-95748	110	4	based	base	VERB
esrj-95748	110	5	on	on	ADP
esrj-95748	110	6	the	the	DET
esrj-95748	110	7	dempster	dempster	PROPN
esrj-95748	110	8	-	-	PUNCT
esrj-95748	110	9	shafer	shafer	PROPN
esrj-95748	110	10	theory	theory	NOUN
esrj-95748	110	11	(	(	PUNCT
esrj-95748	110	12	dempster	dempster	PROPN
esrj-95748	110	13	,	,	PUNCT
esrj-95748	110	14	1967	1967	NUM
esrj-95748	110	15	;	;	PUNCT
esrj-95748	110	16	shafer	shafer	NOUN
esrj-95748	110	17	,	,	PUNCT
esrj-95748	110	18	1976	1976	NUM
esrj-95748	110	19	)	)	PUNCT
esrj-95748	110	20	,	,	PUNCT
esrj-95748	110	21	which	which	PRON
esrj-95748	110	22	evaluates	evaluate	VERB
esrj-95748	110	23	the	the	DET
esrj-95748	110	24	uncertainty	uncertainty	NOUN
esrj-95748	110	25	sources	source	NOUN
esrj-95748	110	26	affecting	affect	VERB
esrj-95748	110	27	the	the	DET
esrj-95748	110	28	occurrence	occurrence	NOUN
esrj-95748	110	29	probability	probability	NOUN
esrj-95748	110	30	.	.	PUNCT
esrj-95748	111	1	this	this	DET
esrj-95748	111	2	statistical	statistical	ADJ
esrj-95748	111	3	model	model	NOUN
esrj-95748	111	4	includes	include	VERB
esrj-95748	111	5	the	the	DET
esrj-95748	111	6	degree	degree	NOUN
esrj-95748	111	7	of	of	ADP
esrj-95748	111	8	disbelief	disbelief	NOUN
esrj-95748	111	9	(	(	PUNCT
esrj-95748	111	10	dis	dis	PROPN
esrj-95748	111	11	)	)	PUNCT
esrj-95748	111	12	,	,	PUNCT
esrj-95748	111	13	the	the	DET
esrj-95748	111	14	degree	degree	NOUN
esrj-95748	111	15	of	of	ADP
esrj-95748	111	16	belief	belief	NOUN
esrj-95748	111	17	(	(	PUNCT
esrj-95748	111	18	bel	bel	NOUN
esrj-95748	111	19	)	)	PUNCT
esrj-95748	111	20	,	,	PUNCT
esrj-95748	111	21	the	the	DET
esrj-95748	111	22	degree	degree	NOUN
esrj-95748	111	23	of	of	ADP
esrj-95748	111	24	plausibility	plausibility	NOUN
esrj-95748	111	25	(	(	PUNCT
esrj-95748	111	26	pls	pls	INTJ
esrj-95748	111	27	)	)	PUNCT
esrj-95748	111	28	,	,	PUNCT
esrj-95748	111	29	and	and	CCONJ
esrj-95748	111	30	the	the	DET
esrj-95748	111	31	degree	degree	NOUN
esrj-95748	111	32	of	of	ADP
esrj-95748	111	33	uncertainty	uncertainty	NOUN
esrj-95748	111	34	(	(	PUNCT
esrj-95748	111	35	unc	unc	PROPN
esrj-95748	111	36	)	)	PUNCT
esrj-95748	111	37	(	(	PUNCT
esrj-95748	111	38	althuwaynee	althuwaynee	NOUN
esrj-95748	111	39	et	et	PROPN
esrj-95748	111	40	al	al	PROPN
esrj-95748	111	41	.	.	PROPN
esrj-95748	111	42	,	,	PUNCT
esrj-95748	111	43	2014	2014	NUM
esrj-95748	111	44	)	)	PUNCT
esrj-95748	111	45	.	.	PUNCT
esrj-95748	112	1	the	the	DET
esrj-95748	112	2	pls	pls	NOUN
esrj-95748	112	3	and	and	CCONJ
esrj-95748	112	4	bel	bel	NOUN
esrj-95748	112	5	were	be	AUX
esrj-95748	112	6	defined	define	VERB
esrj-95748	112	7	as	as	ADP
esrj-95748	112	8	the	the	DET
esrj-95748	112	9	lower	low	ADJ
esrj-95748	112	10	and	and	CCONJ
esrj-95748	112	11	upper	upper	ADJ
esrj-95748	112	12	limits	limit	NOUN
esrj-95748	112	13	of	of	ADP
esrj-95748	112	14	probabilities	probability	NOUN
esrj-95748	112	15	.	.	PUNCT
esrj-95748	113	1	the	the	DET
esrj-95748	113	2	uncertainty	uncertainty	NOUN
esrj-95748	113	3	degree	degree	NOUN
esrj-95748	113	4	(	(	PUNCT
esrj-95748	113	5	unc	unc	PROPN
esrj-95748	113	6	)	)	PUNCT
esrj-95748	113	7	determines	determine	NOUN
esrj-95748	113	8	based	base	VERB
esrj-95748	113	9	on	on	ADP
esrj-95748	113	10	bel	bel	NOUN
esrj-95748	113	11	pls	pls	PROPN
esrj-95748	113	12	.	.	PUNCT
esrj-95748	114	1	dis	dis	PROPN
esrj-95748	114	2	https://www.sciencedirect.com/topics/earth-and-planetary-sciences/support-vector-machine	https://www.sciencedirect.com/topics/earth-and-planetary-sciences/support-vector-machine	VERB
esrj-95748	114	3	426	426	NUM
esrj-95748	114	4	mahdieh	mahdieh	PROPN
esrj-95748	114	5	valipour	valipour	NOUN
esrj-95748	114	6	,	,	PUNCT
esrj-95748	114	7	neda	neda	PROPN
esrj-95748	114	8	mohseni	mohseni	NOUN
esrj-95748	114	9	,	,	PUNCT
esrj-95748	114	10	seyed	seyed	PROPN
esrj-95748	114	11	reza	reza	PROPN
esrj-95748	114	12	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	114	13	illustrates	illustrate	VERB
esrj-95748	114	14	the	the	DET
esrj-95748	114	15	degree	degree	NOUN
esrj-95748	114	16	of	of	ADP
esrj-95748	114	17	disbelief	disbelief	NOUN
esrj-95748	114	18	based	base	VERB
esrj-95748	114	19	on	on	ADP
esrj-95748	114	20	1	1	NUM
esrj-95748	114	21	–	–	PUNCT
esrj-95748	114	22	unc	unc	NOUN
esrj-95748	114	23	–	–	PUNCT
esrj-95748	114	24	bel	bel	NOUN
esrj-95748	114	25	or	or	CCONJ
esrj-95748	114	26	1pls	1pls	NOUN
esrj-95748	114	27	.	.	PUNCT
esrj-95748	115	1	the	the	DET
esrj-95748	115	2	sum	sum	NOUN
esrj-95748	115	3	of	of	ADP
esrj-95748	115	4	unc	unc	PROPN
esrj-95748	115	5	,	,	PUNCT
esrj-95748	115	6	dis	dis	PROPN
esrj-95748	115	7	,	,	PUNCT
esrj-95748	115	8	and	and	CCONJ
esrj-95748	115	9	bel	bel	NOUN
esrj-95748	115	10	is	be	AUX
esrj-95748	115	11	calculated	calculate	VERB
esrj-95748	115	12	as	as	ADP
esrj-95748	115	13	1	1	NUM
esrj-95748	115	14	(	(	PUNCT
esrj-95748	115	15	lee	lee	PROPN
esrj-95748	115	16	et	et	PROPN
esrj-95748	115	17	al	al	PROPN
esrj-95748	115	18	.	.	PROPN
esrj-95748	115	19	,	,	PUNCT
esrj-95748	115	20	2012	2012	NUM
esrj-95748	115	21	;	;	PUNCT
esrj-95748	115	22	carranza	carranza	PROPN
esrj-95748	115	23	et	et	PROPN
esrj-95748	115	24	al	al	PROPN
esrj-95748	115	25	.	.	PROPN
esrj-95748	115	26	,	,	PUNCT
esrj-95748	115	27	2005	2005	NUM
esrj-95748	115	28	)	)	PUNCT
esrj-95748	115	29	.	.	PUNCT
esrj-95748	116	1	further	further	ADJ
esrj-95748	116	2	information	information	NOUN
esrj-95748	116	3	on	on	ADP
esrj-95748	116	4	this	this	DET
esrj-95748	116	5	algorithm	algorithm	NOUN
esrj-95748	116	6	can	can	AUX
esrj-95748	116	7	be	be	AUX
esrj-95748	116	8	seen	see	VERB
esrj-95748	116	9	in	in	ADP
esrj-95748	116	10	the	the	DET
esrj-95748	116	11	research	research	NOUN
esrj-95748	116	12	of	of	ADP
esrj-95748	116	13	park	park	NOUN
esrj-95748	116	14	(	(	PUNCT
esrj-95748	116	15	2011	2011	NUM
esrj-95748	116	16	)	)	PUNCT
esrj-95748	116	17	.	.	PUNCT
esrj-95748	117	1	evaluation	evaluation	NOUN
esrj-95748	117	2	of	of	ADP
esrj-95748	117	3	the	the	DET
esrj-95748	117	4	importance	importance	NOUN
esrj-95748	117	5	of	of	ADP
esrj-95748	117	6	independent	independent	ADJ
esrj-95748	117	7	variables	variable	NOUN
esrj-95748	117	8	the	the	DET
esrj-95748	117	9	selection	selection	NOUN
esrj-95748	117	10	of	of	ADP
esrj-95748	117	11	variables	variable	NOUN
esrj-95748	117	12	that	that	PRON
esrj-95748	117	13	have	have	VERB
esrj-95748	117	14	the	the	DET
esrj-95748	117	15	most	most	ADJ
esrj-95748	117	16	importance	importance	NOUN
esrj-95748	117	17	in	in	ADP
esrj-95748	117	18	gully	gully	ADJ
esrj-95748	117	19	erosion	erosion	NOUN
esrj-95748	117	20	is	be	AUX
esrj-95748	117	21	a	a	DET
esrj-95748	117	22	crucial	crucial	ADJ
esrj-95748	117	23	step	step	NOUN
esrj-95748	117	24	in	in	ADP
esrj-95748	117	25	the	the	DET
esrj-95748	117	26	modeling	modeling	NOUN
esrj-95748	117	27	process	process	NOUN
esrj-95748	117	28	.	.	PUNCT
esrj-95748	118	1	the	the	DET
esrj-95748	118	2	importance	importance	NOUN
esrj-95748	118	3	of	of	ADP
esrj-95748	118	4	the	the	DET
esrj-95748	118	5	independent	independent	ADJ
esrj-95748	118	6	variables	variable	NOUN
esrj-95748	118	7	controlling	control	VERB
esrj-95748	118	8	gully	gully	ADJ
esrj-95748	118	9	erosion	erosion	NOUN
esrj-95748	118	10	was	be	AUX
esrj-95748	118	11	determined	determine	VERB
esrj-95748	118	12	by	by	ADP
esrj-95748	118	13	applying	apply	VERB
esrj-95748	118	14	the	the	DET
esrj-95748	118	15	brouta	brouta	ADJ
esrj-95748	118	16	algorithm	algorithm	NOUN
esrj-95748	118	17	.	.	PUNCT
esrj-95748	119	1	boruta	boruta	PROPN
esrj-95748	119	2	algorithm	algorithm	PROPN
esrj-95748	119	3	is	be	AUX
esrj-95748	119	4	a	a	DET
esrj-95748	119	5	variable	variable	ADJ
esrj-95748	119	6	selection	selection	NOUN
esrj-95748	119	7	algorithm	algorithm	NOUN
esrj-95748	119	8	.	.	PUNCT
esrj-95748	120	1	it	it	PRON
esrj-95748	120	2	is	be	AUX
esrj-95748	120	3	a	a	DET
esrj-95748	120	4	wrapper	wrapper	NOUN
esrj-95748	120	5	algorithm	algorithm	NOUN
esrj-95748	120	6	around	around	ADP
esrj-95748	120	7	random	random	ADJ
esrj-95748	120	8	forest	forest	NOUN
esrj-95748	120	9	(	(	PUNCT
esrj-95748	120	10	liaw	liaw	NOUN
esrj-95748	120	11	and	and	CCONJ
esrj-95748	120	12	wiener	wiener	NOUN
esrj-95748	120	13	,	,	PUNCT
esrj-95748	120	14	2002	2002	NUM
esrj-95748	120	15	)	)	PUNCT
esrj-95748	120	16	.	.	PUNCT
esrj-95748	121	1	when	when	SCONJ
esrj-95748	121	2	a	a	DET
esrj-95748	121	3	dataset	dataset	NOUN
esrj-95748	121	4	comprised	comprise	VERB
esrj-95748	121	5	of	of	ADP
esrj-95748	121	6	multiple	multiple	ADJ
esrj-95748	121	7	variables	variable	NOUN
esrj-95748	121	8	is	be	AUX
esrj-95748	121	9	given	give	VERB
esrj-95748	121	10	for	for	ADP
esrj-95748	121	11	modeling	modeling	NOUN
esrj-95748	121	12	,	,	PUNCT
esrj-95748	121	13	this	this	DET
esrj-95748	121	14	algorithm	algorithm	NOUN
esrj-95748	121	15	can	can	AUX
esrj-95748	121	16	determine	determine	VERB
esrj-95748	121	17	the	the	DET
esrj-95748	121	18	most	most	ADV
esrj-95748	121	19	important	important	ADJ
esrj-95748	121	20	conditioning	conditioning	NOUN
esrj-95748	121	21	variables	variable	NOUN
esrj-95748	121	22	.	.	PUNCT
esrj-95748	122	1	machine	machine	NOUN
esrj-95748	122	2	learning	learning	NOUN
esrj-95748	122	3	models	model	NOUN
esrj-95748	122	4	for	for	ADP
esrj-95748	122	5	predicting	predict	VERB
esrj-95748	122	6	gully	gully	NOUN
esrj-95748	122	7	erosion	erosion	NOUN
esrj-95748	122	8	the	the	DET
esrj-95748	122	9	support	support	NOUN
esrj-95748	122	10	vector	vector	NOUN
esrj-95748	122	11	machine	machine	NOUN
esrj-95748	122	12	model	model	NOUN
esrj-95748	122	13	was	be	AUX
esrj-95748	122	14	initially	initially	ADV
esrj-95748	122	15	presented	present	VERB
esrj-95748	122	16	as	as	ADP
esrj-95748	122	17	a	a	DET
esrj-95748	122	18	supervised	supervised	ADJ
esrj-95748	122	19	learning	learning	NOUN
esrj-95748	122	20	technique	technique	NOUN
esrj-95748	122	21	(	(	PUNCT
esrj-95748	122	22	binary	binary	NOUN
esrj-95748	122	23	classifier	classifier	NOUN
esrj-95748	122	24	)	)	PUNCT
esrj-95748	122	25	that	that	PRON
esrj-95748	122	26	can	can	AUX
esrj-95748	122	27	consider	consider	VERB
esrj-95748	122	28	linearly	linearly	ADV
esrj-95748	122	29	multi	multi	ADJ
esrj-95748	122	30	-	-	ADJ
esrj-95748	122	31	dimensional	dimensional	ADJ
esrj-95748	122	32	and	and	CCONJ
esrj-95748	122	33	non	non	ADJ
esrj-95748	122	34	-	-	ADJ
esrj-95748	122	35	separable	separable	ADJ
esrj-95748	122	36	datasets	dataset	NOUN
esrj-95748	122	37	(	(	PUNCT
esrj-95748	122	38	kalantar	kalantar	NOUN
esrj-95748	122	39	et	et	PROPN
esrj-95748	122	40	al	al	PROPN
esrj-95748	122	41	.	.	PROPN
esrj-95748	122	42	,	,	PUNCT
esrj-95748	122	43	2017	2017	NUM
esrj-95748	122	44	;	;	PUNCT
esrj-95748	122	45	kavzoglu	kavzoglu	PROPN
esrj-95748	122	46	et	et	PROPN
esrj-95748	122	47	al	al	PROPN
esrj-95748	122	48	.	.	PROPN
esrj-95748	122	49	,	,	PUNCT
esrj-95748	122	50	2013	2013	NUM
esrj-95748	122	51	)	)	PUNCT
esrj-95748	122	52	.	.	PUNCT
esrj-95748	123	1	this	this	DET
esrj-95748	123	2	model	model	NOUN
esrj-95748	123	3	generates	generate	VERB
esrj-95748	123	4	functions	function	NOUN
esrj-95748	123	5	from	from	ADP
esrj-95748	123	6	a	a	DET
esrj-95748	123	7	training	training	NOUN
esrj-95748	123	8	dataset	dataset	NOUN
esrj-95748	123	9	and	and	CCONJ
esrj-95748	123	10	can	can	AUX
esrj-95748	123	11	distinguish	distinguish	VERB
esrj-95748	123	12	classes	class	NOUN
esrj-95748	123	13	in	in	ADP
esrj-95748	123	14	high	high	ADJ
esrj-95748	123	15	-	-	PUNCT
esrj-95748	123	16	dimensional	dimensional	ADJ
esrj-95748	123	17	feature	feature	NOUN
esrj-95748	123	18	space	space	NOUN
esrj-95748	123	19	.	.	PUNCT
esrj-95748	124	1	in	in	ADP
esrj-95748	124	2	the	the	DET
esrj-95748	124	3	present	present	ADJ
esrj-95748	124	4	study	study	NOUN
esrj-95748	124	5	,	,	PUNCT
esrj-95748	124	6	the	the	DET
esrj-95748	124	7	factors	factor	NOUN
esrj-95748	124	8	controlling	control	VERB
esrj-95748	124	9	gully	gully	ADJ
esrj-95748	124	10	erosion	erosion	NOUN
esrj-95748	124	11	(	(	PUNCT
esrj-95748	124	12	as	as	ADP
esrj-95748	124	13	different	different	ADJ
esrj-95748	124	14	thematic	thematic	ADJ
esrj-95748	124	15	layers	layer	NOUN
esrj-95748	124	16	)	)	PUNCT
esrj-95748	124	17	are	be	AUX
esrj-95748	124	18	considered	consider	VERB
esrj-95748	124	19	as	as	ADP
esrj-95748	124	20	the	the	DET
esrj-95748	124	21	high	high	ADV
esrj-95748	124	22	-	-	PUNCT
esrj-95748	124	23	dimensional	dimensional	ADJ
esrj-95748	124	24	feature	feature	NOUN
esrj-95748	124	25	spaces	space	NOUN
esrj-95748	124	26	.	.	PUNCT
esrj-95748	125	1	then	then	ADV
esrj-95748	125	2	,	,	PUNCT
esrj-95748	125	3	the	the	DET
esrj-95748	125	4	optimal	optimal	ADJ
esrj-95748	125	5	hyper	hyper	ADJ
esrj-95748	125	6	-	-	ADJ
esrj-95748	125	7	plane	plane	NOUN
esrj-95748	125	8	maximizes	maximize	VERB
esrj-95748	125	9	the	the	DET
esrj-95748	125	10	margin	margin	NOUN
esrj-95748	125	11	to	to	PART
esrj-95748	125	12	split	split	VERB
esrj-95748	125	13	into	into	ADP
esrj-95748	125	14	two	two	NUM
esrj-95748	125	15	classes	class	NOUN
esrj-95748	125	16	,	,	PUNCT
esrj-95748	125	17	including	include	VERB
esrj-95748	125	18	nongullying	nongullye	VERB
esrj-95748	125	19	and	and	CCONJ
esrj-95748	125	20	gullying	gullying	NOUN
esrj-95748	125	21	.	.	PUNCT
esrj-95748	126	1	the	the	DET
esrj-95748	126	2	optimal	optimal	ADJ
esrj-95748	126	3	hyper	hyper	NOUN
esrj-95748	126	4	-	-	ADJ
esrj-95748	126	5	plane	plane	NOUN
esrj-95748	126	6	was	be	AUX
esrj-95748	126	7	computed	compute	VERB
esrj-95748	126	8	based	base	VERB
esrj-95748	126	9	on	on	ADP
esrj-95748	126	10	the	the	DET
esrj-95748	126	11	equations	equation	NOUN
esrj-95748	126	12	below	below	ADP
esrj-95748	126	13	.	.	PUNCT
esrj-95748	127	1	(	(	PUNCT
esrj-95748	127	2	5	5	NUM
esrj-95748	127	3	)	)	PUNCT
esrj-95748	127	4	(	(	PUNCT
esrj-95748	127	5	6	6	NUM
esrj-95748	127	6	)	)	PUNCT
esrj-95748	127	7	}	}	PUNCT
esrj-95748	127	8	figure	figure	NOUN
esrj-95748	127	9	3	3	NUM
esrj-95748	127	10	.	.	PUNCT
esrj-95748	127	11	independent	independent	ADJ
esrj-95748	127	12	variables	variable	NOUN
esrj-95748	127	13	selected	select	VERB
esrj-95748	127	14	for	for	ADP
esrj-95748	127	15	assessing	assess	VERB
esrj-95748	127	16	gully	gully	ADJ
esrj-95748	127	17	erosion	erosion	NOUN
esrj-95748	127	18	susceptibility	susceptibility	NOUN
esrj-95748	127	19	figure	figure	NOUN
esrj-95748	127	20	3	3	NUM
esrj-95748	127	21	.	.	PUNCT
esrj-95748	128	1	(	(	PUNCT
esrj-95748	128	2	continued	continue	VERB
esrj-95748	128	3	)	)	PUNCT
esrj-95748	128	4	where	where	SCONJ
esrj-95748	128	5	is	be	AUX
esrj-95748	128	6	the	the	DET
esrj-95748	128	7	penalty	penalty	NOUN
esrj-95748	128	8	factor	factor	NOUN
esrj-95748	128	9	;	;	PUNCT
esrj-95748	128	10	represents	represent	VERB
esrj-95748	128	11	lagrange	lagrange	NOUN
esrj-95748	128	12	multipliers	multiplier	NOUN
esrj-95748	128	13	.	.	PUNCT
esrj-95748	129	1	regarding	regard	VERB
esrj-95748	129	2	the	the	DET
esrj-95748	129	3	present	present	ADJ
esrj-95748	129	4	study	study	NOUN
esrj-95748	129	5	,	,	PUNCT
esrj-95748	129	6	as	as	ADP
esrj-95748	129	7	a	a	DET
esrj-95748	129	8	vector	vector	NOUN
esrj-95748	129	9	of	of	ADP
esrj-95748	129	10	input	input	NOUN
esrj-95748	129	11	space	space	NOUN
esrj-95748	129	12	includes	include	VERB
esrj-95748	129	13	factors	factor	NOUN
esrj-95748	129	14	controlling	control	VERB
esrj-95748	129	15	gully	gully	ADJ
esrj-95748	129	16	erosion	erosion	NOUN
esrj-95748	129	17	.	.	PUNCT
esrj-95748	130	1	the	the	DET
esrj-95748	130	2	non	non	ADJ
esrj-95748	130	3	-	-	ADJ
esrj-95748	130	4	gullied	gullied	ADJ
esrj-95748	130	5	and	and	CCONJ
esrj-95748	130	6	gullied	gully	VERB
esrj-95748	130	7	pixels	pixel	NOUN
esrj-95748	130	8	were	be	AUX
esrj-95748	130	9	determined	determine	VERB
esrj-95748	130	10	as	as	ADP
esrj-95748	130	11	+1	+1	PROPN
esrj-95748	130	12	and	and	CCONJ
esrj-95748	130	13	−1	−1	NOUN
esrj-95748	130	14	,	,	PUNCT
esrj-95748	130	15	respectively	respectively	ADV
esrj-95748	130	16	.	.	PUNCT
esrj-95748	131	1	this	this	DET
esrj-95748	131	2	model	model	NOUN
esrj-95748	131	3	decreases	decrease	VERB
esrj-95748	131	4	the	the	DET
esrj-95748	131	5	possibility	possibility	NOUN
esrj-95748	131	6	of	of	ADP
esrj-95748	131	7	over	over	ADV
esrj-95748	131	8	-	-	PUNCT
esrj-95748	131	9	fitting	fit	VERB
esrj-95748	131	10	error	error	NOUN
esrj-95748	131	11	and	and	CCONJ
esrj-95748	131	12	linearity	linearity	NOUN
esrj-95748	131	13	and	and	CCONJ
esrj-95748	131	14	,	,	PUNCT
esrj-95748	131	15	therefore	therefore	ADV
esrj-95748	131	16	,	,	PUNCT
esrj-95748	131	17	has	have	VERB
esrj-95748	131	18	high	high	ADJ
esrj-95748	131	19	efficiency	efficiency	NOUN
esrj-95748	131	20	to	to	PART
esrj-95748	131	21	process	process	VERB
esrj-95748	131	22	data	datum	NOUN
esrj-95748	131	23	with	with	ADP
esrj-95748	131	24	nonlinear	nonlinear	ADJ
esrj-95748	131	25	interactions	interaction	NOUN
esrj-95748	131	26	by	by	ADP
esrj-95748	131	27	the	the	DET
esrj-95748	131	28	kernel	kernel	PROPN
esrj-95748	131	29	function	function	NOUN
esrj-95748	131	30	(	(	PUNCT
esrj-95748	131	31	naghibi	naghibi	NOUN
esrj-95748	131	32	et	et	PROPN
esrj-95748	131	33	al	al	PROPN
esrj-95748	131	34	.	.	PROPN
esrj-95748	131	35	,	,	PUNCT
esrj-95748	131	36	2015	2015	NUM
esrj-95748	131	37	)	)	PUNCT
esrj-95748	131	38	.	.	PUNCT
esrj-95748	132	1	this	this	DET
esrj-95748	132	2	algorithm	algorithm	NOUN
esrj-95748	132	3	has	have	VERB
esrj-95748	132	4	several	several	ADJ
esrj-95748	132	5	kernel	kernel	NOUN
esrj-95748	132	6	types	type	NOUN
esrj-95748	132	7	to	to	PART
esrj-95748	132	8	measure	measure	VERB
esrj-95748	132	9	the	the	DET
esrj-95748	132	10	errors	error	NOUN
esrj-95748	132	11	that	that	PRON
esrj-95748	132	12	can	can	AUX
esrj-95748	132	13	significantly	significantly	ADV
esrj-95748	132	14	influence	influence	VERB
esrj-95748	132	15	the	the	DET
esrj-95748	132	16	prediction	prediction	NOUN
esrj-95748	132	17	performance	performance	NOUN
esrj-95748	132	18	of	of	ADP
esrj-95748	132	19	the	the	DET
esrj-95748	132	20	model	model	NOUN
esrj-95748	132	21	and	and	CCONJ
esrj-95748	132	22	the	the	DET
esrj-95748	132	23	result	result	NOUN
esrj-95748	132	24	accuracy	accuracy	NOUN
esrj-95748	132	25	.	.	PUNCT
esrj-95748	133	1	the	the	DET
esrj-95748	133	2	most	most	ADV
esrj-95748	133	3	important	important	ADJ
esrj-95748	133	4	kernel	kernel	NOUN
esrj-95748	133	5	functions	function	NOUN
esrj-95748	133	6	of	of	ADP
esrj-95748	133	7	the	the	DET
esrj-95748	133	8	svm	svm	PROPN
esrj-95748	133	9	are	be	AUX
esrj-95748	133	10	:	:	PUNCT
esrj-95748	133	11	polynomial	polynomial	ADJ
esrj-95748	133	12	kernel	kernel	NOUN
esrj-95748	133	13	,	,	PUNCT
esrj-95748	133	14	sigmoid	sigmoid	NOUN
esrj-95748	133	15	kernel	kernel	NOUN
esrj-95748	133	16	,	,	PUNCT
esrj-95748	133	17	radial	radial	ADJ
esrj-95748	133	18	basis	basis	NOUN
esrj-95748	133	19	,	,	PUNCT
esrj-95748	133	20	and	and	CCONJ
esrj-95748	133	21	linear	linear	ADJ
esrj-95748	133	22	kernel	kernel	NOUN
esrj-95748	133	23	.	.	PUNCT
esrj-95748	134	1	this	this	DET
esrj-95748	134	2	study	study	NOUN
esrj-95748	134	3	compared	compare	VERB
esrj-95748	134	4	the	the	DET
esrj-95748	134	5	efficiency	efficiency	NOUN
esrj-95748	134	6	of	of	ADP
esrj-95748	134	7	the	the	DET
esrj-95748	134	8	radial	radial	ADJ
esrj-95748	134	9	basis	basis	NOUN
esrj-95748	134	10	function	function	NOUN
esrj-95748	134	11	(	(	PUNCT
esrj-95748	134	12	rbf	rbf	PROPN
esrj-95748	134	13	-	-	PUNCT
esrj-95748	134	14	svm	svm	PROPN
esrj-95748	134	15	)	)	PUNCT
esrj-95748	134	16	(	(	PUNCT
esrj-95748	134	17	eq	eq	NOUN
esrj-95748	134	18	.	.	NOUN
esrj-95748	134	19	7	7	NUM
esrj-95748	134	20	)	)	PUNCT
esrj-95748	134	21	and	and	CCONJ
esrj-95748	134	22	linear	linear	ADJ
esrj-95748	134	23	kernel	kernel	NOUN
esrj-95748	134	24	(	(	PUNCT
esrj-95748	134	25	ln	ln	ADJ
esrj-95748	134	26	-	-	PUNCT
esrj-95748	134	27	svm	svm	ADJ
esrj-95748	134	28	)	)	PUNCT
esrj-95748	134	29	(	(	PUNCT
esrj-95748	134	30	eq	eq	NOUN
esrj-95748	134	31	.	.	PROPN
esrj-95748	134	32	8)	8)	NUM
esrj-95748	134	33	for	for	ADP
esrj-95748	134	34	modeling	model	VERB
esrj-95748	134	35	the	the	DET
esrj-95748	134	36	gully	gully	ADJ
esrj-95748	134	37	erosion	erosion	NOUN
esrj-95748	134	38	susceptibility	susceptibility	NOUN
esrj-95748	134	39	.	.	PUNCT
esrj-95748	135	1	(	(	PUNCT
esrj-95748	135	2	7	7	NUM
esrj-95748	135	3	)	)	PUNCT
esrj-95748	135	4	(	(	PUNCT
esrj-95748	135	5	8)	8)	NUM
esrj-95748	135	6	where	where	SCONJ
esrj-95748	135	7	γ	γ	X
esrj-95748	135	8	,	,	PUNCT
esrj-95748	135	9	d	d	NOUN
esrj-95748	135	10	,	,	PUNCT
esrj-95748	135	11	and	and	CCONJ
esrj-95748	135	12	r	r	NOUN
esrj-95748	135	13	are	be	AUX
esrj-95748	135	14	defined	define	VERB
esrj-95748	135	15	as	as	ADP
esrj-95748	135	16	kernel	kernel	NOUN
esrj-95748	135	17	width	width	PROPN
esrj-95748	135	18	,	,	PUNCT
esrj-95748	135	19	polynomial	polynomial	ADJ
esrj-95748	135	20	degree	degree	NOUN
esrj-95748	135	21	,	,	PUNCT
esrj-95748	135	22	and	and	CCONJ
esrj-95748	135	23	parameter	parameter	NOUN
esrj-95748	135	24	of	of	ADP
esrj-95748	135	25	the	the	DET
esrj-95748	135	26	kernel	kernel	PROPN
esrj-95748	135	27	functions	function	NOUN
esrj-95748	135	28	,	,	PUNCT
esrj-95748	135	29	respectively	respectively	ADV
esrj-95748	135	30	(	(	PUNCT
esrj-95748	135	31	pradhan	pradhan	NOUN
esrj-95748	135	32	,	,	PUNCT
esrj-95748	135	33	2013	2013	NUM
esrj-95748	135	34	)	)	PUNCT
esrj-95748	135	35	.	.	PUNCT
esrj-95748	136	1	boosted	boost	VERB
esrj-95748	136	2	regression	regression	NOUN
esrj-95748	136	3	tree	tree	NOUN
esrj-95748	136	4	model	model	NOUN
esrj-95748	136	5	(	(	PUNCT
esrj-95748	136	6	eq	eq	NOUN
esrj-95748	136	7	.	.	NOUN
esrj-95748	136	8	9	9	NUM
esrj-95748	136	9	)	)	PUNCT
esrj-95748	136	10	adaptively	adaptively	ADV
esrj-95748	136	11	combined	combine	VERB
esrj-95748	136	12	machine	machine	NOUN
esrj-95748	136	13	learning	learn	VERB
esrj-95748	136	14	techniques	technique	NOUN
esrj-95748	136	15	to	to	PART
esrj-95748	136	16	produce	produce	VERB
esrj-95748	136	17	an	an	DET
esrj-95748	136	18	appropriate	appropriate	ADJ
esrj-95748	136	19	performance	performance	NOUN
esrj-95748	136	20	(	(	PUNCT
esrj-95748	136	21	elith	elith	ADP
esrj-95748	136	22	et	et	PROPN
esrj-95748	136	23	al	al	PROPN
esrj-95748	136	24	.	.	PROPN
esrj-95748	136	25	,	,	PUNCT
esrj-95748	136	26	2008	2008	NUM
esrj-95748	136	27	)	)	PUNCT
esrj-95748	136	28	.	.	PUNCT
esrj-95748	137	1	brt	brt	PROPN
esrj-95748	137	2	combines	combine	VERB
esrj-95748	137	3	different	different	ADJ
esrj-95748	137	4	regression	regression	NOUN
esrj-95748	137	5	algorithms	algorithm	NOUN
esrj-95748	137	6	and	and	CCONJ
esrj-95748	137	7	boosting	boost	VERB
esrj-95748	137	8	builds	build	NOUN
esrj-95748	137	9	to	to	PART
esrj-95748	137	10	reduce	reduce	VERB
esrj-95748	137	11	the	the	DET
esrj-95748	137	12	final	final	ADJ
esrj-95748	137	13	model	model	NOUN
esrj-95748	137	14	variance	variance	NOUN
esrj-95748	137	15	and	and	CCONJ
esrj-95748	137	16	enhance	enhance	VERB
esrj-95748	137	17	predictive	predictive	ADJ
esrj-95748	137	18	accuracy	accuracy	NOUN
esrj-95748	137	19	(	(	PUNCT
esrj-95748	137	20	aertsen	aertsen	PROPN
esrj-95748	137	21	et	et	PROPN
esrj-95748	137	22	al	al	PROPN
esrj-95748	137	23	.	.	PROPN
esrj-95748	137	24	,	,	PUNCT
esrj-95748	137	25	2010	2010	NUM
esrj-95748	137	26	)	)	PUNCT
esrj-95748	137	27	.	.	PUNCT
esrj-95748	138	1	this	this	DET
esrj-95748	138	2	model	model	NOUN
esrj-95748	138	3	,	,	PUNCT
esrj-95748	138	4	with	with	ADP
esrj-95748	138	5	large	large	ADJ
esrj-95748	138	6	volume	volume	NOUN
esrj-95748	138	7	of	of	ADP
esrj-95748	138	8	inputs	input	NOUN
esrj-95748	138	9	,	,	PUNCT
esrj-95748	138	10	stimulated	stimulate	VERB
esrj-95748	138	11	the	the	DET
esrj-95748	138	12	speed	speed	NOUN
esrj-95748	138	13	in	in	ADP
esrj-95748	138	14	data	data	NOUN
esrj-95748	138	15	processing	processing	NOUN
esrj-95748	138	16	and	and	CCONJ
esrj-95748	138	17	,	,	PUNCT
esrj-95748	138	18	subsequently	subsequently	ADV
esrj-95748	138	19	reduced	reduce	VERB
esrj-95748	138	20	sensitivity	sensitivity	NOUN
esrj-95748	138	21	to	to	ADP
esrj-95748	138	22	over	over	ADV
esrj-95748	138	23	-	-	PUNCT
esrj-95748	138	24	fitting	fitting	ADJ
esrj-95748	138	25	.	.	PUNCT
esrj-95748	139	1	(	(	PUNCT
esrj-95748	139	2	9	9	X
esrj-95748	139	3	)	)	PUNCT
esrj-95748	139	4	427factors	427factor	NOUN
esrj-95748	139	5	affecting	affect	VERB
esrj-95748	139	6	topographic	topographic	ADJ
esrj-95748	139	7	thresholds	threshold	NOUN
esrj-95748	139	8	in	in	ADP
esrj-95748	139	9	gully	gully	ADJ
esrj-95748	139	10	erosion	erosion	NOUN
esrj-95748	139	11	occurrence	occurrence	NOUN
esrj-95748	139	12	and	and	CCONJ
esrj-95748	139	13	its	its	PRON
esrj-95748	139	14	management	management	NOUN
esrj-95748	139	15	using	use	VERB
esrj-95748	139	16	predictive	predictive	ADJ
esrj-95748	139	17	machine	machine	NOUN
esrj-95748	139	18	learning	learning	NOUN
esrj-95748	139	19	models	model	NOUN
esrj-95748	139	20	where	where	SCONJ
esrj-95748	139	21	,	,	PUNCT
esrj-95748	139	22	m	m	PROPN
esrj-95748	139	23	,	,	PUNCT
esrj-95748	139	24	and	and	CCONJ
esrj-95748	139	25	are	be	AUX
esrj-95748	139	26	defined	define	VERB
esrj-95748	139	27	as	as	ADP
esrj-95748	139	28	a	a	DET
esrj-95748	139	29	classification	classification	NOUN
esrj-95748	139	30	function	function	NOUN
esrj-95748	139	31	with	with	ADP
esrj-95748	139	32	α	α	NOUN
esrj-95748	139	33	parameters	parameter	NOUN
esrj-95748	139	34	and	and	CCONJ
esrj-95748	139	35	x	x	NOUN
esrj-95748	139	36	variables	variable	NOUN
esrj-95748	139	37	,	,	PUNCT
esrj-95748	139	38	the	the	DET
esrj-95748	139	39	stage	stage	NOUN
esrj-95748	139	40	of	of	ADP
esrj-95748	139	41	the	the	DET
esrj-95748	139	42	model	model	NOUN
esrj-95748	139	43	,	,	PUNCT
esrj-95748	139	44	and	and	CCONJ
esrj-95748	139	45	the	the	DET
esrj-95748	139	46	weighting	weighting	NOUN
esrj-95748	139	47	factor	factor	NOUN
esrj-95748	139	48	m	m	PROPN
esrj-95748	139	49	,	,	PUNCT
esrj-95748	139	50	respectively	respectively	ADV
esrj-95748	139	51	.	.	PUNCT
esrj-95748	140	1	to	to	PART
esrj-95748	140	2	process	process	VERB
esrj-95748	140	3	the	the	DET
esrj-95748	140	4	models	model	NOUN
esrj-95748	140	5	,	,	PUNCT
esrj-95748	140	6	the	the	DET
esrj-95748	140	7	spatial	spatial	ADJ
esrj-95748	140	8	correlation	correlation	NOUN
esrj-95748	140	9	among	among	ADP
esrj-95748	140	10	conditioning	conditioning	NOUN
esrj-95748	140	11	variables	variable	NOUN
esrj-95748	140	12	and	and	CCONJ
esrj-95748	140	13	gullied	gully	VERB
esrj-95748	140	14	locations	location	NOUN
esrj-95748	140	15	was	be	AUX
esrj-95748	140	16	first	first	ADV
esrj-95748	140	17	calculated	calculate	VERB
esrj-95748	140	18	.	.	PUNCT
esrj-95748	141	1	in	in	ADP
esrj-95748	141	2	the	the	DET
esrj-95748	141	3	next	next	ADJ
esrj-95748	141	4	step	step	NOUN
esrj-95748	141	5	,	,	PUNCT
esrj-95748	141	6	the	the	DET
esrj-95748	141	7	data	datum	NOUN
esrj-95748	141	8	was	be	AUX
esrj-95748	141	9	transformed	transform	VERB
esrj-95748	141	10	into	into	ADP
esrj-95748	141	11	the	the	DET
esrj-95748	141	12	r	r	NOUN
esrj-95748	141	13	statistical	statistical	ADJ
esrj-95748	141	14	software	software	NOUN
esrj-95748	141	15	.	.	PUNCT
esrj-95748	142	1	finally	finally	ADV
esrj-95748	142	2	,	,	PUNCT
esrj-95748	142	3	the	the	DET
esrj-95748	142	4	maps	map	NOUN
esrj-95748	142	5	of	of	ADP
esrj-95748	142	6	gully	gully	NOUN
esrj-95748	142	7	erosion	erosion	NOUN
esrj-95748	142	8	susceptibility	susceptibility	NOUN
esrj-95748	142	9	were	be	AUX
esrj-95748	142	10	generated	generate	VERB
esrj-95748	142	11	in	in	ADP
esrj-95748	142	12	the	the	DET
esrj-95748	142	13	arcgis	arcgis	PROPN
esrj-95748	142	14	software	software	NOUN
esrj-95748	142	15	based	base	VERB
esrj-95748	142	16	on	on	ADP
esrj-95748	142	17	the	the	DET
esrj-95748	142	18	outputs	output	NOUN
esrj-95748	142	19	of	of	ADP
esrj-95748	142	20	the	the	DET
esrj-95748	142	21	models	model	NOUN
esrj-95748	142	22	.	.	PUNCT
esrj-95748	143	1	the	the	DET
esrj-95748	143	2	susceptibility	susceptibility	NOUN
esrj-95748	143	3	maps	map	NOUN
esrj-95748	143	4	were	be	AUX
esrj-95748	143	5	classified	classify	VERB
esrj-95748	143	6	into	into	ADP
esrj-95748	143	7	five	five	NUM
esrj-95748	143	8	categories	category	NOUN
esrj-95748	143	9	,	,	PUNCT
esrj-95748	143	10	including	include	VERB
esrj-95748	143	11	low	low	ADJ
esrj-95748	143	12	,	,	PUNCT
esrj-95748	143	13	very	very	ADV
esrj-95748	143	14	low	low	ADJ
esrj-95748	143	15	,	,	PUNCT
esrj-95748	143	16	moderate	moderate	ADJ
esrj-95748	143	17	,	,	PUNCT
esrj-95748	143	18	high	high	ADJ
esrj-95748	143	19	,	,	PUNCT
esrj-95748	143	20	and	and	CCONJ
esrj-95748	143	21	very	very	ADV
esrj-95748	143	22	high	high	ADJ
esrj-95748	143	23	susceptibility	susceptibility	NOUN
esrj-95748	143	24	,	,	PUNCT
esrj-95748	143	25	using	use	VERB
esrj-95748	143	26	natural	natural	ADJ
esrj-95748	143	27	break	break	NOUN
esrj-95748	143	28	algorithm	algorithm	NOUN
esrj-95748	143	29	in	in	ADP
esrj-95748	143	30	arcgis	arcgis	PROPN
esrj-95748	143	31	.	.	PUNCT
esrj-95748	144	1	evaluation	evaluation	NOUN
esrj-95748	144	2	of	of	ADP
esrj-95748	144	3	discrimination	discrimination	NOUN
esrj-95748	144	4	and	and	CCONJ
esrj-95748	144	5	reliability	reliability	NOUN
esrj-95748	144	6	of	of	ADP
esrj-95748	144	7	the	the	DET
esrj-95748	144	8	models	model	NOUN
esrj-95748	144	9	the	the	DET
esrj-95748	144	10	predictive	predictive	ADJ
esrj-95748	144	11	performance	performance	NOUN
esrj-95748	144	12	of	of	ADP
esrj-95748	144	13	models	model	NOUN
esrj-95748	144	14	was	be	AUX
esrj-95748	144	15	discriminated	discriminate	VERB
esrj-95748	144	16	using	use	VERB
esrj-95748	144	17	the	the	DET
esrj-95748	144	18	roc	roc	NOUN
esrj-95748	144	19	and	and	CCONJ
esrj-95748	144	20	auc	auc	ADJ
esrj-95748	144	21	curves	curve	NOUN
esrj-95748	144	22	.	.	PUNCT
esrj-95748	145	1	the	the	DET
esrj-95748	145	2	roc	roc	PROPN
esrj-95748	145	3	curve	curve	NOUN
esrj-95748	145	4	plots	plot	NOUN
esrj-95748	145	5	sensitivity	sensitivity	NOUN
esrj-95748	145	6	(	(	PUNCT
esrj-95748	145	7	x	x	NOUN
esrj-95748	145	8	-	-	NOUN
esrj-95748	145	9	axis	axis	ADJ
esrj-95748	145	10	)	)	PUNCT
esrj-95748	145	11	against	against	ADP
esrj-95748	145	12	1	1	NUM
esrj-95748	145	13	specificity	specificity	NOUN
esrj-95748	145	14	(	(	PUNCT
esrj-95748	145	15	y	y	NOUN
esrj-95748	145	16	-	-	PUNCT
esrj-95748	145	17	axis	axis	NOUN
esrj-95748	145	18	)	)	PUNCT
esrj-95748	145	19	,	,	PUNCT
esrj-95748	145	20	where	where	SCONJ
esrj-95748	145	21	sensitivity	sensitivity	NOUN
esrj-95748	145	22	is	be	AUX
esrj-95748	145	23	the	the	DET
esrj-95748	145	24	true	true	ADJ
esrj-95748	145	25	positive	positive	ADJ
esrj-95748	145	26	rate	rate	NOUN
esrj-95748	145	27	and	and	CCONJ
esrj-95748	145	28	specificity	specificity	NOUN
esrj-95748	145	29	is	be	AUX
esrj-95748	145	30	the	the	DET
esrj-95748	145	31	true	true	ADJ
esrj-95748	145	32	negative	negative	ADJ
esrj-95748	145	33	rate	rate	NOUN
esrj-95748	145	34	.	.	PUNCT
esrj-95748	146	1	auc	auc	NOUN
esrj-95748	146	2	values	value	NOUN
esrj-95748	146	3	close	close	ADJ
esrj-95748	146	4	to	to	ADP
esrj-95748	146	5	0.5	0.5	NUM
esrj-95748	146	6	reflects	reflect	VERB
esrj-95748	146	7	the	the	DET
esrj-95748	146	8	predictive	predictive	ADJ
esrj-95748	146	9	ability	ability	NOUN
esrj-95748	146	10	of	of	ADP
esrj-95748	146	11	a	a	DET
esrj-95748	146	12	random	random	ADJ
esrj-95748	146	13	model	model	NOUN
esrj-95748	146	14	,	,	PUNCT
esrj-95748	146	15	whereas	whereas	SCONJ
esrj-95748	146	16	value	value	NOUN
esrj-95748	146	17	close	close	ADV
esrj-95748	146	18	to	to	PART
esrj-95748	146	19	1.0	1.0	NUM
esrj-95748	146	20	reveals	reveal	VERB
esrj-95748	146	21	perfect	perfect	ADJ
esrj-95748	146	22	accuracy	accuracy	NOUN
esrj-95748	146	23	.	.	PUNCT
esrj-95748	147	1	in	in	ADP
esrj-95748	147	2	this	this	DET
esrj-95748	147	3	study	study	NOUN
esrj-95748	147	4	,	,	PUNCT
esrj-95748	147	5	the	the	DET
esrj-95748	147	6	auc	auc	NOUN
esrj-95748	147	7	values	value	NOUN
esrj-95748	147	8	were	be	AUX
esrj-95748	147	9	classified	classify	VERB
esrj-95748	147	10	into	into	ADP
esrj-95748	147	11	four	four	NUM
esrj-95748	147	12	levels	level	NOUN
esrj-95748	147	13	,	,	PUNCT
esrj-95748	147	14	including	include	VERB
esrj-95748	147	15	moderate	moderate	ADJ
esrj-95748	147	16	(	(	PUNCT
esrj-95748	147	17	0.6	0.6	NUM
esrj-95748	147	18	to	to	ADP
esrj-95748	147	19	0.7	0.7	NUM
esrj-95748	147	20	)	)	PUNCT
esrj-95748	147	21	,	,	PUNCT
esrj-95748	147	22	good	good	ADJ
esrj-95748	147	23	(	(	PUNCT
esrj-95748	147	24	0.7	0.7	NUM
esrj-95748	147	25	to	to	PART
esrj-95748	147	26	0.8	0.8	NUM
esrj-95748	147	27	)	)	PUNCT
esrj-95748	147	28	,	,	PUNCT
esrj-95748	147	29	very	very	ADV
esrj-95748	147	30	good	good	ADJ
esrj-95748	147	31	(	(	PUNCT
esrj-95748	147	32	0.8	0.8	NUM
esrj-95748	147	33	to	to	PART
esrj-95748	147	34	0.9	0.9	NUM
esrj-95748	147	35	)	)	PUNCT
esrj-95748	147	36	,	,	PUNCT
esrj-95748	147	37	and	and	CCONJ
esrj-95748	147	38	excellent	excellent	ADJ
esrj-95748	147	39	(	(	PUNCT
esrj-95748	147	40	0.9	0.9	NUM
esrj-95748	147	41	to	to	ADP
esrj-95748	147	42	1.0	1.0	NUM
esrj-95748	147	43	)	)	PUNCT
esrj-95748	147	44	.	.	PUNCT
esrj-95748	148	1	the	the	DET
esrj-95748	148	2	present	present	ADJ
esrj-95748	148	3	research	research	NOUN
esrj-95748	148	4	plotted	plot	VERB
esrj-95748	148	5	the	the	DET
esrj-95748	148	6	roc	roc	PROPN
esrj-95748	148	7	curve	curve	NOUN
esrj-95748	148	8	based	base	VERB
esrj-95748	148	9	on	on	ADP
esrj-95748	148	10	both	both	DET
esrj-95748	148	11	datasets	dataset	NOUN
esrj-95748	148	12	of	of	ADP
esrj-95748	148	13	the	the	DET
esrj-95748	148	14	train	train	NOUN
esrj-95748	148	15	(	(	PUNCT
esrj-95748	148	16	70	70	NUM
esrj-95748	148	17	%	%	NOUN
esrj-95748	148	18	of	of	ADP
esrj-95748	148	19	gullied	gully	VERB
esrj-95748	148	20	locations	location	NOUN
esrj-95748	148	21	)	)	PUNCT
esrj-95748	148	22	and	and	CCONJ
esrj-95748	148	23	validation	validation	NOUN
esrj-95748	148	24	(	(	PUNCT
esrj-95748	148	25	30	30	NUM
esrj-95748	148	26	%	%	NOUN
esrj-95748	148	27	of	of	ADP
esrj-95748	148	28	gullied	gully	VERB
esrj-95748	148	29	locations	location	NOUN
esrj-95748	148	30	)	)	PUNCT
esrj-95748	148	31	.	.	PUNCT
esrj-95748	149	1	the	the	DET
esrj-95748	149	2	following	follow	VERB
esrj-95748	149	3	equations	equation	NOUN
esrj-95748	149	4	were	be	AUX
esrj-95748	149	5	employed	employ	VERB
esrj-95748	149	6	to	to	PART
esrj-95748	149	7	draw	draw	VERB
esrj-95748	149	8	the	the	DET
esrj-95748	149	9	roc	roc	PROPN
esrj-95748	149	10	curve	curve	NOUN
esrj-95748	149	11	:	:	PUNCT
esrj-95748	149	12	(	(	PUNCT
esrj-95748	149	13	10	10	NUM
esrj-95748	149	14	)	)	PUNCT
esrj-95748	149	15	(	(	PUNCT
esrj-95748	149	16	11	11	NUM
esrj-95748	149	17	)	)	PUNCT
esrj-95748	149	18	where	where	SCONJ
esrj-95748	149	19	tp	tp	NOUN
esrj-95748	149	20	,	,	PUNCT
esrj-95748	149	21	fn	fn	PROPN
esrj-95748	149	22	,	,	PUNCT
esrj-95748	149	23	tn	tn	PROPN
esrj-95748	149	24	and	and	CCONJ
esrj-95748	149	25	fp	fp	PROPN
esrj-95748	149	26	are	be	AUX
esrj-95748	149	27	the	the	DET
esrj-95748	149	28	true	true	ADJ
esrj-95748	149	29	positive	positive	ADJ
esrj-95748	149	30	,	,	PUNCT
esrj-95748	149	31	false	false	ADJ
esrj-95748	149	32	negative	negative	ADJ
esrj-95748	149	33	,	,	PUNCT
esrj-95748	149	34	true	true	ADJ
esrj-95748	149	35	negative	negative	ADJ
esrj-95748	149	36	and	and	CCONJ
esrj-95748	149	37	false	false	ADJ
esrj-95748	149	38	positive	positive	ADJ
esrj-95748	149	39	rates	rate	NOUN
esrj-95748	149	40	,	,	PUNCT
esrj-95748	149	41	respectively	respectively	ADV
esrj-95748	149	42	.	.	PUNCT
esrj-95748	150	1	reliability	reliability	NOUN
esrj-95748	150	2	of	of	ADP
esrj-95748	150	3	model	model	NOUN
esrj-95748	150	4	accuracy	accuracy	NOUN
esrj-95748	150	5	was	be	AUX
esrj-95748	150	6	then	then	ADV
esrj-95748	150	7	evaluated	evaluate	VERB
esrj-95748	150	8	using	use	VERB
esrj-95748	150	9	rmse	rmse	NOUN
esrj-95748	150	10	(	(	PUNCT
esrj-95748	150	11	eq	eq	NOUN
esrj-95748	150	12	.	.	PROPN
esrj-95748	150	13	12	12	NUM
esrj-95748	150	14	)	)	PUNCT
esrj-95748	150	15	and	and	CCONJ
esrj-95748	150	16	r2	r2	PROPN
esrj-95748	150	17	.	.	PUNCT
esrj-95748	151	1	rmse	rmse	PROPN
esrj-95748	151	2	is	be	AUX
esrj-95748	151	3	defined	define	VERB
esrj-95748	151	4	as	as	ADP
esrj-95748	151	5	the	the	DET
esrj-95748	151	6	differences	difference	NOUN
esrj-95748	151	7	between	between	ADP
esrj-95748	151	8	the	the	DET
esrj-95748	151	9	values	value	NOUN
esrj-95748	151	10	actually	actually	ADV
esrj-95748	151	11	observed	observe	VERB
esrj-95748	151	12	(	(	PUNCT
esrj-95748	151	13	i.e.	i.e.	X
esrj-95748	151	14	gullied	gullied	ADJ
esrj-95748	151	15	locations	location	NOUN
esrj-95748	151	16	in	in	ADP
esrj-95748	151	17	the	the	DET
esrj-95748	151	18	region	region	NOUN
esrj-95748	151	19	)	)	PUNCT
esrj-95748	151	20	and	and	CCONJ
esrj-95748	151	21	values	value	NOUN
esrj-95748	151	22	predicted	predict	VERB
esrj-95748	151	23	(	(	PUNCT
esrj-95748	151	24	i.e.	i.e.	X
esrj-95748	151	25	gullyprone	gullyprone	NOUN
esrj-95748	151	26	areas	area	NOUN
esrj-95748	151	27	based	base	VERB
esrj-95748	151	28	on	on	ADP
esrj-95748	151	29	the	the	DET
esrj-95748	151	30	model	model	NOUN
esrj-95748	151	31	predictions	prediction	NOUN
esrj-95748	151	32	)	)	PUNCT
esrj-95748	151	33	.	.	PUNCT
esrj-95748	152	1	a	a	DET
esrj-95748	152	2	lower	low	ADJ
esrj-95748	152	3	value	value	NOUN
esrj-95748	152	4	for	for	ADP
esrj-95748	152	5	rmse	rmse	NOUN
esrj-95748	152	6	and	and	CCONJ
esrj-95748	152	7	a	a	DET
esrj-95748	152	8	higher	high	ADJ
esrj-95748	152	9	value	value	NOUN
esrj-95748	152	10	for	for	ADP
esrj-95748	152	11	r2	r2	PROPN
esrj-95748	152	12	show	show	VERB
esrj-95748	152	13	the	the	DET
esrj-95748	152	14	robust	robust	ADJ
esrj-95748	152	15	performance	performance	NOUN
esrj-95748	152	16	of	of	ADP
esrj-95748	152	17	the	the	DET
esrj-95748	152	18	models	model	NOUN
esrj-95748	152	19	(	(	PUNCT
esrj-95748	152	20	garosi	garosi	NOUN
esrj-95748	152	21	et	et	PROPN
esrj-95748	152	22	al	al	PROPN
esrj-95748	152	23	.	.	PROPN
esrj-95748	152	24	,	,	PUNCT
esrj-95748	152	25	2019	2019	NUM
esrj-95748	152	26	)	)	PUNCT
esrj-95748	152	27	(	(	PUNCT
esrj-95748	152	28	12	12	NUM
esrj-95748	152	29	)	)	PUNCT
esrj-95748	152	30	where	where	SCONJ
esrj-95748	152	31	y	y	PROPN
esrj-95748	152	32	(	(	PUNCT
esrj-95748	152	33	actual	actual	ADJ
esrj-95748	152	34	values	value	NOUN
esrj-95748	152	35	of	of	ADP
esrj-95748	152	36	dependent	dependent	ADJ
esrj-95748	152	37	factor	factor	NOUN
esrj-95748	152	38	)	)	PUNCT
esrj-95748	152	39	,	,	PUNCT
esrj-95748	152	40	ỹ	ỹ	X
esrj-95748	152	41	(	(	PUNCT
esrj-95748	152	42	predicted	predict	VERB
esrj-95748	152	43	values	value	NOUN
esrj-95748	152	44	of	of	ADP
esrj-95748	152	45	dependent	dependent	ADJ
esrj-95748	152	46	factor	factor	NOUN
esrj-95748	152	47	)	)	PUNCT
esrj-95748	152	48	,	,	PUNCT
esrj-95748	152	49	and	and	CCONJ
esrj-95748	152	50	n	n	X
esrj-95748	152	51	(	(	PUNCT
esrj-95748	152	52	sample	sample	NOUN
esrj-95748	152	53	size	size	NOUN
esrj-95748	152	54	)	)	PUNCT
esrj-95748	152	55	.	.	PUNCT
esrj-95748	153	1	results	result	NOUN
esrj-95748	153	2	and	and	CCONJ
esrj-95748	153	3	discussion	discussion	NOUN
esrj-95748	153	4	multi	multi	NOUN
esrj-95748	153	5	-	-	NOUN
esrj-95748	153	6	collinearity	collinearity	NOUN
esrj-95748	153	7	between	between	ADP
esrj-95748	153	8	variables	variable	NOUN
esrj-95748	153	9	controlling	control	VERB
esrj-95748	153	10	gully	gully	ADJ
esrj-95748	153	11	erosion	erosion	NOUN
esrj-95748	153	12	as	as	SCONJ
esrj-95748	153	13	shown	show	VERB
esrj-95748	153	14	in	in	ADP
esrj-95748	153	15	table	table	NOUN
esrj-95748	153	16	1	1	NUM
esrj-95748	153	17	,	,	PUNCT
esrj-95748	153	18	tol	tol	NOUN
esrj-95748	153	19	and	and	CCONJ
esrj-95748	153	20	vif	vif	NOUN
esrj-95748	153	21	values	value	NOUN
esrj-95748	153	22	for	for	ADP
esrj-95748	153	23	all	all	DET
esrj-95748	153	24	the	the	DET
esrj-95748	153	25	variables	variable	NOUN
esrj-95748	153	26	were	be	AUX
esrj-95748	153	27	higher	high	ADJ
esrj-95748	153	28	than	than	ADP
esrj-95748	153	29	0.2	0.2	NUM
esrj-95748	153	30	and	and	CCONJ
esrj-95748	153	31	less	less	ADJ
esrj-95748	153	32	than	than	ADP
esrj-95748	153	33	5	5	NUM
esrj-95748	153	34	,	,	PUNCT
esrj-95748	153	35	respectively	respectively	ADV
esrj-95748	153	36	.	.	PUNCT
esrj-95748	154	1	the	the	DET
esrj-95748	154	2	greatest	great	ADJ
esrj-95748	154	3	values	value	NOUN
esrj-95748	154	4	for	for	ADP
esrj-95748	154	5	vif	vif	NOUN
esrj-95748	154	6	and	and	CCONJ
esrj-95748	154	7	the	the	DET
esrj-95748	154	8	lowest	low	ADJ
esrj-95748	154	9	coefficients	coefficient	NOUN
esrj-95748	154	10	for	for	ADP
esrj-95748	154	11	tol	tol	NOUN
esrj-95748	154	12	were	be	AUX
esrj-95748	154	13	2.38	2.38	NUM
esrj-95748	154	14	and	and	CCONJ
esrj-95748	154	15	0.42	0.42	NUM
esrj-95748	154	16	,	,	PUNCT
esrj-95748	154	17	respectively	respectively	ADV
esrj-95748	154	18	.	.	PUNCT
esrj-95748	155	1	this	this	DET
esrj-95748	155	2	result	result	NOUN
esrj-95748	155	3	illustrates	illustrate	VERB
esrj-95748	155	4	no	no	DET
esrj-95748	155	5	collinearity	collinearity	NOUN
esrj-95748	155	6	problem	problem	NOUN
esrj-95748	155	7	among	among	ADP
esrj-95748	155	8	the	the	DET
esrj-95748	155	9	twelve	twelve	NUM
esrj-95748	155	10	independent	independent	ADJ
esrj-95748	155	11	variables	variable	NOUN
esrj-95748	155	12	and	and	CCONJ
esrj-95748	155	13	,	,	PUNCT
esrj-95748	155	14	therefore	therefore	ADV
esrj-95748	155	15	,	,	PUNCT
esrj-95748	155	16	all	all	DET
esrj-95748	155	17	the	the	DET
esrj-95748	155	18	factors	factor	NOUN
esrj-95748	155	19	were	be	AUX
esrj-95748	155	20	considered	consider	VERB
esrj-95748	155	21	for	for	ADP
esrj-95748	155	22	the	the	DET
esrj-95748	155	23	modeling	modeling	NOUN
esrj-95748	155	24	process	process	NOUN
esrj-95748	155	25	.	.	PUNCT
esrj-95748	156	1	table	table	NOUN
esrj-95748	156	2	1	1	NUM
esrj-95748	156	3	.	.	PUNCT
esrj-95748	156	4	results	result	NOUN
esrj-95748	156	5	of	of	ADP
esrj-95748	156	6	the	the	DET
esrj-95748	156	7	collinearity	collinearity	NOUN
esrj-95748	156	8	among	among	ADP
esrj-95748	156	9	independent	independent	ADJ
esrj-95748	156	10	variables	variable	NOUN
esrj-95748	156	11	factor	factor	NOUN
esrj-95748	156	12	tolerance	tolerance	NOUN
esrj-95748	156	13	vif	vif	NOUN
esrj-95748	156	14	elevation	elevation	NOUN
esrj-95748	156	15	0.58	0.58	NUM
esrj-95748	156	16	1.72	1.72	NUM
esrj-95748	156	17	slope	slope	NOUN
esrj-95748	156	18	0.89	0.89	NUM
esrj-95748	156	19	1.12	1.12	NUM
esrj-95748	156	20	aspect	aspect	NOUN
esrj-95748	156	21	0.96	0.96	NUM
esrj-95748	156	22	1.04	1.04	NUM
esrj-95748	156	23	river	river	NOUN
esrj-95748	156	24	density	density	NOUN
esrj-95748	156	25	0.49	0.49	NUM
esrj-95748	156	26	2.03	2.03	NUM
esrj-95748	156	27	lithology	lithology	NOUN
esrj-95748	156	28	0.84	0.84	NUM
esrj-95748	156	29	1.19	1.19	NUM
esrj-95748	156	30	land	land	NOUN
esrj-95748	156	31	use	use	NOUN
esrj-95748	156	32	0.92	0.92	NUM
esrj-95748	156	33	1.09	1.09	NUM
esrj-95748	156	34	distance	distance	NOUN
esrj-95748	156	35	from	from	ADP
esrj-95748	156	36	river	river	NOUN
esrj-95748	156	37	0.44	0.44	NUM
esrj-95748	156	38	2.25	2.25	NUM
esrj-95748	156	39	distance	distance	NOUN
esrj-95748	156	40	from	from	ADP
esrj-95748	156	41	fault	fault	NOUN
esrj-95748	156	42	0.55	0.55	NUM
esrj-95748	156	43	1.81	1.81	NUM
esrj-95748	156	44	distance	distance	NOUN
esrj-95748	156	45	from	from	ADP
esrj-95748	156	46	road	road	NOUN
esrj-95748	156	47	0.73	0.73	NUM
esrj-95748	156	48	1.36	1.36	NUM
esrj-95748	156	49	plan	plan	NOUN
esrj-95748	156	50	curvature	curvature	VERB
esrj-95748	156	51	0.42	0.42	NUM
esrj-95748	156	52	2.38	2.38	NUM
esrj-95748	156	53	topographic	topographic	PROPN
esrj-95748	156	54	wetness	wetness	PROPN
esrj-95748	156	55	index	index	NOUN
esrj-95748	156	56	0.96	0.96	NUM
esrj-95748	156	57	1.04	1.04	NUM
esrj-95748	156	58	stream	stream	NOUN
esrj-95748	156	59	power	power	NOUN
esrj-95748	156	60	index	index	NOUN
esrj-95748	156	61	0.96	0.96	NUM
esrj-95748	156	62	1.05	1.05	NUM
esrj-95748	156	63	importance	importance	NOUN
esrj-95748	156	64	of	of	ADP
esrj-95748	156	65	conditioning	conditioning	NOUN
esrj-95748	156	66	variables	variable	NOUN
esrj-95748	156	67	and	and	CCONJ
esrj-95748	156	68	their	their	PRON
esrj-95748	156	69	relationship	relationship	NOUN
esrj-95748	156	70	with	with	ADP
esrj-95748	156	71	gully	gully	ADJ
esrj-95748	156	72	erosion	erosion	NOUN
esrj-95748	156	73	table	table	NOUN
esrj-95748	156	74	2	2	NUM
esrj-95748	156	75	shows	show	VERB
esrj-95748	156	76	the	the	DET
esrj-95748	156	77	spatial	spatial	ADJ
esrj-95748	156	78	correlation	correlation	NOUN
esrj-95748	156	79	between	between	ADP
esrj-95748	156	80	the	the	DET
esrj-95748	156	81	independent	independent	ADJ
esrj-95748	156	82	variables	variable	NOUN
esrj-95748	156	83	and	and	CCONJ
esrj-95748	156	84	the	the	DET
esrj-95748	156	85	spatial	spatial	ADJ
esrj-95748	156	86	distribution	distribution	NOUN
esrj-95748	156	87	of	of	ADP
esrj-95748	156	88	gullied	gully	VERB
esrj-95748	156	89	locations	location	NOUN
esrj-95748	156	90	according	accord	VERB
esrj-95748	156	91	to	to	ADP
esrj-95748	156	92	the	the	DET
esrj-95748	156	93	results	result	NOUN
esrj-95748	156	94	of	of	ADP
esrj-95748	156	95	the	the	DET
esrj-95748	156	96	ebf	ebf	NOUN
esrj-95748	156	97	method	method	NOUN
esrj-95748	156	98	.	.	PUNCT
esrj-95748	157	1	the	the	DET
esrj-95748	157	2	highest	high	ADJ
esrj-95748	157	3	ebf	ebf	NOUN
esrj-95748	157	4	value	value	NOUN
esrj-95748	157	5	was	be	AUX
esrj-95748	157	6	observed	observe	VERB
esrj-95748	157	7	in	in	ADP
esrj-95748	157	8	the	the	DET
esrj-95748	157	9	elevation	elevation	NOUN
esrj-95748	157	10	class	class	NOUN
esrj-95748	157	11	of	of	ADP
esrj-95748	157	12	472	472	NUM
esrj-95748	157	13	-	-	SYM
esrj-95748	157	14	899	899	NUM
esrj-95748	157	15	m	m	NOUN
esrj-95748	157	16	asl	asl	NOUN
esrj-95748	157	17	(	(	PUNCT
esrj-95748	157	18	bel=	bel=	PROPN
esrj-95748	157	19	0.54	0.54	NUM
esrj-95748	157	20	)	)	PUNCT
esrj-95748	157	21	,	,	PUNCT
esrj-95748	157	22	followed	follow	VERB
esrj-95748	157	23	by	by	ADP
esrj-95748	157	24	the	the	DET
esrj-95748	157	25	elevation	elevation	NOUN
esrj-95748	157	26	classes	class	NOUN
esrj-95748	157	27	of	of	ADP
esrj-95748	157	28	46–472	46–472	NUM
esrj-95748	157	29	m	m	VERB
esrj-95748	157	30	asl	asl	NOUN
esrj-95748	157	31	(	(	PUNCT
esrj-95748	157	32	bel=	bel=	PROPN
esrj-95748	157	33	0.39	0.39	NUM
esrj-95748	157	34	)	)	PUNCT
esrj-95748	157	35	and	and	CCONJ
esrj-95748	157	36	899	899	NUM
esrj-95748	157	37	-	-	SYM
esrj-95748	157	38	1,326	1,326	NUM
esrj-95748	157	39	m	m	NOUN
esrj-95748	157	40	asl	asl	NOUN
esrj-95748	157	41	(	(	PUNCT
esrj-95748	157	42	bel=	bel=	PROPN
esrj-95748	157	43	0.23	0.23	NUM
esrj-95748	157	44	)	)	PUNCT
esrj-95748	157	45	.	.	PUNCT
esrj-95748	158	1	no	no	DET
esrj-95748	158	2	gullying	gullying	NOUN
esrj-95748	158	3	occurred	occur	VERB
esrj-95748	158	4	in	in	ADP
esrj-95748	158	5	the	the	DET
esrj-95748	158	6	highest	high	ADJ
esrj-95748	158	7	elevation	elevation	NOUN
esrj-95748	158	8	class	class	NOUN
esrj-95748	158	9	,	,	PUNCT
esrj-95748	158	10	i.e.	i.e.	X
esrj-95748	158	11	,	,	PUNCT
esrj-95748	158	12	1,753–2,180	1,753–2,180	NUM
esrj-95748	158	13	m	m	PROPN
esrj-95748	158	14	asl	asl	NOUN
esrj-95748	158	15	(	(	PUNCT
esrj-95748	158	16	bel=	bel=	PROPN
esrj-95748	158	17	0	0	NUM
esrj-95748	158	18	)	)	PUNCT
esrj-95748	158	19	.	.	PUNCT
esrj-95748	159	1	these	these	DET
esrj-95748	159	2	findings	finding	NOUN
esrj-95748	159	3	showed	show	VERB
esrj-95748	159	4	that	that	SCONJ
esrj-95748	159	5	there	there	PRON
esrj-95748	159	6	is	be	VERB
esrj-95748	159	7	a	a	DET
esrj-95748	159	8	negative	negative	ADJ
esrj-95748	159	9	correlation	correlation	NOUN
esrj-95748	159	10	between	between	ADP
esrj-95748	159	11	elevation	elevation	NOUN
esrj-95748	159	12	and	and	CCONJ
esrj-95748	159	13	gullied	gully	VERB
esrj-95748	159	14	locations	location	NOUN
esrj-95748	159	15	so	so	SCONJ
esrj-95748	159	16	that	that	SCONJ
esrj-95748	159	17	the	the	DET
esrj-95748	159	18	greatest	great	ADJ
esrj-95748	159	19	gullying	gullying	NOUN
esrj-95748	159	20	occurred	occur	VERB
esrj-95748	159	21	in	in	ADP
esrj-95748	159	22	lowland	lowland	NOUN
esrj-95748	159	23	positions	position	NOUN
esrj-95748	159	24	(	(	PUNCT
esrj-95748	159	25	values	value	NOUN
esrj-95748	159	26	of	of	ADP
esrj-95748	159	27	plan	plan	NOUN
esrj-95748	159	28	curvature	curvature	NOUN
esrj-95748	159	29	)	)	PUNCT
esrj-95748	159	30	.	.	PUNCT
esrj-95748	160	1	the	the	DET
esrj-95748	160	2	highest	high	ADJ
esrj-95748	160	3	gullying	gullying	NOUN
esrj-95748	160	4	occurred	occur	VERB
esrj-95748	160	5	in	in	ADP
esrj-95748	160	6	the	the	DET
esrj-95748	160	7	slope	slope	NOUN
esrj-95748	160	8	classes	class	NOUN
esrj-95748	160	9	of	of	ADP
esrj-95748	160	10	5	5	NUM
esrj-95748	160	11	-	-	SYM
esrj-95748	160	12	10	10	NUM
esrj-95748	160	13	°	°	NOUN
esrj-95748	160	14	(	(	PUNCT
esrj-95748	160	15	bel=	bel=	PROPN
esrj-95748	160	16	0.88	0.88	NUM
esrj-95748	160	17	)	)	PUNCT
esrj-95748	160	18	and	and	CCONJ
esrj-95748	160	19	10	10	NUM
esrj-95748	160	20	-	-	SYM
esrj-95748	160	21	20	20	NUM
esrj-95748	160	22	°	°	NOUN
esrj-95748	160	23	(	(	PUNCT
esrj-95748	160	24	bel=	bel=	PROPN
esrj-95748	160	25	0.61	0.61	NUM
esrj-95748	160	26	)	)	PUNCT
esrj-95748	160	27	.	.	PUNCT
esrj-95748	161	1	furthermore	furthermore	ADV
esrj-95748	161	2	,	,	PUNCT
esrj-95748	161	3	gullies	gully	NOUN
esrj-95748	161	4	frequency	frequency	NOUN
esrj-95748	161	5	significantly	significantly	ADV
esrj-95748	161	6	decreased	decrease	VERB
esrj-95748	161	7	in	in	ADP
esrj-95748	161	8	the	the	DET
esrj-95748	161	9	slope	slope	NOUN
esrj-95748	161	10	classes	class	NOUN
esrj-95748	161	11	higher	high	ADJ
esrj-95748	161	12	than	than	ADP
esrj-95748	161	13	20	20	NUM
esrj-95748	161	14	°	°	NOUN
esrj-95748	161	15	(	(	PUNCT
esrj-95748	161	16	bel=	bel=	PROPN
esrj-95748	161	17	0.30	0.30	NUM
esrj-95748	161	18	)	)	PUNCT
esrj-95748	161	19	.	.	PUNCT
esrj-95748	162	1	the	the	DET
esrj-95748	162	2	most	most	ADV
esrj-95748	162	3	frequent	frequent	ADJ
esrj-95748	162	4	occurrence	occurrence	NOUN
esrj-95748	162	5	of	of	ADP
esrj-95748	162	6	gullies	gully	NOUN
esrj-95748	162	7	was	be	AUX
esrj-95748	162	8	observed	observe	VERB
esrj-95748	162	9	in	in	ADP
esrj-95748	162	10	the	the	DET
esrj-95748	162	11	northeast	northeast	NOUN
esrj-95748	162	12	,	,	PUNCT
esrj-95748	162	13	east	east	PROPN
esrj-95748	162	14	,	,	PUNCT
esrj-95748	162	15	southeast	southeast	ADJ
esrj-95748	162	16	,	,	PUNCT
esrj-95748	162	17	south	south	ADJ
esrj-95748	162	18	,	,	PUNCT
esrj-95748	162	19	southwest	southwest	NOUN
esrj-95748	162	20	,	,	PUNCT
esrj-95748	162	21	and	and	CCONJ
esrj-95748	162	22	northwest	northwest	ADJ
esrj-95748	162	23	directions	direction	NOUN
esrj-95748	162	24	.	.	PUNCT
esrj-95748	163	1	the	the	DET
esrj-95748	163	2	highest	high	ADJ
esrj-95748	163	3	values	value	NOUN
esrj-95748	163	4	for	for	ADP
esrj-95748	163	5	river	river	NOUN
esrj-95748	163	6	density	density	NOUN
esrj-95748	163	7	were	be	AUX
esrj-95748	163	8	observed	observe	VERB
esrj-95748	163	9	in	in	ADP
esrj-95748	163	10	the	the	DET
esrj-95748	163	11	classes	class	NOUN
esrj-95748	163	12	of	of	ADP
esrj-95748	163	13	1.01	1.01	NUM
esrj-95748	163	14	-	-	SYM
esrj-95748	163	15	1.26	1.26	NUM
esrj-95748	163	16	m	m	NOUN
esrj-95748	163	17	/	/	SYM
esrj-95748	163	18	m2	m2	PROPN
esrj-95748	163	19	(	(	PUNCT
esrj-95748	163	20	bel=	bel=	PROPN
esrj-95748	163	21	0.53	0.53	NUM
esrj-95748	163	22	)	)	PUNCT
esrj-95748	163	23	and	and	CCONJ
esrj-95748	163	24	0.76	0.76	NUM
esrj-95748	163	25	-	-	SYM
esrj-95748	163	26	1.01	1.01	NUM
esrj-95748	163	27	m	m	NOUN
esrj-95748	163	28	/	/	SYM
esrj-95748	163	29	m2	m2	PROPN
esrj-95748	163	30	(	(	PUNCT
esrj-95748	163	31	bel=	bel=	PROPN
esrj-95748	163	32	0.44	0.44	NUM
esrj-95748	163	33	)	)	PUNCT
esrj-95748	163	34	.	.	PUNCT
esrj-95748	164	1	in	in	ADP
esrj-95748	164	2	the	the	DET
esrj-95748	164	3	case	case	NOUN
esrj-95748	164	4	of	of	ADP
esrj-95748	164	5	lithological	lithological	ADJ
esrj-95748	164	6	units	unit	NOUN
esrj-95748	164	7	,	,	PUNCT
esrj-95748	164	8	gully	gully	NOUN
esrj-95748	164	9	erosion	erosion	NOUN
esrj-95748	164	10	showed	show	VERB
esrj-95748	164	11	its	its	PRON
esrj-95748	164	12	highest	high	ADJ
esrj-95748	164	13	occurrence	occurrence	NOUN
esrj-95748	164	14	in	in	ADP
esrj-95748	164	15	weak	weak	ADJ
esrj-95748	164	16	textured	textured	ADJ
esrj-95748	164	17	soils	soil	NOUN
esrj-95748	164	18	,	,	PUNCT
esrj-95748	164	19	i.e.	i.e.	X
esrj-95748	164	20	,	,	PUNCT
esrj-95748	164	21	loess	loess	NOUN
esrj-95748	164	22	(	(	PUNCT
esrj-95748	164	23	bel=	bel=	PROPN
esrj-95748	164	24	0.76	0.76	NUM
esrj-95748	164	25	)	)	PUNCT
esrj-95748	164	26	and	and	CCONJ
esrj-95748	164	27	marl	marl	NOUN
esrj-95748	164	28	(	(	PUNCT
esrj-95748	164	29	bel=	bel=	PROPN
esrj-95748	164	30	0.57	0.57	NUM
esrj-95748	164	31	)	)	PUNCT
esrj-95748	164	32	.	.	PUNCT
esrj-95748	165	1	based	base	VERB
esrj-95748	165	2	on	on	ADP
esrj-95748	165	3	table	table	NOUN
esrj-95748	165	4	2	2	NUM
esrj-95748	165	5	,	,	PUNCT
esrj-95748	165	6	the	the	DET
esrj-95748	165	7	highest	high	ADJ
esrj-95748	165	8	and	and	CCONJ
esrj-95748	165	9	the	the	DET
esrj-95748	165	10	lowest	low	ADJ
esrj-95748	165	11	gullying	gullying	NOUN
esrj-95748	165	12	occurred	occur	VERB
esrj-95748	165	13	in	in	ADP
esrj-95748	165	14	the	the	DET
esrj-95748	165	15	rangeland	rangeland	NOUN
esrj-95748	165	16	(	(	PUNCT
esrj-95748	165	17	bel=	bel=	PROPN
esrj-95748	165	18	0.73	0.73	NUM
esrj-95748	165	19	)	)	PUNCT
esrj-95748	165	20	shrubland	shrubland	NOUN
esrj-95748	165	21	(	(	PUNCT
esrj-95748	165	22	bel=	bel=	PROPN
esrj-95748	165	23	0.41	0.41	NUM
esrj-95748	165	24	)	)	PUNCT
esrj-95748	165	25	and	and	CCONJ
esrj-95748	165	26	forest	forest	NOUN
esrj-95748	165	27	(	(	PUNCT
esrj-95748	165	28	bel=	bel=	PROPN
esrj-95748	165	29	0.12	0.12	NUM
esrj-95748	165	30	)	)	PUNCT
esrj-95748	165	31	,	,	PUNCT
esrj-95748	165	32	respectively	respectively	ADV
esrj-95748	165	33	.	.	PUNCT
esrj-95748	166	1	the	the	DET
esrj-95748	166	2	results	result	NOUN
esrj-95748	166	3	of	of	ADP
esrj-95748	166	4	distance	distance	NOUN
esrj-95748	166	5	from	from	ADP
esrj-95748	166	6	rivers	river	NOUN
esrj-95748	166	7	showed	show	VERB
esrj-95748	166	8	that	that	SCONJ
esrj-95748	166	9	the	the	DET
esrj-95748	166	10	occurrence	occurrence	NOUN
esrj-95748	166	11	of	of	ADP
esrj-95748	166	12	gully	gully	ADJ
esrj-95748	166	13	erosion	erosion	NOUN
esrj-95748	166	14	increased	increase	VERB
esrj-95748	166	15	as	as	SCONJ
esrj-95748	166	16	the	the	DET
esrj-95748	166	17	distance	distance	NOUN
esrj-95748	166	18	to	to	ADP
esrj-95748	166	19	rivers	river	NOUN
esrj-95748	166	20	decreased	decrease	VERB
esrj-95748	166	21	(	(	PUNCT
esrj-95748	166	22	bel=	bel=	PROPN
esrj-95748	166	23	0.53	0.53	NUM
esrj-95748	166	24	for	for	ADP
esrj-95748	166	25	the	the	DET
esrj-95748	166	26	class	class	NOUN
esrj-95748	166	27	of	of	ADP
esrj-95748	166	28	0	0	NUM
esrj-95748	166	29	-	-	SYM
esrj-95748	166	30	658	658	NUM
esrj-95748	166	31	m	m	NOUN
esrj-95748	166	32	and	and	CCONJ
esrj-95748	166	33	bel=	bel=	PROPN
esrj-95748	166	34	0.40	0.40	NUM
esrj-95748	166	35	for	for	ADP
esrj-95748	166	36	the	the	DET
esrj-95748	166	37	class	class	NOUN
esrj-95748	166	38	of	of	ADP
esrj-95748	166	39	658	658	NUM
esrj-95748	166	40	-	-	SYM
esrj-95748	166	41	1,515	1,515	NUM
esrj-95748	166	42	m	m	NOUN
esrj-95748	166	43	)	)	PUNCT
esrj-95748	166	44	.	.	PUNCT
esrj-95748	167	1	furthermore	furthermore	ADV
esrj-95748	167	2	,	,	PUNCT
esrj-95748	167	3	the	the	DET
esrj-95748	167	4	gully	gully	NOUN
esrj-95748	167	5	erosion	erosion	NOUN
esrj-95748	167	6	occurrence	occurrence	NOUN
esrj-95748	167	7	reached	reach	VERB
esrj-95748	167	8	zero	zero	NUM
esrj-95748	167	9	in	in	ADP
esrj-95748	167	10	the	the	DET
esrj-95748	167	11	highest	high	ADJ
esrj-95748	167	12	distance	distance	NOUN
esrj-95748	167	13	to	to	ADP
esrj-95748	167	14	rivers	river	NOUN
esrj-95748	167	15	(	(	PUNCT
esrj-95748	167	16	classes	class	NOUN
esrj-95748	167	17	of	of	ADP
esrj-95748	167	18	4,189	4,189	NUM
esrj-95748	167	19	-	-	SYM
esrj-95748	167	20	6,341	6,341	NUM
esrj-95748	167	21	m	m	NOUN
esrj-95748	167	22	and	and	CCONJ
esrj-95748	167	23	6,341	6,341	NUM
esrj-95748	167	24	-	-	SYM
esrj-95748	167	25	9,746	9,746	NUM
esrj-95748	167	26	m	m	NOUN
esrj-95748	167	27	)	)	PUNCT
esrj-95748	167	28	.	.	PUNCT
esrj-95748	168	1	the	the	DET
esrj-95748	168	2	ebf	ebf	NOUN
esrj-95748	168	3	exhibited	exhibit	VERB
esrj-95748	168	4	the	the	DET
esrj-95748	168	5	highest	high	ADJ
esrj-95748	168	6	weight	weight	NOUN
esrj-95748	168	7	of	of	ADP
esrj-95748	168	8	distance	distance	NOUN
esrj-95748	168	9	from	from	ADP
esrj-95748	168	10	fault	fault	NOUN
esrj-95748	168	11	in	in	ADP
esrj-95748	168	12	the	the	DET
esrj-95748	168	13	class	class	NOUN
esrj-95748	168	14	of	of	ADP
esrj-95748	168	15	3,000	3,000	NUM
esrj-95748	168	16	-	-	SYM
esrj-95748	168	17	6,000	6,000	NUM
esrj-95748	168	18	m	m	NOUN
esrj-95748	168	19	(	(	PUNCT
esrj-95748	168	20	bel=	bel=	PROPN
esrj-95748	168	21	0.49	0.49	NUM
esrj-95748	168	22	)	)	PUNCT
esrj-95748	168	23	.	.	PUNCT
esrj-95748	169	1	therefore	therefore	ADV
esrj-95748	169	2	,	,	PUNCT
esrj-95748	169	3	the	the	DET
esrj-95748	169	4	ebf	ebf	NOUN
esrj-95748	169	5	decreased	decrease	VERB
esrj-95748	169	6	(	(	PUNCT
esrj-95748	169	7	i.e.	i.e.	X
esrj-95748	169	8	decreasing	decrease	VERB
esrj-95748	169	9	gullying	gullying	NOUN
esrj-95748	169	10	)	)	PUNCT
esrj-95748	169	11	as	as	SCONJ
esrj-95748	169	12	the	the	DET
esrj-95748	169	13	distance	distance	NOUN
esrj-95748	169	14	from	from	ADP
esrj-95748	169	15	the	the	DET
esrj-95748	169	16	fault	fault	NOUN
esrj-95748	169	17	increased	increase	VERB
esrj-95748	169	18	.	.	PUNCT
esrj-95748	170	1	the	the	DET
esrj-95748	170	2	probability	probability	NOUN
esrj-95748	170	3	of	of	ADP
esrj-95748	170	4	gullying	gullye	VERB
esrj-95748	170	5	increased	increase	VERB
esrj-95748	170	6	as	as	ADP
esrj-95748	170	7	distance	distance	NOUN
esrj-95748	170	8	to	to	ADP
esrj-95748	170	9	the	the	DET
esrj-95748	170	10	roads	road	NOUN
esrj-95748	170	11	decreased	decrease	VERB
esrj-95748	170	12	(	(	PUNCT
esrj-95748	170	13	bel=	bel=	PROPN
esrj-95748	170	14	0.59	0.59	NUM
esrj-95748	170	15	for	for	ADP
esrj-95748	170	16	the	the	DET
esrj-95748	170	17	class	class	NOUN
esrj-95748	170	18	of	of	ADP
esrj-95748	170	19	500	500	NUM
esrj-95748	170	20	-	-	SYM
esrj-95748	170	21	1,000	1,000	NUM
esrj-95748	170	22	m	m	NOUN
esrj-95748	170	23	and	and	CCONJ
esrj-95748	170	24	bel=	bel=	PROPN
esrj-95748	170	25	0.47	0.47	NUM
esrj-95748	170	26	for	for	ADP
esrj-95748	170	27	the	the	DET
esrj-95748	170	28	class	class	NOUN
esrj-95748	170	29	of	of	ADP
esrj-95748	170	30	0	0	NUM
esrj-95748	170	31	-	-	SYM
esrj-95748	170	32	500	500	NUM
esrj-95748	170	33	m	m	NOUN
esrj-95748	170	34	)	)	PUNCT
esrj-95748	170	35	.	.	PUNCT
esrj-95748	171	1	these	these	DET
esrj-95748	171	2	findings	finding	NOUN
esrj-95748	171	3	show	show	VERB
esrj-95748	171	4	the	the	DET
esrj-95748	171	5	crucial	crucial	ADJ
esrj-95748	171	6	effect	effect	NOUN
esrj-95748	171	7	of	of	ADP
esrj-95748	171	8	the	the	DET
esrj-95748	171	9	road	road	NOUN
esrj-95748	171	10	network	network	NOUN
esrj-95748	171	11	on	on	ADP
esrj-95748	171	12	increasing	increase	VERB
esrj-95748	171	13	the	the	DET
esrj-95748	171	14	probability	probability	NOUN
esrj-95748	171	15	of	of	ADP
esrj-95748	171	16	gully	gully	ADJ
esrj-95748	171	17	erosion	erosion	NOUN
esrj-95748	171	18	occurrence	occurrence	NOUN
esrj-95748	171	19	due	due	ADP
esrj-95748	171	20	to	to	ADP
esrj-95748	171	21	the	the	DET
esrj-95748	171	22	anthropogenic	anthropogenic	ADJ
esrj-95748	171	23	destruction	destruction	NOUN
esrj-95748	171	24	of	of	ADP
esrj-95748	171	25	natural	natural	ADJ
esrj-95748	171	26	hydrological	hydrological	ADJ
esrj-95748	171	27	processes	process	NOUN
esrj-95748	171	28	that	that	PRON
esrj-95748	171	29	encourages	encourage	VERB
esrj-95748	171	30	the	the	DET
esrj-95748	171	31	accumulation	accumulation	NOUN
esrj-95748	171	32	of	of	ADP
esrj-95748	171	33	surface	surface	NOUN
esrj-95748	171	34	runoff	runoff	NOUN
esrj-95748	171	35	and	and	CCONJ
esrj-95748	171	36	accelerates	accelerate	VERB
esrj-95748	171	37	broad	broad	ADJ
esrj-95748	171	38	-	-	PUNCT
esrj-95748	171	39	scale	scale	NOUN
esrj-95748	171	40	soil	soil	NOUN
esrj-95748	171	41	erosion	erosion	NOUN
esrj-95748	171	42	.	.	PUNCT
esrj-95748	172	1	the	the	DET
esrj-95748	172	2	ebf	ebf	NOUN
esrj-95748	172	3	value	value	NOUN
esrj-95748	172	4	for	for	ADP
esrj-95748	172	5	plan	plan	NOUN
esrj-95748	172	6	curvature	curvature	NOUN
esrj-95748	172	7	was	be	AUX
esrj-95748	172	8	highest	high	ADJ
esrj-95748	172	9	in	in	ADP
esrj-95748	172	10	the	the	DET
esrj-95748	172	11	concave	concave	ADJ
esrj-95748	172	12	positions	position	NOUN
esrj-95748	172	13	(	(	PUNCT
esrj-95748	172	14	bel=	bel=	PROPN
esrj-95748	172	15	0.61	0.61	NUM
esrj-95748	172	16	)	)	PUNCT
esrj-95748	172	17	,	,	PUNCT
esrj-95748	172	18	compared	compare	VERB
esrj-95748	172	19	with	with	ADP
esrj-95748	172	20	the	the	DET
esrj-95748	172	21	convex	convex	NOUN
esrj-95748	172	22	positions	position	NOUN
esrj-95748	172	23	(	(	PUNCT
esrj-95748	172	24	bel=	bel=	PROPN
esrj-95748	172	25	0.23	0.23	NUM
esrj-95748	172	26	)	)	PUNCT
esrj-95748	172	27	.	.	PUNCT
esrj-95748	173	1	the	the	DET
esrj-95748	173	2	highest	high	ADJ
esrj-95748	173	3	ebf	ebf	NOUN
esrj-95748	173	4	weights	weight	NOUN
esrj-95748	173	5	for	for	ADP
esrj-95748	173	6	twi	twi	NUM
esrj-95748	173	7	were	be	AUX
esrj-95748	173	8	observed	observe	VERB
esrj-95748	173	9	in	in	ADP
esrj-95748	173	10	the	the	DET
esrj-95748	173	11	classes	class	NOUN
esrj-95748	173	12	of	of	ADP
esrj-95748	173	13	12	12	NUM
esrj-95748	173	14	-	-	SYM
esrj-95748	173	15	15.6	15.6	NUM
esrj-95748	173	16	(	(	PUNCT
esrj-95748	173	17	bel=	bel=	PROPN
esrj-95748	173	18	0.36	0.36	NUM
esrj-95748	173	19	)	)	PUNCT
esrj-95748	173	20	and	and	CCONJ
esrj-95748	173	21	9	9	NUM
esrj-95748	173	22	-	-	SYM
esrj-95748	173	23	12	12	NUM
esrj-95748	173	24	(	(	PUNCT
esrj-95748	173	25	bel=	bel=	PROPN
esrj-95748	173	26	0.35	0.35	NUM
esrj-95748	173	27	)	)	PUNCT
esrj-95748	173	28	.	.	PUNCT
esrj-95748	174	1	therefore	therefore	ADV
esrj-95748	174	2	,	,	PUNCT
esrj-95748	174	3	the	the	DET
esrj-95748	174	4	probability	probability	NOUN
esrj-95748	174	5	of	of	ADP
esrj-95748	174	6	gullying	gullye	VERB
esrj-95748	174	7	enhanced	enhance	VERB
esrj-95748	174	8	in	in	ADP
esrj-95748	174	9	higher	high	ADJ
esrj-95748	174	10	topographic	topographic	ADJ
esrj-95748	174	11	wetness	wetness	NOUN
esrj-95748	174	12	.	.	PUNCT
esrj-95748	175	1	further	far	ADV
esrj-95748	175	2	,	,	PUNCT
esrj-95748	175	3	the	the	DET
esrj-95748	175	4	greatest	great	ADJ
esrj-95748	175	5	gullying	gullying	NOUN
esrj-95748	175	6	occurred	occur	VERB
esrj-95748	175	7	in	in	ADP
esrj-95748	175	8	the	the	DET
esrj-95748	175	9	highest	high	ADJ
esrj-95748	175	10	spi	spi	NOUN
esrj-95748	175	11	(	(	PUNCT
esrj-95748	175	12	bel=	bel=	PROPN
esrj-95748	175	13	0.61	0.61	NUM
esrj-95748	175	14	for	for	ADP
esrj-95748	175	15	the	the	DET
esrj-95748	175	16	class	class	NOUN
esrj-95748	175	17	of	of	ADP
esrj-95748	175	18	0	0	NUM
esrj-95748	175	19	-	-	SYM
esrj-95748	175	20	7	7	NUM
esrj-95748	175	21	)	)	PUNCT
esrj-95748	175	22	,	,	PUNCT
esrj-95748	175	23	illustrating	illustrate	VERB
esrj-95748	175	24	the	the	DET
esrj-95748	175	25	probability	probability	NOUN
esrj-95748	175	26	of	of	ADP
esrj-95748	175	27	gully	gully	ADJ
esrj-95748	175	28	erosion	erosion	NOUN
esrj-95748	175	29	is	be	AUX
esrj-95748	175	30	higher	high	ADJ
esrj-95748	175	31	in	in	ADP
esrj-95748	175	32	higher	high	ADJ
esrj-95748	175	33	stream	stream	NOUN
esrj-95748	175	34	power	power	NOUN
esrj-95748	175	35	.	.	PUNCT
esrj-95748	176	1	428	428	NUM
esrj-95748	176	2	mahdieh	mahdieh	PROPN
esrj-95748	176	3	valipour	valipour	NOUN
esrj-95748	176	4	,	,	PUNCT
esrj-95748	176	5	neda	neda	PROPN
esrj-95748	176	6	mohseni	mohseni	NOUN
esrj-95748	176	7	,	,	PUNCT
esrj-95748	176	8	seyed	seyed	PROPN
esrj-95748	176	9	reza	reza	PROPN
esrj-95748	176	10	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	176	11	table	table	NOUN
esrj-95748	176	12	2	2	NUM
esrj-95748	176	13	.	.	PUNCT
esrj-95748	176	14	correlation	correlation	NOUN
esrj-95748	176	15	among	among	ADP
esrj-95748	176	16	conditioning	conditioning	NOUN
esrj-95748	176	17	factors	factor	NOUN
esrj-95748	176	18	and	and	CCONJ
esrj-95748	176	19	gully	gully	NOUN
esrj-95748	176	20	erosion	erosion	NOUN
esrj-95748	176	21	based	base	VERB
esrj-95748	176	22	on	on	ADP
esrj-95748	176	23	the	the	DET
esrj-95748	176	24	ebf	ebf	NOUN
esrj-95748	176	25	model	model	NOUN
esrj-95748	176	26	factor	factor	NOUN
esrj-95748	176	27	class	class	NOUN
esrj-95748	176	28	bel	bel	NOUN
esrj-95748	176	29	dis	dis	PROPN
esrj-95748	176	30	unc	unc	PROPN
esrj-95748	176	31	pls	pls	PROPN
esrj-95748	176	32	elevation	elevation	PROPN
esrj-95748	176	33	(	(	PUNCT
esrj-95748	176	34	masl	masl	PROPN
esrj-95748	176	35	)	)	PUNCT
esrj-95748	176	36	46	46	NUM
esrj-95748	177	1	472.8	472.8	NUM
esrj-95748	177	2	0.39	0.39	NUM
esrj-95748	177	3	0.05	0.05	NUM
esrj-95748	177	4	0.65	0.65	NUM
esrj-95748	177	5	0.94	0.94	NUM
esrj-95748	177	6	472.8	472.8	NUM
esrj-95748	177	7	899.6	899.6	NUM
esrj-95748	177	8	0.54	0.54	NUM
esrj-95748	177	9	0.17	0.17	NUM
esrj-95748	177	10	0.28	0.28	NUM
esrj-95748	177	11	0.82	0.82	NUM
esrj-95748	177	12	899.61326.4	899.61326.4	NUM
esrj-95748	177	13	0.23	0.23	NUM
esrj-95748	177	14	0.09	0.09	NUM
esrj-95748	177	15	0.76	0.76	NUM
esrj-95748	177	16	0.90	0.90	NUM
esrj-95748	177	17	1,326.4	1,326.4	NUM
esrj-95748	177	18	–	–	PUNCT
esrj-95748	177	19	1,753.2	1,753.2	NUM
esrj-95748	177	20	0.03	0.03	NUM
esrj-95748	177	21	0.51	0.51	NUM
esrj-95748	177	22	0.45	0.45	NUM
esrj-95748	177	23	0.48	0.48	NUM
esrj-95748	177	24	1,753.2	1,753.2	NUM
esrj-95748	177	25	–	–	PUNCT
esrj-95748	177	26	2,180	2,180	NUM
esrj-95748	177	27	0	0	NUM
esrj-95748	178	1	0.16	0.16	NUM
esrj-95748	178	2	0.83	0.83	NUM
esrj-95748	178	3	0.83	0.83	NUM
esrj-95748	178	4	slope	slope	NOUN
esrj-95748	178	5	(	(	PUNCT
esrj-95748	178	6	degree	degree	NOUN
esrj-95748	178	7	)	)	PUNCT
esrj-95748	178	8	0	0	NUM
esrj-95748	178	9	–	–	PUNCT
esrj-95748	178	10	5	5	NUM
esrj-95748	178	11	0.12	0.12	NUM
esrj-95748	178	12	0.25	0.25	NUM
esrj-95748	178	13	0.61	0.61	NUM
esrj-95748	178	14	0.74	0.74	NUM
esrj-95748	178	15	5	5	NUM
esrj-95748	178	16	-	-	SYM
esrj-95748	178	17	10	10	NUM
esrj-95748	178	18	0.88	0.88	NUM
esrj-95748	178	19	0.21	0.21	NUM
esrj-95748	178	20	0.09	0.09	NUM
esrj-95748	178	21	0.78	0.78	NUM
esrj-95748	178	22	10	10	NUM
esrj-95748	178	23	-	-	SYM
esrj-95748	178	24	20	20	NUM
esrj-95748	178	25	0.61	0.61	NUM
esrj-95748	178	26	0.02	0.02	NUM
esrj-95748	178	27	0.76	0.76	NUM
esrj-95748	178	28	0.97	0.97	NUM
esrj-95748	178	29	20	20	NUM
esrj-95748	178	30	–	–	PUNCT
esrj-95748	178	31	30	30	NUM
esrj-95748	178	32	0.30	0.30	NUM
esrj-95748	178	33	0.55	0.55	NUM
esrj-95748	178	34	0.23	0.23	NUM
esrj-95748	178	35	0.44	0.44	NUM
esrj-95748	178	36	>	>	PUNCT
esrj-95748	178	37	30	30	NUM
esrj-95748	178	38	0.34	0.34	NUM
esrj-95748	178	39	0.00	0.00	NUM
esrj-95748	178	40	0.74	0.74	NUM
esrj-95748	178	41	0.99	0.99	NUM
esrj-95748	178	42	aspect	aspect	NOUN
esrj-95748	178	43	flat	flat	ADJ
esrj-95748	178	44	0.06	0.06	NUM
esrj-95748	178	45	0.54	0.54	NUM
esrj-95748	178	46	0.38	0.38	NUM
esrj-95748	178	47	0.45	0.45	NUM
esrj-95748	178	48	north	north	NOUN
esrj-95748	178	49	0.09	0.09	NUM
esrj-95748	178	50	1.08	1.08	NUM
esrj-95748	178	51	-0.18	-0.18	NUM
esrj-95748	178	52	-0.08	-0.08	ADV
esrj-95748	178	53	northeast	northeast	ADJ
esrj-95748	178	54	0.21	0.21	NUM
esrj-95748	178	55	0.41	0.41	NUM
esrj-95748	178	56	0.47	0.47	NUM
esrj-95748	178	57	0.58	0.58	NUM
esrj-95748	178	58	east	east	NOUN
esrj-95748	178	59	0.22	0.22	NUM
esrj-95748	178	60	1.66	1.66	NUM
esrj-95748	178	61	-0.78	-0.78	NUM
esrj-95748	178	62	-0.66	-0.66	NUM
esrj-95748	178	63	southeast	southeast	NOUN
esrj-95748	178	64	0.25	0.25	NUM
esrj-95748	178	65	0.78	0.78	NUM
esrj-95748	178	66	0.05	0.05	NUM
esrj-95748	178	67	0.21	0.21	NUM
esrj-95748	178	68	south	south	NOUN
esrj-95748	178	69	0.27	0.27	NUM
esrj-95748	178	70	0.14	0.14	NUM
esrj-95748	178	71	0.67	0.67	NUM
esrj-95748	178	72	0.85	0.85	NUM
esrj-95748	178	73	southwest	southwest	NOUN
esrj-95748	178	74	0.24	0.24	NUM
esrj-95748	178	75	0.12	0.12	NUM
esrj-95748	178	76	0.73	0.73	NUM
esrj-95748	178	77	0.87	0.87	NUM
esrj-95748	178	78	west	west	NOUN
esrj-95748	178	79	0.01	0.01	NUM
esrj-95748	178	80	1.14	1.14	NUM
esrj-95748	178	81	-0.15	-0.15	NUM
esrj-95748	178	82	-0.14	-0.14	NUM
esrj-95748	178	83	northwest	northwest	ADV
esrj-95748	178	84	0.21	0.21	NUM
esrj-95748	178	85	0.75	0.75	NUM
esrj-95748	178	86	0.134	0.134	NUM
esrj-95748	178	87	0.24	0.24	NUM
esrj-95748	178	88	river	river	NOUN
esrj-95748	178	89	density	density	NOUN
esrj-95748	178	90	(	(	PUNCT
esrj-95748	178	91	m	m	NOUN
esrj-95748	178	92	/	/	SYM
esrj-95748	178	93	m2	m2	PROPN
esrj-95748	178	94	)	)	PUNCT
esrj-95748	178	95	0	0	NUM
esrj-95748	179	1	0.253	0.253	NUM
esrj-95748	179	2	0.04	0.04	NUM
esrj-95748	179	3	0.29	0.29	NUM
esrj-95748	179	4	0.66	0.66	NUM
esrj-95748	179	5	0.70	0.70	NUM
esrj-95748	179	6	0.253	0.253	NUM
esrj-95748	179	7	0.507	0.507	NUM
esrj-95748	179	8	0.19	0.19	NUM
esrj-95748	179	9	0.13	0.13	NUM
esrj-95748	179	10	0.67	0.67	NUM
esrj-95748	179	11	0.86	0.86	NUM
esrj-95748	179	12	0.507	0.507	NUM
esrj-95748	179	13	0.761	0.761	NUM
esrj-95748	179	14	0.37	0.37	NUM
esrj-95748	179	15	0.19	0.19	NUM
esrj-95748	179	16	0.53	0.53	NUM
esrj-95748	179	17	0.80	0.80	NUM
esrj-95748	179	18	0.761	0.761	NUM
esrj-95748	179	19	1.014	1.014	NUM
esrj-95748	179	20	0.44	0.44	NUM
esrj-95748	179	21	0.17	0.17	NUM
esrj-95748	179	22	0.57	0.57	NUM
esrj-95748	179	23	0.82	0.82	NUM
esrj-95748	179	24	1.014	1.014	NUM
esrj-95748	179	25	1.268	1.268	NUM
esrj-95748	179	26	0.53	0.53	NUM
esrj-95748	179	27	0.21	0.21	NUM
esrj-95748	179	28	0.55	0.55	NUM
esrj-95748	179	29	0.78	0.78	NUM
esrj-95748	179	30	lithology	lithology	NOUN
esrj-95748	179	31	limestone	limestone	NOUN
esrj-95748	179	32	0	0	NUM
esrj-95748	179	33	0.00	0.00	NUM
esrj-95748	179	34	0.99	0.99	NUM
esrj-95748	179	35	0.99	0.99	NUM
esrj-95748	179	36	colluvium	colluvium	NOUN
esrj-95748	179	37	0.00	0.00	NUM
esrj-95748	179	38	0.11	0.11	NUM
esrj-95748	179	39	0.88	0.88	NUM
esrj-95748	179	40	0.88	0.88	NUM
esrj-95748	179	41	shale	shale	NOUN
esrj-95748	179	42	0	0	NUM
esrj-95748	179	43	0.11	0.11	NUM
esrj-95748	179	44	0.88	0.88	NUM
esrj-95748	179	45	0.88	0.88	NUM
esrj-95748	179	46	conglomerate	conglomerate	NOUN
esrj-95748	179	47	&	&	CCONJ
esrj-95748	179	48	sandstone	sandstone	NOUN
esrj-95748	179	49	0	0	NUM
esrj-95748	179	50	0.01	0.01	NUM
esrj-95748	179	51	0.98	0.98	NUM
esrj-95748	179	52	0.98	0.98	NUM
esrj-95748	179	53	loess	loess	NOUN
esrj-95748	179	54	0.76	0.76	NUM
esrj-95748	179	55	0.10	0.10	NUM
esrj-95748	179	56	0.73	0.73	NUM
esrj-95748	179	57	0.90	0.90	NUM
esrj-95748	179	58	marl	marl	NOUN
esrj-95748	179	59	0.57	0.57	NUM
esrj-95748	179	60	0.10	0.10	NUM
esrj-95748	179	61	0.72	0.72	NUM
esrj-95748	179	62	0.89	0.89	NUM
esrj-95748	179	63	land	land	NOUN
esrj-95748	179	64	use	use	NOUN
esrj-95748	179	65	/	/	SYM
esrj-95748	179	66	cover	cover	NOUN
esrj-95748	179	67	cultivated	cultivate	VERB
esrj-95748	179	68	land	land	NOUN
esrj-95748	179	69	0.31	0.31	NUM
esrj-95748	179	70	1.45	1.45	NUM
esrj-95748	179	71	-0.77	-0.77	NUM
esrj-95748	179	72	-0.45	-0.45	NUM
esrj-95748	179	73	forest	forest	NOUN
esrj-95748	179	74	0.12	0.12	NUM
esrj-95748	179	75	0.15	0.15	NUM
esrj-95748	179	76	0.72	0.72	NUM
esrj-95748	179	77	0.84	0.84	NUM
esrj-95748	179	78	bare	bare	ADJ
esrj-95748	179	79	land	land	NOUN
esrj-95748	179	80	0.26	0.26	NUM
esrj-95748	179	81	0.10	0.10	NUM
esrj-95748	179	82	0.63	0.63	NUM
esrj-95748	179	83	0.89	0.89	NUM
esrj-95748	179	84	shrubland	shrubland	NOUN
esrj-95748	179	85	0.41	0.41	NUM
esrj-95748	179	86	1.45	1.45	NUM
esrj-95748	179	87	-0.77	-0.77	NUM
esrj-95748	179	88	-0.45	-0.45	NUM
esrj-95748	179	89	water	water	NOUN
esrj-95748	179	90	body	body	NOUN
esrj-95748	179	91	0	0	NUM
esrj-95748	179	92	0.00	0.00	NUM
esrj-95748	179	93	0.99	0.99	NUM
esrj-95748	179	94	0.99	0.99	NUM
esrj-95748	179	95	residential	residential	ADJ
esrj-95748	179	96	0	0	NUM
esrj-95748	179	97	0.01	0.01	NUM
esrj-95748	179	98	0.98	0.98	NUM
esrj-95748	179	99	0.98	0.98	NUM
esrj-95748	179	100	rangeland	rangeland	NOUN
esrj-95748	179	101	0.73	0.73	NUM
esrj-95748	179	102	1.87	1.87	NUM
esrj-95748	179	103	0.03	0.03	NUM
esrj-95748	179	104	0.08	0.08	NUM
esrj-95748	179	105	distance	distance	NOUN
esrj-95748	179	106	from	from	ADP
esrj-95748	179	107	river	river	PROPN
esrj-95748	179	108	(	(	PUNCT
esrj-95748	179	109	m	m	NOUN
esrj-95748	179	110	)	)	PUNCT
esrj-95748	179	111	0	0	NUM
esrj-95748	180	1	658.28	658.28	NUM
esrj-95748	180	2	0.53	0.53	NUM
esrj-95748	180	3	0.15	0.15	NUM
esrj-95748	180	4	0.63	0.63	NUM
esrj-95748	180	5	0.84	0.84	NUM
esrj-95748	180	6	658.28	658.28	NUM
esrj-95748	180	7	–	–	PUNCT
esrj-95748	180	8	1,515.49	1,515.49	NUM
esrj-95748	180	9	0.40	0.40	NUM
esrj-95748	180	10	0.21	0.21	NUM
esrj-95748	180	11	0.58	0.58	NUM
esrj-95748	180	12	0.78	0.78	NUM
esrj-95748	180	13	1,515.49	1,515.49	NUM
esrj-95748	180	14	–	–	PUNCT
esrj-95748	180	15	2,574.91	2,574.91	NUM
esrj-95748	180	16	0.06	0.06	NUM
esrj-95748	180	17	0.10	0.10	NUM
esrj-95748	180	18	0.83	0.83	NUM
esrj-95748	180	19	0.89	0.89	NUM
esrj-95748	180	20	2,574.91	2,574.91	NUM
esrj-95748	180	21	–	–	PUNCT
esrj-95748	180	22	4,189.32	4,189.32	NUM
esrj-95748	180	23	0.03	0.03	NUM
esrj-95748	180	24	0.00	0.00	NUM
esrj-95748	180	25	0.95	0.95	NUM
esrj-95748	180	26	0.99	0.99	NUM
esrj-95748	180	27	4,189.32	4,189.32	NUM
esrj-95748	180	28	–	–	PUNCT
esrj-95748	180	29	6,341.47	6,341.47	NUM
esrj-95748	180	30	0	0	NUM
esrj-95748	180	31	0.04	0.04	NUM
esrj-95748	180	32	0.95	0.95	NUM
esrj-95748	180	33	0.95	0.95	NUM
esrj-95748	180	34	6,341.479,746.22	6,341.479,746.22	NUM
esrj-95748	180	35	0	0	NUM
esrj-95748	180	36	0.41	0.41	NUM
esrj-95748	180	37	0.58	0.58	NUM
esrj-95748	180	38	0.58	0.58	NUM
esrj-95748	180	39	distance	distance	NOUN
esrj-95748	180	40	from	from	ADP
esrj-95748	180	41	fault	fault	NOUN
esrj-95748	180	42	(	(	PUNCT
esrj-95748	180	43	m	m	NOUN
esrj-95748	180	44	)	)	PUNCT
esrj-95748	180	45	0	0	NUM
esrj-95748	180	46	–	–	PUNCT
esrj-95748	181	1	3,000	3,000	NUM
esrj-95748	181	2	0.18	0.18	NUM
esrj-95748	181	3	0.31	0.31	NUM
esrj-95748	181	4	0.49	0.49	NUM
esrj-95748	181	5	0.68	0.68	NUM
esrj-95748	181	6	3,000	3,000	NUM
esrj-95748	181	7	–	–	PUNCT
esrj-95748	181	8	6,000	6,000	NUM
esrj-95748	181	9	0.49	0.49	NUM
esrj-95748	181	10	0.10	0.10	NUM
esrj-95748	181	11	0.60	0.60	NUM
esrj-95748	181	12	0.89	0.89	NUM
esrj-95748	181	13	6,000	6,000	NUM
esrj-95748	181	14	–	–	PUNCT
esrj-95748	181	15	9,000	9,000	NUM
esrj-95748	181	16	0.16	0.16	NUM
esrj-95748	181	17	0.11	0.11	NUM
esrj-95748	181	18	0.72	0.72	NUM
esrj-95748	181	19	0.88	0.88	NUM
esrj-95748	181	20	9,000	9,000	NUM
esrj-95748	181	21	–	–	PUNCT
esrj-95748	181	22	14,000	14,000	NUM
esrj-95748	181	23	0.18	0.18	NUM
esrj-95748	181	24	0.11	0.11	NUM
esrj-95748	181	25	0.70	0.70	NUM
esrj-95748	181	26	0.88	0.88	NUM
esrj-95748	181	27	14,000	14,000	NUM
esrj-95748	181	28	–	–	PUNCT
esrj-95748	181	29	19,000	19,000	NUM
esrj-95748	181	30	0.13	0.13	NUM
esrj-95748	181	31	0.11	0.11	NUM
esrj-95748	181	32	0.74	0.74	NUM
esrj-95748	181	33	0.88	0.88	NUM
esrj-95748	181	34	19,000	19,000	NUM
esrj-95748	181	35	–	–	PUNCT
esrj-95748	181	36	23,000	23,000	NUM
esrj-95748	181	37	0.03	0.03	NUM
esrj-95748	181	38	0.11	0.11	NUM
esrj-95748	181	39	0.85	0.85	NUM
esrj-95748	181	40	0.88	0.88	NUM
esrj-95748	181	41	23,000	23,000	NUM
esrj-95748	181	42	–	–	PUNCT
esrj-95748	181	43	36,363	36,363	NUM
esrj-95748	181	44	0	0	NUM
esrj-95748	181	45	0.12	0.12	NUM
esrj-95748	181	46	0.87	0.87	NUM
esrj-95748	181	47	0.87	0.87	NUM
esrj-95748	181	48	distance	distance	NOUN
esrj-95748	181	49	from	from	ADP
esrj-95748	181	50	road	road	NOUN
esrj-95748	181	51	(	(	PUNCT
esrj-95748	181	52	m	m	NOUN
esrj-95748	181	53	)	)	PUNCT
esrj-95748	181	54	0	0	NUM
esrj-95748	181	55	–	–	PUNCT
esrj-95748	181	56	500	500	NUM
esrj-95748	181	57	0.47	0.47	NUM
esrj-95748	181	58	0.01	0.01	NUM
esrj-95748	181	59	0.50	0.50	NUM
esrj-95748	181	60	0.98	0.98	NUM
esrj-95748	181	61	500	500	NUM
esrj-95748	181	62	–	–	PUNCT
esrj-95748	181	63	1,000	1,000	NUM
esrj-95748	181	64	0.59	0.59	NUM
esrj-95748	181	65	0.21	0.21	NUM
esrj-95748	181	66	-0.02	-0.02	NUM
esrj-95748	181	67	0.78	0.78	NUM
esrj-95748	181	68	1,000	1,000	NUM
esrj-95748	181	69	–	–	PUNCT
esrj-95748	181	70	3,000	3,000	NUM
esrj-95748	181	71	0.16	0.16	NUM
esrj-95748	181	72	0.11	0.11	NUM
esrj-95748	181	73	0.72	0.72	NUM
esrj-95748	181	74	0.88	0.88	NUM
esrj-95748	181	75	3,000	3,000	NUM
esrj-95748	181	76	–	–	PUNCT
esrj-95748	181	77	6,000	6,000	NUM
esrj-95748	181	78	0.33	0.33	NUM
esrj-95748	181	79	0.24	0.24	NUM
esrj-95748	181	80	0.51	0.51	NUM
esrj-95748	181	81	0.75	0.75	NUM
esrj-95748	181	82	6,000	6,000	NUM
esrj-95748	181	83	–	–	PUNCT
esrj-95748	181	84	9,000	9,000	NUM
esrj-95748	181	85	0.03	0.03	NUM
esrj-95748	181	86	0.31	0.31	NUM
esrj-95748	181	87	0.64	0.64	NUM
esrj-95748	181	88	0.68	0.68	NUM
esrj-95748	181	89	9,000	9,000	NUM
esrj-95748	181	90	–	–	PUNCT
esrj-95748	181	91	11,963	11,963	NUM
esrj-95748	181	92	0	0	NUM
esrj-95748	181	93	0.10	0.10	NUM
esrj-95748	181	94	0.89	0.89	NUM
esrj-95748	181	95	0.89	0.89	NUM
esrj-95748	181	96	429factors	429factors	PROPN
esrj-95748	181	97	affecting	affect	VERB
esrj-95748	181	98	topographic	topographic	ADJ
esrj-95748	181	99	thresholds	threshold	NOUN
esrj-95748	181	100	in	in	ADP
esrj-95748	181	101	gully	gully	ADJ
esrj-95748	181	102	erosion	erosion	NOUN
esrj-95748	181	103	occurrence	occurrence	NOUN
esrj-95748	181	104	and	and	CCONJ
esrj-95748	181	105	its	its	PRON
esrj-95748	181	106	management	management	NOUN
esrj-95748	181	107	using	use	VERB
esrj-95748	181	108	predictive	predictive	ADJ
esrj-95748	181	109	machine	machine	NOUN
esrj-95748	181	110	learning	learning	NOUN
esrj-95748	181	111	models	model	NOUN
esrj-95748	181	112	factor	factor	NOUN
esrj-95748	181	113	class	class	NOUN
esrj-95748	181	114	bel	bel	NOUN
esrj-95748	181	115	dis	dis	PROPN
esrj-95748	181	116	unc	unc	PROPN
esrj-95748	181	117	pls	pls	PROPN
esrj-95748	181	118	plan	plan	PROPN
esrj-95748	181	119	curvature	curvature	NOUN
esrj-95748	181	120	convex	convex	NOUN
esrj-95748	181	121	(	(	PUNCT
esrj-95748	181	122	>	>	X
esrj-95748	181	123	0.15	0.15	NUM
esrj-95748	181	124	)	)	PUNCT
esrj-95748	181	125	0.23	0.23	NUM
esrj-95748	181	126	0.40	0.40	NUM
esrj-95748	181	127	0.35	0.35	NUM
esrj-95748	181	128	0.59	0.59	NUM
esrj-95748	181	129	concave	concave	NOUN
esrj-95748	181	130	(	(	PUNCT
esrj-95748	181	131	<	<	X
esrj-95748	181	132	-0.15	-0.15	NUM
esrj-95748	181	133	)	)	PUNCT
esrj-95748	181	134	0.61	0.61	NUM
esrj-95748	181	135	0.29	0.29	NUM
esrj-95748	181	136	0.11	0.11	NUM
esrj-95748	181	137	0.70	0.70	NUM
esrj-95748	181	138	flat	flat	ADJ
esrj-95748	181	139	(	(	PUNCT
esrj-95748	181	140	-0.15	-0.15	NUM
esrj-95748	181	141	0.15	0.15	NUM
esrj-95748	181	142	)	)	PUNCT
esrj-95748	181	143	0.16	0.16	NUM
esrj-95748	181	144	0.11	0.11	NUM
esrj-95748	181	145	0.72	0.72	NUM
esrj-95748	181	146	0.88	0.88	NUM
esrj-95748	181	147	topographic	topographic	ADJ
esrj-95748	181	148	wetness	wetness	NOUN
esrj-95748	181	149	index	index	NOUN
esrj-95748	181	150	3.5	3.5	NUM
esrj-95748	181	151	–	–	PUNCT
esrj-95748	181	152	6	6	NUM
esrj-95748	181	153	0.15	0.15	NUM
esrj-95748	181	154	0.02	0.02	NUM
esrj-95748	181	155	0.82	0.82	NUM
esrj-95748	181	156	0.97	0.97	NUM
esrj-95748	181	157	6	6	NUM
esrj-95748	181	158	–	–	PUNCT
esrj-95748	181	159	9	9	NUM
esrj-95748	181	160	0.23	0.23	NUM
esrj-95748	181	161	0.32	0.32	NUM
esrj-95748	181	162	0.44	0.44	NUM
esrj-95748	181	163	0.67	0.67	NUM
esrj-95748	181	164	9	9	NUM
esrj-95748	181	165	–	–	PUNCT
esrj-95748	181	166	12	12	NUM
esrj-95748	181	167	0.35	0.35	NUM
esrj-95748	181	168	0.43	0.43	NUM
esrj-95748	181	169	0.30	0.30	NUM
esrj-95748	181	170	0.56	0.56	NUM
esrj-95748	181	171	12	12	NUM
esrj-95748	181	172	–	–	PUNCT
esrj-95748	181	173	15.6	15.6	NUM
esrj-95748	181	174	0.36	0.36	NUM
esrj-95748	181	175	0.21	0.21	NUM
esrj-95748	181	176	0.42	0.42	NUM
esrj-95748	181	177	0.78	0.78	NUM
esrj-95748	181	178	stream	stream	NOUN
esrj-95748	181	179	power	power	NOUN
esrj-95748	181	180	index	index	NOUN
esrj-95748	181	181	-16	-16	PROPN
esrj-95748	181	182	-10	-10	PUNCT
esrj-95748	181	183	0	0	NUM
esrj-95748	181	184	0.02	0.02	NUM
esrj-95748	181	185	0.97	0.97	NUM
esrj-95748	181	186	0.97	0.97	NUM
esrj-95748	181	187	-10	-10	PUNCT
esrj-95748	181	188	–	–	PUNCT
esrj-95748	181	189	0	0	NUM
esrj-95748	181	190	0.38	0.38	NUM
esrj-95748	181	191	0.19	0.19	NUM
esrj-95748	181	192	0.41	0.41	NUM
esrj-95748	181	193	0.80	0.80	NUM
esrj-95748	181	194	0	0	NUM
esrj-95748	181	195	–	–	PUNCT
esrj-95748	181	196	7	7	NUM
esrj-95748	181	197	0.61	0.61	NUM
esrj-95748	181	198	0.77	0.77	NUM
esrj-95748	181	199	-0.39	-0.39	NUM
esrj-95748	181	200	0.22	0.22	NUM
esrj-95748	181	201	based	base	VERB
esrj-95748	181	202	on	on	ADP
esrj-95748	181	203	the	the	DET
esrj-95748	181	204	results	result	NOUN
esrj-95748	181	205	of	of	ADP
esrj-95748	181	206	the	the	DET
esrj-95748	181	207	boruta	boruta	NOUN
esrj-95748	181	208	algorithm	algorithm	NOUN
esrj-95748	181	209	,	,	PUNCT
esrj-95748	181	210	slope	slope	NOUN
esrj-95748	181	211	gradient	gradient	NOUN
esrj-95748	181	212	(	(	PUNCT
esrj-95748	181	213	25.65	25.65	NUM
esrj-95748	181	214	)	)	PUNCT
esrj-95748	181	215	,	,	PUNCT
esrj-95748	181	216	land	land	NOUN
esrj-95748	181	217	use	use	NOUN
esrj-95748	181	218	(	(	PUNCT
esrj-95748	181	219	10.65	10.65	NUM
esrj-95748	181	220	)	)	PUNCT
esrj-95748	181	221	,	,	PUNCT
esrj-95748	181	222	lithology	lithology	NOUN
esrj-95748	181	223	(	(	PUNCT
esrj-95748	181	224	10.94	10.94	NUM
esrj-95748	181	225	)	)	PUNCT
esrj-95748	181	226	,	,	PUNCT
esrj-95748	181	227	plan	plan	NOUN
esrj-95748	181	228	curvature	curvature	NOUN
esrj-95748	181	229	(	(	PUNCT
esrj-95748	181	230	7.15	7.15	NUM
esrj-95748	181	231	)	)	PUNCT
esrj-95748	181	232	,	,	PUNCT
esrj-95748	181	233	elevation	elevation	NOUN
esrj-95748	181	234	(	(	PUNCT
esrj-95748	181	235	6.30	6.30	NUM
esrj-95748	181	236	)	)	PUNCT
esrj-95748	181	237	,	,	PUNCT
esrj-95748	181	238	river	river	NOUN
esrj-95748	181	239	density	density	NOUN
esrj-95748	181	240	(	(	PUNCT
esrj-95748	181	241	5.30	5.30	NUM
esrj-95748	181	242	)	)	PUNCT
esrj-95748	181	243	,	,	PUNCT
esrj-95748	181	244	distance	distance	NOUN
esrj-95748	181	245	from	from	ADP
esrj-95748	181	246	river	river	NOUN
esrj-95748	181	247	(	(	PUNCT
esrj-95748	181	248	5.12	5.12	NUM
esrj-95748	181	249	)	)	PUNCT
esrj-95748	181	250	,	,	PUNCT
esrj-95748	181	251	were	be	AUX
esrj-95748	181	252	the	the	DET
esrj-95748	181	253	most	most	ADV
esrj-95748	181	254	important	important	ADJ
esrj-95748	181	255	factors	factor	NOUN
esrj-95748	181	256	that	that	PRON
esrj-95748	181	257	controlled	control	VERB
esrj-95748	181	258	gully	gully	ADJ
esrj-95748	181	259	erosion	erosion	NOUN
esrj-95748	181	260	susceptibility	susceptibility	NOUN
esrj-95748	181	261	(	(	PUNCT
esrj-95748	181	262	table	table	NOUN
esrj-95748	181	263	3	3	NUM
esrj-95748	181	264	)	)	PUNCT
esrj-95748	181	265	.	.	PUNCT
esrj-95748	182	1	the	the	DET
esrj-95748	182	2	lowest	low	ADJ
esrj-95748	182	3	importance	importance	NOUN
esrj-95748	182	4	variables	variable	NOUN
esrj-95748	182	5	for	for	ADP
esrj-95748	182	6	gully	gully	ADJ
esrj-95748	182	7	erosion	erosion	NOUN
esrj-95748	182	8	susceptibility	susceptibility	NOUN
esrj-95748	182	9	were	be	AUX
esrj-95748	182	10	slope	slope	NOUN
esrj-95748	182	11	aspect	aspect	NOUN
esrj-95748	182	12	(	(	PUNCT
esrj-95748	182	13	1.53	1.53	NUM
esrj-95748	182	14	)	)	PUNCT
esrj-95748	182	15	,	,	PUNCT
esrj-95748	182	16	distance	distance	NOUN
esrj-95748	182	17	from	from	ADP
esrj-95748	182	18	road	road	NOUN
esrj-95748	182	19	(	(	PUNCT
esrj-95748	182	20	2.15	2.15	NUM
esrj-95748	182	21	)	)	PUNCT
esrj-95748	182	22	,	,	PUNCT
esrj-95748	182	23	twi	twi	INTJ
esrj-95748	182	24	(	(	PUNCT
esrj-95748	182	25	2.19	2.19	NUM
esrj-95748	182	26	)	)	PUNCT
esrj-95748	182	27	,	,	PUNCT
esrj-95748	182	28	distance	distance	NOUN
esrj-95748	182	29	from	from	ADP
esrj-95748	182	30	fault	fault	NOUN
esrj-95748	182	31	(	(	PUNCT
esrj-95748	182	32	2.91	2.91	NUM
esrj-95748	182	33	)	)	PUNCT
esrj-95748	182	34	,	,	PUNCT
esrj-95748	182	35	and	and	CCONJ
esrj-95748	182	36	spi	spi	PROPN
esrj-95748	182	37	(	(	PUNCT
esrj-95748	182	38	2.93	2.93	NUM
esrj-95748	182	39	)	)	PUNCT
esrj-95748	182	40	.	.	PUNCT
esrj-95748	183	1	table	table	NOUN
esrj-95748	183	2	3	3	NUM
esrj-95748	183	3	.	.	PUNCT
esrj-95748	184	1	importance	importance	NOUN
esrj-95748	184	2	of	of	ADP
esrj-95748	184	3	independent	independent	ADJ
esrj-95748	184	4	variables	variable	NOUN
esrj-95748	184	5	based	base	VERB
esrj-95748	184	6	on	on	ADP
esrj-95748	184	7	boruta	boruta	NOUN
esrj-95748	184	8	algorithm	algorithm	NOUN
esrj-95748	184	9	factor	factor	NOUN
esrj-95748	184	10	mean	mean	VERB
esrj-95748	184	11	importance	importance	NOUN
esrj-95748	184	12	median	median	ADJ
esrj-95748	184	13	importance	importance	NOUN
esrj-95748	184	14	min	min	NOUN
esrj-95748	184	15	importance	importance	NOUN
esrj-95748	184	16	max	max	PROPN
esrj-95748	184	17	importance	importance	NOUN
esrj-95748	184	18	slope	slope	NOUN
esrj-95748	184	19	25.65	25.65	NUM
esrj-95748	184	20	25.15	25.15	NUM
esrj-95748	184	21	10.88	10.88	NUM
esrj-95748	184	22	22.24	22.24	NUM
esrj-95748	184	23	land	land	NOUN
esrj-95748	184	24	use	use	NOUN
esrj-95748	184	25	10.65	10.65	NUM
esrj-95748	184	26	10.80	10.80	NUM
esrj-95748	184	27	7.01	7.01	NUM
esrj-95748	184	28	12.34	12.34	NUM
esrj-95748	184	29	lithology	lithology	NOUN
esrj-95748	184	30	10.94	10.94	NUM
esrj-95748	184	31	10.85	10.85	NUM
esrj-95748	184	32	7.20	7.20	NUM
esrj-95748	184	33	14.50	14.50	NUM
esrj-95748	184	34	plan	plan	NOUN
esrj-95748	184	35	curvature	curvature	NOUN
esrj-95748	184	36	7.15	7.15	NUM
esrj-95748	184	37	7.20	7.20	NUM
esrj-95748	184	38	4.85	4.85	NUM
esrj-95748	184	39	9.21	9.21	NUM
esrj-95748	184	40	elevation	elevation	NOUN
esrj-95748	184	41	6.30	6.30	NUM
esrj-95748	184	42	6.80	6.80	NUM
esrj-95748	184	43	4.49	4.49	NUM
esrj-95748	184	44	8.98	8.98	NUM
esrj-95748	184	45	drainage	drainage	NOUN
esrj-95748	184	46	density	density	NOUN
esrj-95748	184	47	5.30	5.30	NUM
esrj-95748	184	48	5.10	5.10	NUM
esrj-95748	184	49	3.45	3.45	NUM
esrj-95748	184	50	7.20	7.20	NUM
esrj-95748	184	51	distance	distance	NOUN
esrj-95748	184	52	from	from	ADP
esrj-95748	184	53	river	river	NOUN
esrj-95748	184	54	5.12	5.12	NUM
esrj-95748	184	55	5.36	5.36	NUM
esrj-95748	184	56	3.05	3.05	NUM
esrj-95748	184	57	7.13	7.13	NUM
esrj-95748	184	58	distance	distance	NOUN
esrj-95748	184	59	from	from	ADP
esrj-95748	184	60	fault	fault	NOUN
esrj-95748	184	61	2.93	2.93	NUM
esrj-95748	184	62	1.56	1.56	NUM
esrj-95748	184	63	0.18	0.18	NUM
esrj-95748	184	64	2.12	2.12	NUM
esrj-95748	184	65	stream	stream	NOUN
esrj-95748	184	66	power	power	NOUN
esrj-95748	184	67	index	index	NOUN
esrj-95748	184	68	2.91	2.91	NUM
esrj-95748	184	69	2.87	2.87	NUM
esrj-95748	184	70	1.87	1.87	NUM
esrj-95748	184	71	4.00	4.00	NUM
esrj-95748	184	72	topographic	topographic	ADJ
esrj-95748	184	73	wetness	wetness	NOUN
esrj-95748	184	74	index	index	NOUN
esrj-95748	184	75	2.19	2.19	NUM
esrj-95748	184	76	2.17	2.17	NUM
esrj-95748	184	77	-1.35	-1.35	NUM
esrj-95748	184	78	3.11	3.11	NUM
esrj-95748	184	79	distance	distance	NOUN
esrj-95748	184	80	from	from	ADP
esrj-95748	184	81	road	road	NOUN
esrj-95748	184	82	2.15	2.15	NUM
esrj-95748	184	83	2.19	2.19	NUM
esrj-95748	184	84	1.24	1.24	NUM
esrj-95748	184	85	3.58	3.58	NUM
esrj-95748	184	86	aspect	aspect	NOUN
esrj-95748	184	87	1.53	1.53	NUM
esrj-95748	184	88	2.89	2.89	NUM
esrj-95748	184	89	1.76	1.76	NUM
esrj-95748	184	90	4.39	4.39	NUM
esrj-95748	184	91	as	as	SCONJ
esrj-95748	184	92	can	can	AUX
esrj-95748	184	93	be	be	AUX
esrj-95748	184	94	seen	see	VERB
esrj-95748	184	95	in	in	ADP
esrj-95748	184	96	the	the	DET
esrj-95748	184	97	research	research	NOUN
esrj-95748	184	98	of	of	ADP
esrj-95748	184	99	garosi	garosi	NOUN
esrj-95748	184	100	et	et	PROPN
esrj-95748	184	101	al	al	PROPN
esrj-95748	184	102	.	.	PROPN
esrj-95748	185	1	(	(	PUNCT
esrj-95748	185	2	2019	2019	NUM
esrj-95748	185	3	)	)	PUNCT
esrj-95748	185	4	,	,	PUNCT
esrj-95748	185	5	amiri	amiri	PROPN
esrj-95748	185	6	et	et	PROPN
esrj-95748	185	7	al	al	PROPN
esrj-95748	185	8	.	.	PROPN
esrj-95748	186	1	(	(	PUNCT
esrj-95748	186	2	2019	2019	NUM
esrj-95748	186	3	)	)	PUNCT
esrj-95748	186	4	,	,	PUNCT
esrj-95748	186	5	and	and	CCONJ
esrj-95748	186	6	rahmati	rahmati	NOUN
esrj-95748	186	7	et	et	PROPN
esrj-95748	186	8	al	al	PROPN
esrj-95748	186	9	.	.	PROPN
esrj-95748	187	1	(	(	PUNCT
esrj-95748	187	2	2017	2017	NUM
esrj-95748	187	3	)	)	PUNCT
esrj-95748	187	4	,	,	PUNCT
esrj-95748	187	5	steep	steep	ADJ
esrj-95748	187	6	slopes	slope	NOUN
esrj-95748	187	7	,	,	PUNCT
esrj-95748	187	8	intensively	intensively	ADV
esrj-95748	187	9	cultivated	cultivate	VERB
esrj-95748	187	10	hillslopes	hillslope	NOUN
esrj-95748	187	11	,	,	PUNCT
esrj-95748	187	12	and	and	CCONJ
esrj-95748	187	13	the	the	DET
esrj-95748	187	14	presence	presence	NOUN
esrj-95748	187	15	of	of	ADP
esrj-95748	187	16	loess	loess	NOUN
esrj-95748	187	17	soils	soil	NOUN
esrj-95748	187	18	significantly	significantly	ADV
esrj-95748	187	19	encourage	encourage	VERB
esrj-95748	187	20	the	the	DET
esrj-95748	187	21	formation	formation	NOUN
esrj-95748	187	22	and	and	CCONJ
esrj-95748	187	23	development	development	NOUN
esrj-95748	187	24	of	of	ADP
esrj-95748	187	25	gullies	gully	NOUN
esrj-95748	187	26	in	in	ADP
esrj-95748	187	27	watershed	watershed	ADJ
esrj-95748	187	28	environments	environment	NOUN
esrj-95748	187	29	.	.	PUNCT
esrj-95748	188	1	however	however	ADV
esrj-95748	188	2	,	,	PUNCT
esrj-95748	188	3	in	in	ADP
esrj-95748	188	4	the	the	DET
esrj-95748	188	5	study	study	NOUN
esrj-95748	188	6	region	region	NOUN
esrj-95748	188	7	,	,	PUNCT
esrj-95748	188	8	the	the	DET
esrj-95748	188	9	occurrence	occurrence	NOUN
esrj-95748	188	10	of	of	ADP
esrj-95748	188	11	gully	gully	ADJ
esrj-95748	188	12	erosion	erosion	NOUN
esrj-95748	188	13	was	be	AUX
esrj-95748	188	14	predominant	predominant	ADJ
esrj-95748	188	15	in	in	ADP
esrj-95748	188	16	the	the	DET
esrj-95748	188	17	slope	slope	NOUN
esrj-95748	188	18	classes	class	NOUN
esrj-95748	188	19	of	of	ADP
esrj-95748	188	20	5	5	NUM
esrj-95748	188	21	°	°	NOUN
esrj-95748	188	22	–10	–10	NOUN
esrj-95748	188	23	°	°	NOUN
esrj-95748	188	24	and	and	CCONJ
esrj-95748	188	25	10	10	NUM
esrj-95748	188	26	°	°	NOUN
esrj-95748	188	27	–20	–20	NOUN
esrj-95748	188	28	°	°	ADJ
esrj-95748	188	29	and	and	CCONJ
esrj-95748	188	30	lower	low	ADJ
esrj-95748	188	31	elevations	elevation	NOUN
esrj-95748	188	32	(	(	PUNCT
esrj-95748	188	33	472	472	NUM
esrj-95748	188	34	-	-	SYM
esrj-95748	188	35	899	899	NUM
esrj-95748	188	36	masl	masl	PROPN
esrj-95748	188	37	)	)	PUNCT
esrj-95748	188	38	,	,	PUNCT
esrj-95748	188	39	illustrating	illustrate	VERB
esrj-95748	188	40	the	the	DET
esrj-95748	188	41	most	most	ADV
esrj-95748	188	42	frequent	frequent	ADJ
esrj-95748	188	43	erosion	erosion	NOUN
esrj-95748	188	44	occurred	occur	VERB
esrj-95748	188	45	in	in	ADP
esrj-95748	188	46	the	the	DET
esrj-95748	188	47	lowland	lowland	NOUN
esrj-95748	188	48	watershed	watershe	VERB
esrj-95748	188	49	positions	position	NOUN
esrj-95748	188	50	.	.	PUNCT
esrj-95748	189	1	almost	almost	ADV
esrj-95748	189	2	no	no	DET
esrj-95748	189	3	gullying	gullying	NOUN
esrj-95748	189	4	occurred	occur	VERB
esrj-95748	189	5	in	in	ADP
esrj-95748	189	6	the	the	DET
esrj-95748	189	7	upper	upper	ADJ
esrj-95748	189	8	positions	position	NOUN
esrj-95748	189	9	and	and	CCONJ
esrj-95748	189	10	slopes	slope	NOUN
esrj-95748	189	11	higher	high	ADJ
esrj-95748	189	12	than	than	ADP
esrj-95748	189	13	20	20	NUM
esrj-95748	189	14	°	°	NOUN
esrj-95748	189	15	.	.	PUNCT
esrj-95748	190	1	the	the	DET
esrj-95748	190	2	predominance	predominance	NOUN
esrj-95748	190	3	of	of	ADP
esrj-95748	190	4	gullied	gully	VERB
esrj-95748	190	5	locations	location	NOUN
esrj-95748	190	6	on	on	ADP
esrj-95748	190	7	the	the	DET
esrj-95748	190	8	concave	concave	ADJ
esrj-95748	190	9	positions	position	NOUN
esrj-95748	190	10	,	,	PUNCT
esrj-95748	190	11	with	with	ADP
esrj-95748	190	12	the	the	DET
esrj-95748	190	13	slope	slope	NOUN
esrj-95748	190	14	of	of	ADP
esrj-95748	190	15	5	5	NUM
esrj-95748	190	16	°	°	NOUN
esrj-95748	190	17	–20	–20	NOUN
esrj-95748	190	18	°	°	NOUN
esrj-95748	190	19	in	in	ADP
esrj-95748	190	20	the	the	DET
esrj-95748	190	21	vicinity	vicinity	NOUN
esrj-95748	190	22	of	of	ADP
esrj-95748	190	23	drainage	drainage	NOUN
esrj-95748	190	24	lines	line	NOUN
esrj-95748	190	25	(	(	PUNCT
esrj-95748	190	26	factor	factor	NOUN
esrj-95748	190	27	of	of	ADP
esrj-95748	190	28	distance	distance	NOUN
esrj-95748	190	29	from	from	ADP
esrj-95748	190	30	the	the	DET
esrj-95748	190	31	river	river	NOUN
esrj-95748	190	32	)	)	PUNCT
esrj-95748	190	33	,	,	PUNCT
esrj-95748	190	34	illustrates	illustrate	VERB
esrj-95748	190	35	a	a	DET
esrj-95748	190	36	preferential	preferential	ADJ
esrj-95748	190	37	topographic	topographic	NOUN
esrj-95748	190	38	zone	zone	NOUN
esrj-95748	190	39	and	and	CCONJ
esrj-95748	190	40	,	,	PUNCT
esrj-95748	190	41	therefore	therefore	ADV
esrj-95748	190	42	,	,	PUNCT
esrj-95748	190	43	a	a	DET
esrj-95748	190	44	terrain	terrain	NOUN
esrj-95748	190	45	threshold	threshold	NOUN
esrj-95748	190	46	for	for	ADP
esrj-95748	190	47	gullying	gullye	VERB
esrj-95748	190	48	.	.	PUNCT
esrj-95748	191	1	furthermore	furthermore	ADV
esrj-95748	191	2	,	,	PUNCT
esrj-95748	191	3	the	the	DET
esrj-95748	191	4	results	result	NOUN
esrj-95748	191	5	of	of	ADP
esrj-95748	191	6	the	the	DET
esrj-95748	191	7	ebf	ebf	NOUN
esrj-95748	191	8	model	model	NOUN
esrj-95748	191	9	showed	show	VERB
esrj-95748	191	10	the	the	DET
esrj-95748	191	11	predominance	predominance	NOUN
esrj-95748	191	12	of	of	ADP
esrj-95748	191	13	gully	gully	ADJ
esrj-95748	191	14	erosion	erosion	NOUN
esrj-95748	191	15	on	on	ADP
esrj-95748	191	16	rangeland	rangeland	NOUN
esrj-95748	191	17	and	and	CCONJ
esrj-95748	191	18	loess	loess	NOUN
esrj-95748	191	19	-	-	PUNCT
esrj-95748	191	20	marl	marl	NOUN
esrj-95748	191	21	deposition	deposition	NOUN
esrj-95748	191	22	(	(	PUNCT
esrj-95748	191	23	figure	figure	NOUN
esrj-95748	191	24	4	4	NUM
esrj-95748	191	25	)	)	PUNCT
esrj-95748	191	26	.	.	PUNCT
esrj-95748	192	1	loess	loess	PROPN
esrj-95748	192	2	,	,	PUNCT
esrj-95748	192	3	due	due	ADP
esrj-95748	192	4	to	to	ADP
esrj-95748	192	5	weak	weak	ADJ
esrj-95748	192	6	structure	structure	NOUN
esrj-95748	192	7	and	and	CCONJ
esrj-95748	192	8	poor	poor	ADJ
esrj-95748	192	9	organic	organic	ADJ
esrj-95748	192	10	matter	matter	NOUN
esrj-95748	192	11	and	and	CCONJ
esrj-95748	192	12	nutrient	nutrient	NOUN
esrj-95748	192	13	content	content	NOUN
esrj-95748	192	14	,	,	PUNCT
esrj-95748	192	15	and	and	CCONJ
esrj-95748	192	16	marl	marl	NOUN
esrj-95748	192	17	,	,	PUNCT
esrj-95748	192	18	with	with	ADP
esrj-95748	192	19	a	a	DET
esrj-95748	192	20	high	high	ADJ
esrj-95748	192	21	plasticity	plasticity	NOUN
esrj-95748	192	22	potential	potential	NOUN
esrj-95748	192	23	,	,	PUNCT
esrj-95748	192	24	significantly	significantly	ADV
esrj-95748	192	25	encourage	encourage	VERB
esrj-95748	192	26	the	the	DET
esrj-95748	192	27	formation	formation	NOUN
esrj-95748	192	28	and	and	CCONJ
esrj-95748	192	29	development	development	NOUN
esrj-95748	192	30	of	of	ADP
esrj-95748	192	31	gullies	gully	NOUN
esrj-95748	192	32	(	(	PUNCT
esrj-95748	192	33	razavi	razavi	NOUN
esrj-95748	192	34	-	-	PUNCT
esrj-95748	192	35	termeh	termeh	NOUN
esrj-95748	192	36	et	et	PROPN
esrj-95748	192	37	al	al	PROPN
esrj-95748	192	38	.	.	PROPN
esrj-95748	192	39	,	,	PUNCT
esrj-95748	192	40	2020	2020	NUM
esrj-95748	192	41	;	;	PUNCT
esrj-95748	192	42	arabameri	arabameri	PROPN
esrj-95748	192	43	et	et	PROPN
esrj-95748	192	44	al	al	PROPN
esrj-95748	192	45	.	.	PROPN
esrj-95748	192	46	,	,	PUNCT
esrj-95748	192	47	2020	2020	NUM
esrj-95748	192	48	;	;	PUNCT
esrj-95748	192	49	garosi	garosi	NOUN
esrj-95748	192	50	et	et	PROPN
esrj-95748	192	51	al	al	PROPN
esrj-95748	192	52	.	.	PROPN
esrj-95748	192	53	,	,	PUNCT
esrj-95748	192	54	2019	2019	NUM
esrj-95748	192	55	)	)	PUNCT
esrj-95748	192	56	.	.	PUNCT
esrj-95748	193	1	the	the	DET
esrj-95748	193	2	highest	high	ADJ
esrj-95748	193	3	distribution	distribution	NOUN
esrj-95748	193	4	of	of	ADP
esrj-95748	193	5	the	the	DET
esrj-95748	193	6	rangelands	rangeland	NOUN
esrj-95748	193	7	and	and	CCONJ
esrj-95748	193	8	loess	loess	NOUN
esrj-95748	193	9	-	-	PUNCT
esrj-95748	193	10	marl	marl	NOUN
esrj-95748	193	11	depositions	deposition	NOUN
esrj-95748	193	12	occurred	occur	VERB
esrj-95748	193	13	on	on	ADP
esrj-95748	193	14	concave	concave	ADJ
esrj-95748	193	15	positions	position	NOUN
esrj-95748	193	16	of	of	ADP
esrj-95748	193	17	the	the	DET
esrj-95748	193	18	study	study	NOUN
esrj-95748	193	19	watershed	watershe	VERB
esrj-95748	193	20	where	where	SCONJ
esrj-95748	193	21	the	the	DET
esrj-95748	193	22	slope	slope	NOUN
esrj-95748	193	23	angle	angle	NOUN
esrj-95748	193	24	tends	tend	VERB
esrj-95748	193	25	to	to	PART
esrj-95748	193	26	be	be	AUX
esrj-95748	193	27	lower	low	ADJ
esrj-95748	193	28	.	.	PUNCT
esrj-95748	194	1	despite	despite	SCONJ
esrj-95748	194	2	some	some	DET
esrj-95748	194	3	studies	study	NOUN
esrj-95748	194	4	showed	show	VERB
esrj-95748	194	5	the	the	DET
esrj-95748	194	6	predominance	predominance	NOUN
esrj-95748	194	7	of	of	ADP
esrj-95748	194	8	gullied	gully	VERB
esrj-95748	194	9	locations	location	NOUN
esrj-95748	194	10	on	on	ADP
esrj-95748	194	11	steep	steep	ADJ
esrj-95748	194	12	slopes	slope	NOUN
esrj-95748	194	13	,	,	PUNCT
esrj-95748	194	14	the	the	DET
esrj-95748	194	15	findings	finding	NOUN
esrj-95748	194	16	of	of	ADP
esrj-95748	194	17	this	this	DET
esrj-95748	194	18	study	study	NOUN
esrj-95748	194	19	illustrated	illustrate	VERB
esrj-95748	194	20	how	how	SCONJ
esrj-95748	194	21	land	land	NOUN
esrj-95748	194	22	use	use	NOUN
esrj-95748	194	23	/	/	SYM
esrj-95748	194	24	cover	cover	NOUN
esrj-95748	194	25	and	and	CCONJ
esrj-95748	194	26	lithological	lithological	ADJ
esrj-95748	194	27	structure	structure	NOUN
esrj-95748	194	28	could	could	AUX
esrj-95748	194	29	stimulate	stimulate	VERB
esrj-95748	194	30	the	the	DET
esrj-95748	194	31	low	low	ADJ
esrj-95748	194	32	topographic	topographic	ADJ
esrj-95748	194	33	thresholds	threshold	NOUN
esrj-95748	194	34	for	for	ADP
esrj-95748	194	35	gully	gully	NOUN
esrj-95748	194	36	development	development	NOUN
esrj-95748	194	37	.	.	PUNCT
esrj-95748	195	1	the	the	DET
esrj-95748	195	2	development	development	NOUN
esrj-95748	195	3	of	of	ADP
esrj-95748	195	4	gullies	gully	NOUN
esrj-95748	195	5	on	on	ADP
esrj-95748	195	6	rangelands	rangeland	NOUN
esrj-95748	195	7	and	and	CCONJ
esrj-95748	195	8	weak	weak	ADJ
esrj-95748	195	9	textured	textured	ADJ
esrj-95748	195	10	soils	soil	NOUN
esrj-95748	195	11	within	within	ADP
esrj-95748	195	12	the	the	DET
esrj-95748	195	13	lower	low	ADJ
esrj-95748	195	14	concave	concave	NOUN
esrj-95748	195	15	positions	position	NOUN
esrj-95748	195	16	of	of	ADP
esrj-95748	195	17	the	the	DET
esrj-95748	195	18	study	study	NOUN
esrj-95748	195	19	region	region	NOUN
esrj-95748	195	20	is	be	AUX
esrj-95748	195	21	consistent	consistent	ADJ
esrj-95748	195	22	with	with	ADP
esrj-95748	195	23	the	the	DET
esrj-95748	195	24	threshold	threshold	NOUN
esrj-95748	195	25	concept	concept	NOUN
esrj-95748	195	26	that	that	SCONJ
esrj-95748	195	27	“	"	PUNCT
esrj-95748	195	28	a	a	DET
esrj-95748	195	29	given	give	VERB
esrj-95748	195	30	soil	soil	NOUN
esrj-95748	195	31	,	,	PUNCT
esrj-95748	195	32	land	land	NOUN
esrj-95748	195	33	use	use	NOUN
esrj-95748	195	34	,	,	PUNCT
esrj-95748	195	35	and	and	CCONJ
esrj-95748	195	36	climate	climate	NOUN
esrj-95748	195	37	within	within	ADP
esrj-95748	195	38	a	a	DET
esrj-95748	195	39	given	give	VERB
esrj-95748	195	40	landscape	landscape	NOUN
esrj-95748	195	41	encourage	encourage	VERB
esrj-95748	195	42	a	a	DET
esrj-95748	195	43	given	give	VERB
esrj-95748	195	44	drainage	drainage	NOUN
esrj-95748	195	45	area	area	NOUN
esrj-95748	195	46	and	and	CCONJ
esrj-95748	195	47	a	a	DET
esrj-95748	195	48	critical	critical	ADJ
esrj-95748	195	49	soil	soil	NOUN
esrj-95748	195	50	surface	surface	NOUN
esrj-95748	195	51	slope	slope	NOUN
esrj-95748	195	52	that	that	PRON
esrj-95748	195	53	are	be	AUX
esrj-95748	195	54	necessary	necessary	ADJ
esrj-95748	195	55	for	for	ADP
esrj-95748	195	56	gully	gully	ADJ
esrj-95748	195	57	incision	incision	NOUN
esrj-95748	195	58	”	"	PUNCT
esrj-95748	195	59	(	(	PUNCT
esrj-95748	195	60	kakembo	kakembo	X
esrj-95748	195	61	et	et	PROPN
esrj-95748	195	62	al	al	PROPN
esrj-95748	195	63	.	.	PROPN
esrj-95748	195	64	,	,	PUNCT
esrj-95748	195	65	2009	2009	NUM
esrj-95748	195	66	;	;	PUNCT
esrj-95748	195	67	poesen	poesen	NOUN
esrj-95748	195	68	et	et	PROPN
esrj-95748	195	69	al	al	PROPN
esrj-95748	195	70	.	.	PROPN
esrj-95748	195	71	,	,	PUNCT
esrj-95748	195	72	2002	2002	NUM
esrj-95748	195	73	)	)	PUNCT
esrj-95748	195	74	.	.	PUNCT
esrj-95748	196	1	considering	consider	VERB
esrj-95748	196	2	given	give	VERB
esrj-95748	196	3	environmental	environmental	ADJ
esrj-95748	196	4	conditions	condition	NOUN
esrj-95748	196	5	,	,	PUNCT
esrj-95748	196	6	when	when	SCONJ
esrj-95748	196	7	a	a	DET
esrj-95748	196	8	certain	certain	ADJ
esrj-95748	196	9	topographic	topographic	ADJ
esrj-95748	196	10	threshold	threshold	NOUN
esrj-95748	196	11	is	be	AUX
esrj-95748	196	12	exceeded	exceed	VERB
esrj-95748	196	13	,	,	PUNCT
esrj-95748	196	14	gully	gully	NOUN
esrj-95748	196	15	heads	head	VERB
esrj-95748	196	16	develop	develop	VERB
esrj-95748	196	17	.	.	PUNCT
esrj-95748	197	1	therefore	therefore	ADV
esrj-95748	197	2	,	,	PUNCT
esrj-95748	197	3	the	the	DET
esrj-95748	197	4	threshold	threshold	NOUN
esrj-95748	197	5	exhibits	exhibit	VERB
esrj-95748	197	6	an	an	DET
esrj-95748	197	7	inverse	inverse	NOUN
esrj-95748	197	8	relationship	relationship	NOUN
esrj-95748	197	9	between	between	ADP
esrj-95748	197	10	surface	surface	NOUN
esrj-95748	197	11	runoff	runoff	NOUN
esrj-95748	197	12	discharge	discharge	NOUN
esrj-95748	197	13	and	and	CCONJ
esrj-95748	197	14	critical	critical	ADJ
esrj-95748	197	15	surface	surface	NOUN
esrj-95748	197	16	slope	slope	NOUN
esrj-95748	197	17	for	for	ADP
esrj-95748	197	18	incision	incision	NOUN
esrj-95748	197	19	.	.	PUNCT
esrj-95748	198	1	assessment	assessment	NOUN
esrj-95748	198	2	of	of	ADP
esrj-95748	198	3	erosion	erosion	NOUN
esrj-95748	198	4	susceptibility	susceptibility	NOUN
esrj-95748	198	5	using	use	VERB
esrj-95748	198	6	svm	svm	PROPN
esrj-95748	198	7	and	and	CCONJ
esrj-95748	198	8	brt	brt	NOUN
esrj-95748	198	9	models	model	NOUN
esrj-95748	198	10	and	and	CCONJ
esrj-95748	198	11	their	their	PRON
esrj-95748	198	12	validation	validation	NOUN
esrj-95748	198	13	to	to	PART
esrj-95748	198	14	predict	predict	VERB
esrj-95748	198	15	gully	gully	ADJ
esrj-95748	198	16	erosion	erosion	NOUN
esrj-95748	198	17	,	,	PUNCT
esrj-95748	198	18	the	the	DET
esrj-95748	198	19	maps	map	NOUN
esrj-95748	198	20	of	of	ADP
esrj-95748	198	21	erosion	erosion	NOUN
esrj-95748	198	22	susceptibility	susceptibility	NOUN
esrj-95748	198	23	were	be	AUX
esrj-95748	198	24	generated	generate	VERB
esrj-95748	198	25	based	base	VERB
esrj-95748	198	26	on	on	ADP
esrj-95748	198	27	the	the	DET
esrj-95748	198	28	results	result	NOUN
esrj-95748	198	29	of	of	ADP
esrj-95748	198	30	the	the	DET
esrj-95748	198	31	svm	svm	PROPN
esrj-95748	198	32	and	and	CCONJ
esrj-95748	198	33	brt	brt	PROPN
esrj-95748	198	34	algorithms	algorithm	NOUN
esrj-95748	198	35	and	and	CCONJ
esrj-95748	198	36	the	the	DET
esrj-95748	198	37	related	related	ADJ
esrj-95748	198	38	conditioning	conditioning	NOUN
esrj-95748	198	39	factors	factor	NOUN
esrj-95748	198	40	.	.	PUNCT
esrj-95748	199	1	these	these	DET
esrj-95748	199	2	maps	map	NOUN
esrj-95748	199	3	exhibited	exhibit	VERB
esrj-95748	199	4	five	five	NUM
esrj-95748	199	5	susceptibility	susceptibility	NOUN
esrj-95748	199	6	degrees	degree	NOUN
esrj-95748	199	7	for	for	ADP
esrj-95748	199	8	gullying	gullye	VERB
esrj-95748	199	9	(	(	PUNCT
esrj-95748	199	10	figure	figure	NOUN
esrj-95748	199	11	5	5	NUM
esrj-95748	199	12	)	)	PUNCT
esrj-95748	199	13	.	.	PUNCT
esrj-95748	200	1	the	the	DET
esrj-95748	200	2	gully	gully	PROPN
esrj-95748	200	3	erosion	erosion	NOUN
esrj-95748	200	4	susceptibility	susceptibility	NOUN
esrj-95748	200	5	map	map	NOUN
esrj-95748	200	6	obtained	obtain	VERB
esrj-95748	200	7	from	from	ADP
esrj-95748	200	8	the	the	DET
esrj-95748	200	9	ln	ln	ADJ
esrj-95748	200	10	-	-	PUNCT
esrj-95748	200	11	svm	svm	ADJ
esrj-95748	200	12	model	model	NOUN
esrj-95748	200	13	illustrated	illustrate	VERB
esrj-95748	200	14	that	that	SCONJ
esrj-95748	200	15	24.51	24.51	NUM
esrj-95748	200	16	%	%	NOUN
esrj-95748	200	17	of	of	ADP
esrj-95748	200	18	the	the	DET
esrj-95748	200	19	watershed	watershed	ADJ
esrj-95748	200	20	area	area	NOUN
esrj-95748	200	21	experienced	experience	VERB
esrj-95748	200	22	very	very	ADV
esrj-95748	200	23	high	high	ADJ
esrj-95748	200	24	susceptibility	susceptibility	NOUN
esrj-95748	200	25	,	,	PUNCT
esrj-95748	200	26	while	while	SCONJ
esrj-95748	200	27	24.49	24.49	NUM
esrj-95748	200	28	%	%	NOUN
esrj-95748	200	29	and	and	CCONJ
esrj-95748	200	30	7.01	7.01	NUM
esrj-95748	200	31	%	%	NOUN
esrj-95748	200	32	of	of	ADP
esrj-95748	200	33	the	the	DET
esrj-95748	200	34	watershed	watershed	ADJ
esrj-95748	200	35	area	area	NOUN
esrj-95748	200	36	exhibited	exhibit	VERB
esrj-95748	200	37	low	low	ADJ
esrj-95748	200	38	and	and	CCONJ
esrj-95748	200	39	very	very	ADV
esrj-95748	200	40	low	low	ADJ
esrj-95748	200	41	susceptibility	susceptibility	NOUN
esrj-95748	200	42	,	,	PUNCT
esrj-95748	200	43	respectively	respectively	ADV
esrj-95748	200	44	(	(	PUNCT
esrj-95748	200	45	figure	figure	NOUN
esrj-95748	200	46	5a	5a	NUM
esrj-95748	200	47	)	)	PUNCT
esrj-95748	200	48	.	.	PUNCT
esrj-95748	201	1	the	the	DET
esrj-95748	201	2	results	result	NOUN
esrj-95748	201	3	of	of	ADP
esrj-95748	201	4	the	the	DET
esrj-95748	201	5	rbf	rbf	PROPN
esrj-95748	201	6	-	-	PUNCT
esrj-95748	201	7	svm	svm	PROPN
esrj-95748	201	8	model	model	NOUN
esrj-95748	201	9	exhibited	exhibit	VERB
esrj-95748	201	10	that	that	SCONJ
esrj-95748	201	11	9.94	9.94	NUM
esrj-95748	201	12	%	%	NOUN
esrj-95748	201	13	,	,	PUNCT
esrj-95748	201	14	41.14	41.14	NUM
esrj-95748	201	15	%	%	NOUN
esrj-95748	201	16	,	,	PUNCT
esrj-95748	201	17	7.15	7.15	NUM
esrj-95748	201	18	%	%	NOUN
esrj-95748	201	19	,	,	PUNCT
esrj-95748	201	20	7.46	7.46	NUM
esrj-95748	201	21	%	%	NOUN
esrj-95748	201	22	,	,	PUNCT
esrj-95748	201	23	and	and	CCONJ
esrj-95748	201	24	34.30	34.30	NUM
esrj-95748	201	25	%	%	NOUN
esrj-95748	201	26	of	of	ADP
esrj-95748	201	27	the	the	DET
esrj-95748	201	28	watershed	watershed	NOUN
esrj-95748	201	29	have	have	VERB
esrj-95748	201	30	very	very	ADV
esrj-95748	201	31	low	low	ADJ
esrj-95748	201	32	,	,	PUNCT
esrj-95748	201	33	low	low	ADJ
esrj-95748	201	34	,	,	PUNCT
esrj-95748	201	35	moderate	moderate	ADJ
esrj-95748	201	36	,	,	PUNCT
esrj-95748	201	37	high	high	ADJ
esrj-95748	201	38	,	,	PUNCT
esrj-95748	201	39	and	and	CCONJ
esrj-95748	201	40	very	very	ADV
esrj-95748	201	41	high	high	ADJ
esrj-95748	201	42	susceptibility	susceptibility	NOUN
esrj-95748	201	43	,	,	PUNCT
esrj-95748	201	44	respectively	respectively	ADV
esrj-95748	201	45	(	(	PUNCT
esrj-95748	201	46	figure	figure	NOUN
esrj-95748	201	47	5b	5b	NUM
esrj-95748	201	48	)	)	PUNCT
esrj-95748	201	49	.	.	PUNCT
esrj-95748	202	1	further	far	ADV
esrj-95748	202	2	,	,	PUNCT
esrj-95748	202	3	based	base	VERB
esrj-95748	202	4	on	on	ADP
esrj-95748	202	5	the	the	DET
esrj-95748	202	6	results	result	NOUN
esrj-95748	202	7	obtained	obtain	VERB
esrj-95748	202	8	from	from	ADP
esrj-95748	202	9	the	the	DET
esrj-95748	202	10	brt	brt	PROPN
esrj-95748	202	11	model	model	NOUN
esrj-95748	202	12	,	,	PUNCT
esrj-95748	202	13	9.64	9.64	NUM
esrj-95748	202	14	%	%	NOUN
esrj-95748	202	15	,	,	PUNCT
esrj-95748	202	16	24.33	24.33	NUM
esrj-95748	202	17	%	%	NOUN
esrj-95748	202	18	,	,	PUNCT
esrj-95748	202	19	34.84	34.84	NUM
esrj-95748	202	20	%	%	NOUN
esrj-95748	202	21	,	,	PUNCT
esrj-95748	202	22	7.44	7.44	NUM
esrj-95748	202	23	%	%	NOUN
esrj-95748	202	24	,	,	PUNCT
esrj-95748	202	25	and	and	CCONJ
esrj-95748	202	26	26.42	26.42	NUM
esrj-95748	202	27	%	%	NOUN
esrj-95748	202	28	of	of	ADP
esrj-95748	202	29	the	the	DET
esrj-95748	202	30	watershed	watershed	NOUN
esrj-95748	202	31	have	have	VERB
esrj-95748	202	32	very	very	ADV
esrj-95748	202	33	low	low	ADJ
esrj-95748	202	34	,	,	PUNCT
esrj-95748	202	35	low	low	ADJ
esrj-95748	202	36	,	,	PUNCT
esrj-95748	202	37	moderate	moderate	ADJ
esrj-95748	202	38	,	,	PUNCT
esrj-95748	202	39	high	high	ADJ
esrj-95748	202	40	,	,	PUNCT
esrj-95748	202	41	and	and	CCONJ
esrj-95748	202	42	very	very	ADV
esrj-95748	202	43	high	high	ADJ
esrj-95748	202	44	susceptibility	susceptibility	NOUN
esrj-95748	202	45	,	,	PUNCT
esrj-95748	202	46	respectively	respectively	ADV
esrj-95748	202	47	(	(	PUNCT
esrj-95748	202	48	figure	figure	NOUN
esrj-95748	202	49	5c	5c	NUM
esrj-95748	202	50	)	)	PUNCT
esrj-95748	202	51	.	.	PUNCT
esrj-95748	203	1	figure	figure	VERB
esrj-95748	203	2	4	4	NUM
esrj-95748	203	3	.	.	PUNCT
esrj-95748	204	1	spatial	spatial	ADJ
esrj-95748	204	2	distributions	distribution	NOUN
esrj-95748	204	3	of	of	ADP
esrj-95748	204	4	gullied	gully	VERB
esrj-95748	204	5	locations	location	NOUN
esrj-95748	204	6	in	in	ADP
esrj-95748	204	7	different	different	ADJ
esrj-95748	204	8	types	type	NOUN
esrj-95748	204	9	of	of	ADP
esrj-95748	204	10	land	land	NOUN
esrj-95748	204	11	use	use	NOUN
esrj-95748	204	12	(	(	PUNCT
esrj-95748	204	13	a	a	NOUN
esrj-95748	204	14	)	)	PUNCT
esrj-95748	204	15	and	and	CCONJ
esrj-95748	204	16	lithological	lithological	ADJ
esrj-95748	204	17	units	unit	NOUN
esrj-95748	204	18	(	(	PUNCT
esrj-95748	204	19	b	b	NOUN
esrj-95748	204	20	)	)	PUNCT
esrj-95748	204	21	430	430	NUM
esrj-95748	204	22	mahdieh	mahdieh	PROPN
esrj-95748	204	23	valipour	valipour	NOUN
esrj-95748	204	24	,	,	PUNCT
esrj-95748	204	25	neda	neda	PROPN
esrj-95748	204	26	mohseni	mohseni	NOUN
esrj-95748	204	27	,	,	PUNCT
esrj-95748	204	28	seyed	seyed	PROPN
esrj-95748	204	29	reza	reza	PROPN
esrj-95748	204	30	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	204	31	figure	figure	NOUN
esrj-95748	204	32	5	5	NUM
esrj-95748	204	33	.	.	PUNCT
esrj-95748	204	34	gully	gully	ADJ
esrj-95748	204	35	erosion	erosion	NOUN
esrj-95748	204	36	susceptibility	susceptibility	NOUN
esrj-95748	204	37	maps	map	NOUN
esrj-95748	204	38	based	base	VERB
esrj-95748	204	39	on	on	ADP
esrj-95748	204	40	ln	ln	ADJ
esrj-95748	204	41	-	-	PUNCT
esrj-95748	204	42	svm	svm	ADJ
esrj-95748	204	43	(	(	PUNCT
esrj-95748	204	44	a	a	NOUN
esrj-95748	204	45	)	)	PUNCT
esrj-95748	204	46	,	,	PUNCT
esrj-95748	204	47	rbf	rbf	PROPN
esrj-95748	204	48	-	-	PUNCT
esrj-95748	204	49	svm	svm	PROPN
esrj-95748	204	50	(	(	PUNCT
esrj-95748	204	51	b	b	NOUN
esrj-95748	204	52	)	)	PUNCT
esrj-95748	204	53	,	,	PUNCT
esrj-95748	204	54	and	and	CCONJ
esrj-95748	204	55	brt	brt	PROPN
esrj-95748	204	56	(	(	PUNCT
esrj-95748	204	57	c	c	NOUN
esrj-95748	204	58	)	)	PUNCT
esrj-95748	204	59	models	model	NOUN
esrj-95748	204	60	the	the	DET
esrj-95748	204	61	results	result	NOUN
esrj-95748	204	62	of	of	ADP
esrj-95748	204	63	the	the	DET
esrj-95748	204	64	two	two	NUM
esrj-95748	204	65	machine	machine	NOUN
esrj-95748	204	66	learning	learn	VERB
esrj-95748	204	67	algorithms	algorithm	NOUN
esrj-95748	204	68	successfully	successfully	ADV
esrj-95748	204	69	assessed	assess	VERB
esrj-95748	204	70	the	the	DET
esrj-95748	204	71	gully	gully	ADJ
esrj-95748	204	72	erosion	erosion	NOUN
esrj-95748	204	73	-	-	PUNCT
esrj-95748	204	74	prone	prone	ADJ
esrj-95748	204	75	areas	area	NOUN
esrj-95748	204	76	within	within	ADP
esrj-95748	204	77	the	the	DET
esrj-95748	204	78	watershed	watershed	NOUN
esrj-95748	204	79	(	(	PUNCT
esrj-95748	204	80	figure	figure	NOUN
esrj-95748	204	81	6	6	NUM
esrj-95748	204	82	)	)	PUNCT
esrj-95748	204	83	.	.	PUNCT
esrj-95748	205	1	the	the	DET
esrj-95748	205	2	validation	validation	NOUN
esrj-95748	205	3	results	result	NOUN
esrj-95748	205	4	(	(	PUNCT
esrj-95748	205	5	auc	auc	NOUN
esrj-95748	205	6	values	value	NOUN
esrj-95748	205	7	)	)	PUNCT
esrj-95748	205	8	for	for	ADP
esrj-95748	205	9	discriminating	discriminate	VERB
esrj-95748	205	10	the	the	DET
esrj-95748	205	11	predictive	predictive	ADJ
esrj-95748	205	12	performance	performance	NOUN
esrj-95748	205	13	of	of	ADP
esrj-95748	205	14	the	the	DET
esrj-95748	205	15	models	model	NOUN
esrj-95748	205	16	illustrated	illustrate	VERB
esrj-95748	205	17	that	that	SCONJ
esrj-95748	205	18	the	the	DET
esrj-95748	205	19	two	two	NUM
esrj-95748	205	20	machine	machine	NOUN
esrj-95748	205	21	learning	learning	NOUN
esrj-95748	205	22	models	model	NOUN
esrj-95748	205	23	were	be	AUX
esrj-95748	205	24	very	very	ADV
esrj-95748	205	25	good	good	ADJ
esrj-95748	205	26	for	for	ADP
esrj-95748	205	27	delimiting	delimit	VERB
esrj-95748	205	28	gully	gully	NOUN
esrj-95748	205	29	-	-	PUNCT
esrj-95748	205	30	prone	prone	ADJ
esrj-95748	205	31	areas	area	NOUN
esrj-95748	205	32	with	with	ADP
esrj-95748	205	33	high	high	ADJ
esrj-95748	205	34	accuracy	accuracy	NOUN
esrj-95748	205	35	.	.	PUNCT
esrj-95748	206	1	the	the	DET
esrj-95748	206	2	brf	brf	NOUN
esrj-95748	206	3	-	-	PUNCT
esrj-95748	206	4	svm	svm	PROPN
esrj-95748	206	5	(	(	PUNCT
esrj-95748	206	6	auc=	auc=	NOUN
esrj-95748	206	7	0.89	0.89	NUM
esrj-95748	206	8	)	)	PUNCT
esrj-95748	206	9	was	be	AUX
esrj-95748	206	10	the	the	DET
esrj-95748	206	11	most	most	ADV
esrj-95748	206	12	robust	robust	ADJ
esrj-95748	206	13	model	model	NOUN
esrj-95748	206	14	,	,	PUNCT
esrj-95748	206	15	illustrating	illustrate	VERB
esrj-95748	206	16	the	the	DET
esrj-95748	206	17	best	good	ADJ
esrj-95748	206	18	prediction	prediction	NOUN
esrj-95748	206	19	rate	rate	NOUN
esrj-95748	206	20	,	,	PUNCT
esrj-95748	206	21	while	while	SCONJ
esrj-95748	206	22	ln	ln	ADJ
esrj-95748	206	23	-	-	PUNCT
esrj-95748	206	24	svm	svm	NOUN
esrj-95748	206	25	did	do	AUX
esrj-95748	206	26	not	not	PART
esrj-95748	206	27	show	show	VERB
esrj-95748	206	28	an	an	DET
esrj-95748	206	29	acceptable	acceptable	ADJ
esrj-95748	206	30	accuracy	accuracy	NOUN
esrj-95748	206	31	(	(	PUNCT
esrj-95748	206	32	auc=	auc=	NOUN
esrj-95748	206	33	0.77	0.77	NUM
esrj-95748	206	34	)	)	PUNCT
esrj-95748	206	35	.	.	PUNCT
esrj-95748	207	1	the	the	DET
esrj-95748	207	2	brt	brt	PROPN
esrj-95748	207	3	model	model	NOUN
esrj-95748	207	4	(	(	PUNCT
esrj-95748	207	5	auc=	auc=	PROPN
esrj-95748	207	6	0.85	0.85	NUM
esrj-95748	207	7	)	)	PUNCT
esrj-95748	207	8	was	be	AUX
esrj-95748	207	9	the	the	DET
esrj-95748	207	10	second	second	ADJ
esrj-95748	207	11	optimal	optimal	ADJ
esrj-95748	207	12	model	model	NOUN
esrj-95748	207	13	for	for	ADP
esrj-95748	207	14	predicting	predict	VERB
esrj-95748	207	15	erosion	erosion	NOUN
esrj-95748	207	16	susceptibility	susceptibility	NOUN
esrj-95748	207	17	in	in	ADP
esrj-95748	207	18	the	the	DET
esrj-95748	207	19	region	region	NOUN
esrj-95748	207	20	.	.	PUNCT
esrj-95748	208	1	furthermore	furthermore	ADV
esrj-95748	208	2	,	,	PUNCT
esrj-95748	208	3	the	the	DET
esrj-95748	208	4	auc	auc	NOUN
esrj-95748	208	5	values	value	NOUN
esrj-95748	208	6	of	of	ADP
esrj-95748	208	7	training	training	NOUN
esrj-95748	208	8	datasets	dataset	NOUN
esrj-95748	208	9	were	be	AUX
esrj-95748	208	10	0.96	0.96	NUM
esrj-95748	208	11	for	for	ADP
esrj-95748	208	12	the	the	DET
esrj-95748	208	13	brf	brf	NOUN
esrj-95748	208	14	-	-	PUNCT
esrj-95748	208	15	svm	svm	ADJ
esrj-95748	208	16	model	model	NOUN
esrj-95748	208	17	and	and	CCONJ
esrj-95748	208	18	0.95	0.95	NUM
esrj-95748	208	19	for	for	ADP
esrj-95748	208	20	the	the	DET
esrj-95748	208	21	brt	brt	PROPN
esrj-95748	208	22	model	model	NOUN
esrj-95748	208	23	.	.	PUNCT
esrj-95748	209	1	further	far	ADV
esrj-95748	209	2	,	,	PUNCT
esrj-95748	209	3	the	the	DET
esrj-95748	209	4	results	result	NOUN
esrj-95748	209	5	of	of	ADP
esrj-95748	209	6	statistical	statistical	ADJ
esrj-95748	209	7	indices	index	NOUN
esrj-95748	209	8	associated	associate	VERB
esrj-95748	209	9	with	with	ADP
esrj-95748	209	10	the	the	DET
esrj-95748	209	11	reliability	reliability	NOUN
esrj-95748	209	12	of	of	ADP
esrj-95748	209	13	the	the	DET
esrj-95748	209	14	models	model	NOUN
esrj-95748	209	15	(	(	PUNCT
esrj-95748	209	16	rmse	rmse	NOUN
esrj-95748	209	17	and	and	CCONJ
esrj-95748	209	18	r2	r2	PROPN
esrj-95748	209	19	)	)	PUNCT
esrj-95748	209	20	illustrated	illustrate	VERB
esrj-95748	209	21	that	that	SCONJ
esrj-95748	209	22	the	the	DET
esrj-95748	209	23	model	model	NOUN
esrj-95748	209	24	of	of	ADP
esrj-95748	209	25	brf	brf	PROPN
esrj-95748	209	26	-	-	PUNCT
esrj-95748	209	27	svm	svm	PROPN
esrj-95748	209	28	,	,	PUNCT
esrj-95748	209	29	followed	follow	VERB
esrj-95748	209	30	by	by	ADP
esrj-95748	209	31	brt	brt	PROPN
esrj-95748	209	32	had	have	VERB
esrj-95748	209	33	the	the	DET
esrj-95748	209	34	lowest	low	ADJ
esrj-95748	209	35	rmse	rmse	NOUN
esrj-95748	209	36	and	and	CCONJ
esrj-95748	209	37	the	the	DET
esrj-95748	209	38	highest	high	ADJ
esrj-95748	209	39	r2	r2	NOUN
esrj-95748	209	40	(	(	PUNCT
esrj-95748	209	41	i.e.	i.e.	X
esrj-95748	209	42	the	the	DET
esrj-95748	209	43	most	most	ADV
esrj-95748	209	44	reliable	reliable	ADJ
esrj-95748	209	45	models	model	NOUN
esrj-95748	209	46	to	to	PART
esrj-95748	209	47	assess	assess	VERB
esrj-95748	209	48	the	the	DET
esrj-95748	209	49	gully	gully	ADJ
esrj-95748	209	50	erosion	erosion	NOUN
esrj-95748	209	51	-	-	PUNCT
esrj-95748	209	52	prone	prone	ADJ
esrj-95748	209	53	areas	area	NOUN
esrj-95748	209	54	)	)	PUNCT
esrj-95748	209	55	compared	compare	VERB
esrj-95748	209	56	with	with	ADP
esrj-95748	209	57	the	the	DET
esrj-95748	209	58	ln	ln	ADJ
esrj-95748	209	59	-	-	PUNCT
esrj-95748	209	60	svm	svm	ADJ
esrj-95748	209	61	(	(	PUNCT
esrj-95748	209	62	table	table	NOUN
esrj-95748	209	63	4	4	NUM
esrj-95748	209	64	)	)	PUNCT
esrj-95748	209	65	.	.	PUNCT
esrj-95748	210	1	figure	figure	VERB
esrj-95748	210	2	6	6	NUM
esrj-95748	210	3	.	.	PUNCT
esrj-95748	211	1	the	the	DET
esrj-95748	211	2	area	area	NOUN
esrj-95748	211	3	under	under	ADP
esrj-95748	211	4	the	the	DET
esrj-95748	211	5	curve	curve	NOUN
esrj-95748	211	6	(	(	PUNCT
esrj-95748	211	7	auc	auc	NOUN
esrj-95748	211	8	)	)	PUNCT
esrj-95748	211	9	based	base	VERB
esrj-95748	211	10	on	on	ADP
esrj-95748	211	11	train	train	NOUN
esrj-95748	211	12	(	(	PUNCT
esrj-95748	211	13	a1	a1	NOUN
esrj-95748	211	14	-	-	PUNCT
esrj-95748	211	15	a3	a3	NOUN
esrj-95748	211	16	)	)	PUNCT
esrj-95748	211	17	and	and	CCONJ
esrj-95748	211	18	validation	validation	NOUN
esrj-95748	211	19	(	(	PUNCT
esrj-95748	211	20	b1	b1	NOUN
esrj-95748	211	21	-	-	PUNCT
esrj-95748	211	22	b3	b3	NOUN
esrj-95748	211	23	)	)	PUNCT
esrj-95748	211	24	datasets	dataset	NOUN
esrj-95748	211	25	for	for	ADP
esrj-95748	211	26	discriminating	discriminate	VERB
esrj-95748	211	27	the	the	DET
esrj-95748	211	28	accuracy	accuracy	NOUN
esrj-95748	211	29	of	of	ADP
esrj-95748	211	30	ln	ln	ADJ
esrj-95748	211	31	-	-	PUNCT
esrj-95748	211	32	svm	svm	ADJ
esrj-95748	211	33	,	,	PUNCT
esrj-95748	211	34	rbf	rbf	PROPN
esrj-95748	211	35	-	-	PUNCT
esrj-95748	211	36	svm	svm	PROPN
esrj-95748	211	37	,	,	PUNCT
esrj-95748	211	38	and	and	CCONJ
esrj-95748	211	39	brt	brt	PROPN
esrj-95748	211	40	models	model	NOUN
esrj-95748	211	41	nonparametric	nonparametric	NOUN
esrj-95748	211	42	methods	method	NOUN
esrj-95748	211	43	such	such	ADJ
esrj-95748	211	44	as	as	ADP
esrj-95748	211	45	svm	svm	PROPN
esrj-95748	211	46	and	and	CCONJ
esrj-95748	211	47	brt	brt	PROPN
esrj-95748	211	48	are	be	AUX
esrj-95748	211	49	appropriate	appropriate	ADJ
esrj-95748	211	50	approaches	approach	NOUN
esrj-95748	211	51	to	to	PART
esrj-95748	211	52	solve	solve	VERB
esrj-95748	211	53	problems	problem	NOUN
esrj-95748	211	54	related	relate	VERB
esrj-95748	211	55	to	to	ADP
esrj-95748	211	56	modeling	modeling	NOUN
esrj-95748	211	57	.	.	PUNCT
esrj-95748	212	1	these	these	DET
esrj-95748	212	2	algorithms	algorithm	NOUN
esrj-95748	212	3	can	can	AUX
esrj-95748	212	4	manage	manage	VERB
esrj-95748	212	5	the	the	DET
esrj-95748	212	6	collinear	collinear	ADJ
esrj-95748	212	7	relationship	relationship	NOUN
esrj-95748	212	8	among	among	ADP
esrj-95748	212	9	conditioning	conditioning	NOUN
esrj-95748	212	10	factors	factor	NOUN
esrj-95748	212	11	.	.	PUNCT
esrj-95748	213	1	other	other	ADJ
esrj-95748	213	2	researchers	researcher	NOUN
esrj-95748	213	3	(	(	PUNCT
esrj-95748	213	4	amiri	amiri	PROPN
esrj-95748	213	5	et	et	PROPN
esrj-95748	213	6	al	al	PROPN
esrj-95748	213	7	.	.	PROPN
esrj-95748	213	8	,	,	PUNCT
esrj-95748	213	9	2019	2019	NUM
esrj-95748	213	10	)	)	PUNCT
esrj-95748	213	11	expressed	express	VERB
esrj-95748	213	12	that	that	SCONJ
esrj-95748	213	13	the	the	DET
esrj-95748	213	14	most	most	ADV
esrj-95748	213	15	important	important	ADJ
esrj-95748	213	16	advantage	advantage	NOUN
esrj-95748	213	17	of	of	ADP
esrj-95748	213	18	the	the	DET
esrj-95748	213	19	brt	brt	PROPN
esrj-95748	213	20	is	be	AUX
esrj-95748	213	21	eliminating	eliminate	VERB
esrj-95748	213	22	variables	variable	NOUN
esrj-95748	213	23	with	with	ADP
esrj-95748	213	24	a	a	DET
esrj-95748	213	25	large	large	ADJ
esrj-95748	213	26	number	number	NOUN
esrj-95748	213	27	of	of	ADP
esrj-95748	213	28	missing	miss	VERB
esrj-95748	213	29	values	value	NOUN
esrj-95748	213	30	compared	compare	VERB
esrj-95748	213	31	with	with	ADP
esrj-95748	213	32	other	other	ADJ
esrj-95748	213	33	models	model	NOUN
esrj-95748	213	34	.	.	PUNCT
esrj-95748	214	1	as	as	SCONJ
esrj-95748	214	2	some	some	DET
esrj-95748	214	3	studies	study	NOUN
esrj-95748	214	4	showed	show	VERB
esrj-95748	214	5	(	(	PUNCT
esrj-95748	214	6	pourghasemi	pourghasemi	NOUN
esrj-95748	214	7	et	et	PROPN
esrj-95748	214	8	al	al	PROPN
esrj-95748	214	9	.	.	PROPN
esrj-95748	214	10	,	,	PUNCT
esrj-95748	214	11	2017	2017	NUM
esrj-95748	214	12	;	;	PUNCT
esrj-95748	214	13	marjanović	marjanović	NOUN
esrj-95748	214	14	et	et	PROPN
esrj-95748	214	15	al	al	PROPN
esrj-95748	214	16	.	.	PROPN
esrj-95748	214	17	,	,	PUNCT
esrj-95748	214	18	2011	2011	NUM
esrj-95748	214	19	)	)	PUNCT
esrj-95748	214	20	,	,	PUNCT
esrj-95748	214	21	the	the	DET
esrj-95748	214	22	improvement	improvement	NOUN
esrj-95748	214	23	of	of	ADP
esrj-95748	214	24	the	the	DET
esrj-95748	214	25	auc	auc	ADJ
esrj-95748	214	26	values	value	NOUN
esrj-95748	214	27	for	for	ADP
esrj-95748	214	28	validation	validation	NOUN
esrj-95748	214	29	and	and	CCONJ
esrj-95748	214	30	train	train	NOUN
esrj-95748	214	31	data	datum	NOUN
esrj-95748	214	32	in	in	ADP
esrj-95748	214	33	different	different	ADJ
esrj-95748	214	34	replicates	replicate	NOUN
esrj-95748	214	35	is	be	AUX
esrj-95748	214	36	the	the	DET
esrj-95748	214	37	most	most	ADV
esrj-95748	214	38	important	important	ADJ
esrj-95748	214	39	advantage	advantage	NOUN
esrj-95748	214	40	of	of	ADP
esrj-95748	214	41	the	the	DET
esrj-95748	214	42	support	support	NOUN
esrj-95748	214	43	vector	vector	NOUN
esrj-95748	214	44	machine	machine	NOUN
esrj-95748	214	45	algorithm	algorithm	NOUN
esrj-95748	214	46	.	.	PUNCT
esrj-95748	215	1	this	this	DET
esrj-95748	215	2	characteristic	characteristic	NOUN
esrj-95748	215	3	caused	cause	VERB
esrj-95748	215	4	this	this	DET
esrj-95748	215	5	model	model	NOUN
esrj-95748	215	6	could	could	AUX
esrj-95748	215	7	handle	handle	VERB
esrj-95748	215	8	complex	complex	ADJ
esrj-95748	215	9	and	and	CCONJ
esrj-95748	215	10	nonlinear	nonlinear	ADJ
esrj-95748	215	11	relationships	relationship	NOUN
esrj-95748	215	12	,	,	PUNCT
esrj-95748	215	13	in	in	ADP
esrj-95748	215	14	comparison	comparison	NOUN
esrj-95748	215	15	with	with	ADP
esrj-95748	215	16	models	model	NOUN
esrj-95748	215	17	such	such	ADJ
esrj-95748	215	18	as	as	ADP
esrj-95748	215	19	the	the	DET
esrj-95748	215	20	artificial	artificial	ADJ
esrj-95748	215	21	neural	neural	ADJ
esrj-95748	215	22	network	network	NOUN
esrj-95748	215	23	.	.	PUNCT
esrj-95748	216	1	the	the	DET
esrj-95748	216	2	findings	finding	NOUN
esrj-95748	216	3	of	of	ADP
esrj-95748	216	4	this	this	DET
esrj-95748	216	5	study	study	NOUN
esrj-95748	216	6	showed	show	VERB
esrj-95748	216	7	that	that	SCONJ
esrj-95748	216	8	the	the	DET
esrj-95748	216	9	models	model	NOUN
esrj-95748	216	10	of	of	ADP
esrj-95748	216	11	svm	svm	PROPN
esrj-95748	216	12	and	and	CCONJ
esrj-95748	216	13	brt	brt	NOUN
esrj-95748	216	14	with	with	ADP
esrj-95748	216	15	considering	consider	VERB
esrj-95748	216	16	the	the	DET
esrj-95748	216	17	interaction	interaction	NOUN
esrj-95748	216	18	between	between	ADP
esrj-95748	216	19	independent	independent	ADJ
esrj-95748	216	20	variables	variable	NOUN
esrj-95748	216	21	could	could	AUX
esrj-95748	216	22	appropriately	appropriately	ADV
esrj-95748	216	23	model	model	VERB
esrj-95748	216	24	gully	gully	ADJ
esrj-95748	216	25	erosion	erosion	NOUN
esrj-95748	216	26	-	-	PUNCT
esrj-95748	216	27	prone	prone	ADJ
esrj-95748	216	28	areas	area	NOUN
esrj-95748	216	29	with	with	ADP
esrj-95748	216	30	a	a	DET
esrj-95748	216	31	high	high	ADJ
esrj-95748	216	32	accuracy	accuracy	NOUN
esrj-95748	216	33	,	,	PUNCT
esrj-95748	216	34	as	as	SCONJ
esrj-95748	216	35	other	other	ADJ
esrj-95748	216	36	studies	study	NOUN
esrj-95748	216	37	reported	report	VERB
esrj-95748	216	38	(	(	PUNCT
esrj-95748	216	39	gayen	gayen	NOUN
esrj-95748	216	40	et	et	PROPN
esrj-95748	216	41	al	al	PROPN
esrj-95748	216	42	.	.	PROPN
esrj-95748	216	43	2019	2019	NUM
esrj-95748	216	44	;	;	PUNCT
esrj-95748	216	45	rahmati	rahmati	NOUN
esrj-95748	216	46	et	et	PROPN
esrj-95748	216	47	al	al	PROPN
esrj-95748	216	48	.	.	PROPN
esrj-95748	216	49	,	,	PUNCT
esrj-95748	216	50	2017	2017	NUM
esrj-95748	216	51	;	;	PUNCT
esrj-95748	216	52	elith	elith	ADP
esrj-95748	216	53	et	et	PROPN
esrj-95748	216	54	al	al	PROPN
esrj-95748	216	55	.	.	PROPN
esrj-95748	216	56	,	,	PUNCT
esrj-95748	216	57	2008	2008	NUM
esrj-95748	216	58	)	)	PUNCT
esrj-95748	216	59	.	.	PUNCT
esrj-95748	217	1	overall	overall	ADV
esrj-95748	217	2	,	,	PUNCT
esrj-95748	217	3	the	the	DET
esrj-95748	217	4	gully	gully	NOUN
esrj-95748	217	5	erosion	erosion	NOUN
esrj-95748	217	6	susceptibility	susceptibility	NOUN
esrj-95748	217	7	maps	map	NOUN
esrj-95748	217	8	could	could	AUX
esrj-95748	217	9	provide	provide	VERB
esrj-95748	217	10	an	an	DET
esrj-95748	217	11	appropriate	appropriate	ADJ
esrj-95748	217	12	strategy	strategy	NOUN
esrj-95748	217	13	for	for	ADP
esrj-95748	217	14	geo	geo	PROPN
esrj-95748	217	15	-	-	PUNCT
esrj-95748	217	16	conservation	conservation	NOUN
esrj-95748	217	17	and	and	CCONJ
esrj-95748	217	18	restoration	restoration	NOUN
esrj-95748	217	19	efforts	effort	NOUN
esrj-95748	217	20	in	in	ADP
esrj-95748	217	21	gully	gully	ADJ
esrj-95748	217	22	erosion	erosion	NOUN
esrj-95748	217	23	-	-	PUNCT
esrj-95748	217	24	prone	prone	ADJ
esrj-95748	217	25	areas	area	NOUN
esrj-95748	217	26	within	within	ADP
esrj-95748	217	27	the	the	DET
esrj-95748	217	28	study	study	NOUN
esrj-95748	217	29	watershed	watershe	VERB
esrj-95748	217	30	.	.	PUNCT
esrj-95748	218	1	table	table	NOUN
esrj-95748	218	2	4	4	NUM
esrj-95748	218	3	.	.	PUNCT
esrj-95748	219	1	reliability	reliability	NOUN
esrj-95748	219	2	of	of	ADP
esrj-95748	219	3	model	model	NOUN
esrj-95748	219	4	accuracy	accuracy	NOUN
esrj-95748	219	5	based	base	VERB
esrj-95748	219	6	on	on	ADP
esrj-95748	219	7	the	the	DET
esrj-95748	219	8	coefficient	coefficient	NOUN
esrj-95748	219	9	of	of	ADP
esrj-95748	219	10	determination	determination	NOUN
esrj-95748	219	11	(	(	PUNCT
esrj-95748	219	12	r2	r2	PROPN
esrj-95748	219	13	)	)	PUNCT
esrj-95748	219	14	and	and	CCONJ
esrj-95748	219	15	root	root	NOUN
esrj-95748	219	16	mean	mean	NOUN
esrj-95748	219	17	square	square	ADJ
esrj-95748	219	18	error	error	NOUN
esrj-95748	219	19	(	(	PUNCT
esrj-95748	219	20	rmse	rmse	NOUN
esrj-95748	219	21	)	)	PUNCT
esrj-95748	219	22	model	model	NOUN
esrj-95748	219	23	train	train	NOUN
esrj-95748	219	24	data	datum	NOUN
esrj-95748	219	25	(	(	PUNCT
esrj-95748	219	26	70	70	NUM
esrj-95748	219	27	%	%	NOUN
esrj-95748	219	28	)	)	PUNCT
esrj-95748	219	29	validation	validation	NOUN
esrj-95748	219	30	data	datum	NOUN
esrj-95748	219	31	(	(	PUNCT
esrj-95748	219	32	30	30	NUM
esrj-95748	219	33	%	%	NOUN
esrj-95748	219	34	)	)	PUNCT
esrj-95748	219	35	r2	r2	PROPN
esrj-95748	219	36	rmse	rmse	PROPN
esrj-95748	219	37	r2	r2	PROPN
esrj-95748	219	38	rmse	rmse	PROPN
esrj-95748	219	39	svm	svm	PROPN
esrj-95748	219	40	(	(	PUNCT
esrj-95748	219	41	linear	linear	PROPN
esrj-95748	219	42	kernel	kernel	PROPN
esrj-95748	219	43	)	)	PUNCT
esrj-95748	219	44	0.34	0.34	NUM
esrj-95748	219	45	0.43	0.43	NUM
esrj-95748	219	46	0.13	0.13	NUM
esrj-95748	219	47	0.46	0.46	NUM
esrj-95748	219	48	svm	svm	NOUN
esrj-95748	219	49	(	(	PUNCT
esrj-95748	219	50	radial	radial	ADJ
esrj-95748	219	51	basis	basis	NOUN
esrj-95748	219	52	function	function	NOUN
esrj-95748	219	53	)	)	PUNCT
esrj-95748	220	1	0.91	0.91	NUM
esrj-95748	220	2	0.23	0.23	NUM
esrj-95748	220	3	0.76	0.76	NUM
esrj-95748	220	4	0.32	0.32	NUM
esrj-95748	220	5	brt	brt	PROPN
esrj-95748	220	6	0.83	0.83	NUM
esrj-95748	220	7	0.29	0.29	NUM
esrj-95748	220	8	0.64	0.64	NUM
esrj-95748	220	9	0.38	0.38	NUM
esrj-95748	220	10	431factors	431factors	PROPN
esrj-95748	220	11	affecting	affect	VERB
esrj-95748	220	12	topographic	topographic	ADJ
esrj-95748	220	13	thresholds	threshold	NOUN
esrj-95748	220	14	in	in	ADP
esrj-95748	220	15	gully	gully	ADJ
esrj-95748	220	16	erosion	erosion	NOUN
esrj-95748	220	17	occurrence	occurrence	NOUN
esrj-95748	220	18	and	and	CCONJ
esrj-95748	220	19	its	its	PRON
esrj-95748	220	20	management	management	NOUN
esrj-95748	220	21	using	use	VERB
esrj-95748	220	22	predictive	predictive	ADJ
esrj-95748	220	23	machine	machine	NOUN
esrj-95748	220	24	learning	learning	NOUN
esrj-95748	220	25	models	model	VERB
esrj-95748	220	26	the	the	DET
esrj-95748	220	27	interactions	interaction	NOUN
esrj-95748	220	28	among	among	ADP
esrj-95748	220	29	various	various	ADJ
esrj-95748	220	30	variables	variable	NOUN
esrj-95748	220	31	such	such	ADJ
esrj-95748	220	32	as	as	ADP
esrj-95748	220	33	terrain	terrain	NOUN
esrj-95748	220	34	indices	index	NOUN
esrj-95748	220	35	,	,	PUNCT
esrj-95748	220	36	lithological	lithological	ADJ
esrj-95748	220	37	characteristics	characteristic	NOUN
esrj-95748	220	38	,	,	PUNCT
esrj-95748	220	39	and	and	CCONJ
esrj-95748	220	40	land	land	NOUN
esrj-95748	220	41	use	use	NOUN
esrj-95748	220	42	/	/	SYM
esrj-95748	220	43	cover	cover	NOUN
esrj-95748	220	44	changes	change	NOUN
esrj-95748	220	45	affect	affect	VERB
esrj-95748	220	46	linear	linear	ADJ
esrj-95748	220	47	erosion	erosion	NOUN
esrj-95748	220	48	development	development	NOUN
esrj-95748	220	49	as	as	ADP
esrj-95748	220	50	rilling	rille	VERB
esrj-95748	220	51	and	and	CCONJ
esrj-95748	220	52	gullying	gullying	NOUN
esrj-95748	220	53	,	,	PUNCT
esrj-95748	220	54	which	which	PRON
esrj-95748	220	55	irreversibly	irreversibly	ADV
esrj-95748	220	56	threaten	threaten	VERB
esrj-95748	220	57	the	the	DET
esrj-95748	220	58	health	health	NOUN
esrj-95748	220	59	and	and	CCONJ
esrj-95748	220	60	resilience	resilience	NOUN
esrj-95748	220	61	of	of	ADP
esrj-95748	220	62	soil	soil	NOUN
esrj-95748	220	63	systems	system	NOUN
esrj-95748	220	64	.	.	PUNCT
esrj-95748	221	1	this	this	DET
esrj-95748	221	2	study	study	NOUN
esrj-95748	221	3	shows	show	VERB
esrj-95748	221	4	the	the	DET
esrj-95748	221	5	results	result	NOUN
esrj-95748	221	6	obtained	obtain	VERB
esrj-95748	221	7	by	by	ADP
esrj-95748	221	8	applying	apply	VERB
esrj-95748	221	9	two	two	NUM
esrj-95748	221	10	machine	machine	NOUN
esrj-95748	221	11	learning	learning	NOUN
esrj-95748	221	12	methods	method	NOUN
esrj-95748	221	13	for	for	ADP
esrj-95748	221	14	predicting	predict	VERB
esrj-95748	221	15	the	the	DET
esrj-95748	221	16	gully	gully	ADJ
esrj-95748	221	17	head	head	NOUN
esrj-95748	221	18	cut	cut	VERB
esrj-95748	221	19	susceptibility	susceptibility	NOUN
esrj-95748	221	20	in	in	ADP
esrj-95748	221	21	northern	northern	ADJ
esrj-95748	221	22	iran	iran	PROPN
esrj-95748	221	23	,	,	PUNCT
esrj-95748	221	24	as	as	ADP
esrj-95748	221	25	the	the	DET
esrj-95748	221	26	second	second	ADJ
esrj-95748	221	27	country	country	NOUN
esrj-95748	221	28	in	in	ADP
esrj-95748	221	29	the	the	DET
esrj-95748	221	30	world	world	NOUN
esrj-95748	221	31	in	in	ADP
esrj-95748	221	32	terms	term	NOUN
esrj-95748	221	33	of	of	ADP
esrj-95748	221	34	soil	soil	NOUN
esrj-95748	221	35	erosion	erosion	NOUN
esrj-95748	221	36	.	.	PUNCT
esrj-95748	222	1	mean	mean	VERB
esrj-95748	222	2	annual	annual	ADJ
esrj-95748	222	3	soil	soil	NOUN
esrj-95748	222	4	losses	loss	NOUN
esrj-95748	222	5	caused	cause	VERB
esrj-95748	222	6	by	by	ADP
esrj-95748	222	7	the	the	DET
esrj-95748	222	8	gully	gully	ADJ
esrj-95748	222	9	erosion	erosion	NOUN
esrj-95748	222	10	in	in	ADP
esrj-95748	222	11	this	this	DET
esrj-95748	222	12	country	country	NOUN
esrj-95748	222	13	estimate	estimate	VERB
esrj-95748	222	14	approximately	approximately	ADV
esrj-95748	222	15	2.5	2.5	NUM
esrj-95748	222	16	billion	billion	NUM
esrj-95748	222	17	tons	ton	NOUN
esrj-95748	222	18	.	.	PUNCT
esrj-95748	223	1	these	these	DET
esrj-95748	223	2	models	model	NOUN
esrj-95748	223	3	can	can	AUX
esrj-95748	223	4	be	be	AUX
esrj-95748	223	5	appropriate	appropriate	ADJ
esrj-95748	223	6	tools	tool	NOUN
esrj-95748	223	7	to	to	PART
esrj-95748	223	8	understand	understand	VERB
esrj-95748	223	9	mechanisms	mechanism	NOUN
esrj-95748	223	10	controlling	control	VERB
esrj-95748	223	11	gully	gully	ADJ
esrj-95748	223	12	erosion	erosion	NOUN
esrj-95748	223	13	and	and	CCONJ
esrj-95748	223	14	,	,	PUNCT
esrj-95748	223	15	therefore	therefore	ADV
esrj-95748	223	16	,	,	PUNCT
esrj-95748	223	17	can	can	AUX
esrj-95748	223	18	help	help	VERB
esrj-95748	223	19	to	to	PART
esrj-95748	223	20	implement	implement	VERB
esrj-95748	223	21	geo	geo	PROPN
esrj-95748	223	22	-	-	PUNCT
esrj-95748	223	23	conservation	conservation	NOUN
esrj-95748	223	24	and	and	CCONJ
esrj-95748	223	25	management	management	NOUN
esrj-95748	223	26	efforts	effort	NOUN
esrj-95748	223	27	for	for	ADP
esrj-95748	223	28	mitigating	mitigate	VERB
esrj-95748	223	29	disasters	disaster	NOUN
esrj-95748	223	30	associated	associate	VERB
esrj-95748	223	31	with	with	ADP
esrj-95748	223	32	this	this	DET
esrj-95748	223	33	hazard	hazard	NOUN
esrj-95748	223	34	.	.	PUNCT
esrj-95748	224	1	conclusions	conclusion	NOUN
esrj-95748	224	2	soil	soil	NOUN
esrj-95748	224	3	degradation	degradation	NOUN
esrj-95748	224	4	induced	induce	VERB
esrj-95748	224	5	by	by	ADP
esrj-95748	224	6	gully	gully	ADJ
esrj-95748	224	7	erosion	erosion	NOUN
esrj-95748	224	8	is	be	AUX
esrj-95748	224	9	the	the	DET
esrj-95748	224	10	most	most	ADV
esrj-95748	224	11	critical	critical	ADJ
esrj-95748	224	12	challenge	challenge	NOUN
esrj-95748	224	13	faced	face	VERB
esrj-95748	224	14	by	by	ADP
esrj-95748	224	15	many	many	ADJ
esrj-95748	224	16	of	of	ADP
esrj-95748	224	17	the	the	DET
esrj-95748	224	18	world	world	NOUN
esrj-95748	224	19	’s	’s	PART
esrj-95748	224	20	dryland	dryland	NOUN
esrj-95748	224	21	regions	region	NOUN
esrj-95748	224	22	.	.	PUNCT
esrj-95748	225	1	although	although	SCONJ
esrj-95748	225	2	this	this	DET
esrj-95748	225	3	hazard	hazard	NOUN
esrj-95748	225	4	occurs	occur	VERB
esrj-95748	225	5	on	on	ADP
esrj-95748	225	6	a	a	DET
esrj-95748	225	7	small	small	ADJ
esrj-95748	225	8	scale	scale	NOUN
esrj-95748	225	9	,	,	PUNCT
esrj-95748	225	10	its	its	PRON
esrj-95748	225	11	consequences	consequence	NOUN
esrj-95748	225	12	will	will	AUX
esrj-95748	225	13	have	have	VERB
esrj-95748	225	14	a	a	DET
esrj-95748	225	15	substantial	substantial	ADJ
esrj-95748	225	16	impact	impact	NOUN
esrj-95748	225	17	on	on	ADP
esrj-95748	225	18	global	global	ADJ
esrj-95748	225	19	scales	scale	NOUN
esrj-95748	225	20	,	,	PUNCT
esrj-95748	225	21	for	for	ADP
esrj-95748	225	22	example	example	NOUN
esrj-95748	225	23	,	,	PUNCT
esrj-95748	225	24	the	the	DET
esrj-95748	225	25	impacts	impact	NOUN
esrj-95748	225	26	of	of	ADP
esrj-95748	225	27	gully	gully	ADJ
esrj-95748	225	28	erosion	erosion	NOUN
esrj-95748	225	29	on	on	ADP
esrj-95748	225	30	the	the	DET
esrj-95748	225	31	degradation	degradation	NOUN
esrj-95748	225	32	of	of	ADP
esrj-95748	225	33	a	a	DET
esrj-95748	225	34	large	large	ADJ
esrj-95748	225	35	amount	amount	NOUN
esrj-95748	225	36	of	of	ADP
esrj-95748	225	37	oc	oc	NOUN
esrj-95748	225	38	-	-	ADJ
esrj-95748	225	39	rich	rich	ADJ
esrj-95748	225	40	topsoil	topsoil	NOUN
esrj-95748	225	41	that	that	PRON
esrj-95748	225	42	is	be	AUX
esrj-95748	225	43	combined	combine	VERB
esrj-95748	225	44	with	with	ADP
esrj-95748	225	45	deeper	deep	ADJ
esrj-95748	225	46	horizons	horizon	NOUN
esrj-95748	225	47	poor	poor	ADJ
esrj-95748	225	48	in	in	ADP
esrj-95748	225	49	oc	oc	PROPN
esrj-95748	225	50	.	.	PUNCT
esrj-95748	226	1	this	this	DET
esrj-95748	226	2	event	event	NOUN
esrj-95748	226	3	stimulates	stimulate	VERB
esrj-95748	226	4	carbon	carbon	NOUN
esrj-95748	226	5	mineralization	mineralization	NOUN
esrj-95748	226	6	and	and	CCONJ
esrj-95748	226	7	,	,	PUNCT
esrj-95748	226	8	subsequently	subsequently	ADV
esrj-95748	226	9	,	,	PUNCT
esrj-95748	226	10	affects	affect	VERB
esrj-95748	226	11	the	the	DET
esrj-95748	226	12	exchange	exchange	NOUN
esrj-95748	226	13	of	of	ADP
esrj-95748	226	14	carbon	carbon	NOUN
esrj-95748	226	15	between	between	ADP
esrj-95748	226	16	the	the	DET
esrj-95748	226	17	atmosphere	atmosphere	NOUN
esrj-95748	226	18	and	and	CCONJ
esrj-95748	226	19	the	the	DET
esrj-95748	226	20	pedosphere	pedosphere	NOUN
esrj-95748	226	21	and	and	CCONJ
esrj-95748	226	22	associated	associated	ADJ
esrj-95748	226	23	instability	instability	NOUN
esrj-95748	226	24	in	in	ADP
esrj-95748	226	25	the	the	DET
esrj-95748	226	26	carbon	carbon	NOUN
esrj-95748	226	27	dioxide	dioxide	NOUN
esrj-95748	226	28	concentrations	concentration	NOUN
esrj-95748	226	29	of	of	ADP
esrj-95748	226	30	the	the	DET
esrj-95748	226	31	atmosphere	atmosphere	NOUN
esrj-95748	226	32	.	.	PUNCT
esrj-95748	227	1	therefore	therefore	ADV
esrj-95748	227	2	,	,	PUNCT
esrj-95748	227	3	to	to	PART
esrj-95748	227	4	mitigate	mitigate	VERB
esrj-95748	227	5	this	this	DET
esrj-95748	227	6	hazard	hazard	NOUN
esrj-95748	227	7	and	and	CCONJ
esrj-95748	227	8	the	the	DET
esrj-95748	227	9	related	relate	VERB
esrj-95748	227	10	environmental	environmental	ADJ
esrj-95748	227	11	problems	problem	NOUN
esrj-95748	227	12	,	,	PUNCT
esrj-95748	227	13	it	it	PRON
esrj-95748	227	14	is	be	AUX
esrj-95748	227	15	necessary	necessary	ADJ
esrj-95748	227	16	to	to	PART
esrj-95748	227	17	understand	understand	VERB
esrj-95748	227	18	the	the	DET
esrj-95748	227	19	mechanisms	mechanism	NOUN
esrj-95748	227	20	controlling	control	VERB
esrj-95748	227	21	gully	gully	ADJ
esrj-95748	227	22	erosion	erosion	NOUN
esrj-95748	227	23	.	.	PUNCT
esrj-95748	228	1	the	the	DET
esrj-95748	228	2	results	result	NOUN
esrj-95748	228	3	of	of	ADP
esrj-95748	228	4	this	this	DET
esrj-95748	228	5	study	study	NOUN
esrj-95748	228	6	showed	show	VERB
esrj-95748	228	7	the	the	DET
esrj-95748	228	8	efficiency	efficiency	NOUN
esrj-95748	228	9	of	of	ADP
esrj-95748	228	10	two	two	NUM
esrj-95748	228	11	machine	machine	NOUN
esrj-95748	228	12	learning	learn	VERB
esrj-95748	228	13	algorithms	algorithm	NOUN
esrj-95748	228	14	,	,	PUNCT
esrj-95748	228	15	including	include	VERB
esrj-95748	228	16	brt	brt	PROPN
esrj-95748	228	17	and	and	CCONJ
esrj-95748	228	18	svm	svm	PROPN
esrj-95748	228	19	,	,	PUNCT
esrj-95748	228	20	in	in	ADP
esrj-95748	228	21	the	the	DET
esrj-95748	228	22	prediction	prediction	NOUN
esrj-95748	228	23	of	of	ADP
esrj-95748	228	24	erosion	erosion	NOUN
esrj-95748	228	25	susceptibility	susceptibility	NOUN
esrj-95748	228	26	in	in	ADP
esrj-95748	228	27	northern	northern	ADJ
esrj-95748	228	28	iran	iran	PROPN
esrj-95748	228	29	.	.	PUNCT
esrj-95748	229	1	based	base	VERB
esrj-95748	229	2	on	on	ADP
esrj-95748	229	3	the	the	DET
esrj-95748	229	4	results	result	NOUN
esrj-95748	229	5	of	of	ADP
esrj-95748	229	6	the	the	DET
esrj-95748	229	7	boruta	boruta	NOUN
esrj-95748	229	8	algorithm	algorithm	NOUN
esrj-95748	229	9	,	,	PUNCT
esrj-95748	229	10	slope	slope	NOUN
esrj-95748	229	11	gradient	gradient	NOUN
esrj-95748	229	12	,	,	PUNCT
esrj-95748	229	13	land	land	NOUN
esrj-95748	229	14	use	use	NOUN
esrj-95748	229	15	,	,	PUNCT
esrj-95748	229	16	lithology	lithology	NOUN
esrj-95748	229	17	,	,	PUNCT
esrj-95748	229	18	distance	distance	NOUN
esrj-95748	229	19	from	from	ADP
esrj-95748	229	20	river	river	NOUN
esrj-95748	229	21	,	,	PUNCT
esrj-95748	229	22	elevation	elevation	NOUN
esrj-95748	229	23	,	,	PUNCT
esrj-95748	229	24	river	river	NOUN
esrj-95748	229	25	density	density	NOUN
esrj-95748	229	26	,	,	PUNCT
esrj-95748	229	27	distance	distance	NOUN
esrj-95748	229	28	from	from	ADP
esrj-95748	229	29	fault	fault	NOUN
esrj-95748	229	30	,	,	PUNCT
esrj-95748	229	31	plan	plan	NOUN
esrj-95748	229	32	curvature	curvature	NOUN
esrj-95748	229	33	,	,	PUNCT
esrj-95748	229	34	and	and	CCONJ
esrj-95748	229	35	spi	spi	NOUN
esrj-95748	229	36	were	be	AUX
esrj-95748	229	37	the	the	DET
esrj-95748	229	38	most	most	ADV
esrj-95748	229	39	effective	effective	ADJ
esrj-95748	229	40	factors	factor	NOUN
esrj-95748	229	41	that	that	PRON
esrj-95748	229	42	controlled	control	VERB
esrj-95748	229	43	the	the	DET
esrj-95748	229	44	occurrence	occurrence	NOUN
esrj-95748	229	45	of	of	ADP
esrj-95748	229	46	gully	gully	ADJ
esrj-95748	229	47	erosion	erosion	NOUN
esrj-95748	229	48	in	in	ADP
esrj-95748	229	49	the	the	DET
esrj-95748	229	50	study	study	NOUN
esrj-95748	229	51	region	region	NOUN
esrj-95748	229	52	.	.	PUNCT
esrj-95748	230	1	further	far	ADV
esrj-95748	230	2	,	,	PUNCT
esrj-95748	230	3	the	the	DET
esrj-95748	230	4	results	result	NOUN
esrj-95748	230	5	of	of	ADP
esrj-95748	230	6	the	the	DET
esrj-95748	230	7	ebf	ebf	NOUN
esrj-95748	230	8	model	model	NOUN
esrj-95748	230	9	showed	show	VERB
esrj-95748	230	10	the	the	DET
esrj-95748	230	11	spatial	spatial	ADJ
esrj-95748	230	12	relationship	relationship	NOUN
esrj-95748	230	13	among	among	ADP
esrj-95748	230	14	causative	causative	ADJ
esrj-95748	230	15	variables	variable	NOUN
esrj-95748	230	16	and	and	CCONJ
esrj-95748	230	17	gullied	gullied	ADJ
esrj-95748	230	18	locations	location	NOUN
esrj-95748	230	19	.	.	PUNCT
esrj-95748	231	1	based	base	VERB
esrj-95748	231	2	on	on	ADP
esrj-95748	231	3	these	these	DET
esrj-95748	231	4	findings	finding	NOUN
esrj-95748	231	5	,	,	PUNCT
esrj-95748	231	6	topographic	topographic	PROPN
esrj-95748	231	7	thresholds	threshold	NOUN
esrj-95748	231	8	for	for	ADP
esrj-95748	231	9	gully	gully	NOUN
esrj-95748	231	10	erosion	erosion	NOUN
esrj-95748	231	11	tended	tend	VERB
esrj-95748	231	12	to	to	PART
esrj-95748	231	13	be	be	AUX
esrj-95748	231	14	lower	low	ADJ
esrj-95748	231	15	on	on	ADP
esrj-95748	231	16	rangeland	rangeland	NOUN
esrj-95748	231	17	and	and	CCONJ
esrj-95748	231	18	weak	weak	ADJ
esrj-95748	231	19	textured	textured	ADJ
esrj-95748	231	20	soils	soil	NOUN
esrj-95748	231	21	,	,	PUNCT
esrj-95748	231	22	such	such	ADJ
esrj-95748	231	23	as	as	ADP
esrj-95748	231	24	loess	loess	NOUN
esrj-95748	231	25	and	and	CCONJ
esrj-95748	231	26	marl	marl	NOUN
esrj-95748	231	27	.	.	PUNCT
esrj-95748	232	1	furthermore	furthermore	ADV
esrj-95748	232	2	,	,	PUNCT
esrj-95748	232	3	the	the	DET
esrj-95748	232	4	spatial	spatial	ADJ
esrj-95748	232	5	correlation	correlation	NOUN
esrj-95748	232	6	of	of	ADP
esrj-95748	232	7	gullying	gullye	VERB
esrj-95748	232	8	with	with	ADP
esrj-95748	232	9	rangeland	rangeland	NOUN
esrj-95748	232	10	and	and	CCONJ
esrj-95748	232	11	weak	weak	ADJ
esrj-95748	232	12	textured	textured	ADJ
esrj-95748	232	13	soils	soil	NOUN
esrj-95748	232	14	within	within	ADP
esrj-95748	232	15	concave	concave	ADJ
esrj-95748	232	16	positions	position	NOUN
esrj-95748	232	17	illustrated	illustrate	VERB
esrj-95748	232	18	that	that	SCONJ
esrj-95748	232	19	the	the	DET
esrj-95748	232	20	interactions	interaction	NOUN
esrj-95748	232	21	among	among	ADP
esrj-95748	232	22	soil	soil	NOUN
esrj-95748	232	23	characteristics	characteristic	NOUN
esrj-95748	232	24	,	,	PUNCT
esrj-95748	232	25	topography	topography	NOUN
esrj-95748	232	26	,	,	PUNCT
esrj-95748	232	27	and	and	CCONJ
esrj-95748	232	28	land	land	NOUN
esrj-95748	232	29	use	use	NOUN
esrj-95748	232	30	could	could	AUX
esrj-95748	232	31	stimulate	stimulate	VERB
esrj-95748	232	32	a	a	DET
esrj-95748	232	33	low	low	ADJ
esrj-95748	232	34	topographic	topographic	ADJ
esrj-95748	232	35	threshold	threshold	NOUN
esrj-95748	232	36	for	for	ADP
esrj-95748	232	37	gullying	gullye	VERB
esrj-95748	232	38	.	.	PUNCT
esrj-95748	233	1	the	the	DET
esrj-95748	233	2	validation	validation	NOUN
esrj-95748	233	3	results	result	NOUN
esrj-95748	233	4	related	relate	VERB
esrj-95748	233	5	to	to	ADP
esrj-95748	233	6	the	the	DET
esrj-95748	233	7	statistical	statistical	ADJ
esrj-95748	233	8	indices	index	NOUN
esrj-95748	233	9	of	of	ADP
esrj-95748	233	10	the	the	DET
esrj-95748	233	11	reliability	reliability	NOUN
esrj-95748	233	12	and	and	CCONJ
esrj-95748	233	13	discrimination	discrimination	NOUN
esrj-95748	233	14	accuracy	accuracy	NOUN
esrj-95748	233	15	of	of	ADP
esrj-95748	233	16	the	the	DET
esrj-95748	233	17	models	model	NOUN
esrj-95748	233	18	showed	show	VERB
esrj-95748	233	19	that	that	SCONJ
esrj-95748	233	20	the	the	DET
esrj-95748	233	21	two	two	NUM
esrj-95748	233	22	machine	machine	NOUN
esrj-95748	233	23	learning	learning	NOUN
esrj-95748	233	24	models	model	NOUN
esrj-95748	233	25	were	be	AUX
esrj-95748	233	26	very	very	ADV
esrj-95748	233	27	good	good	ADJ
esrj-95748	233	28	for	for	ADP
esrj-95748	233	29	demarcating	demarcate	VERB
esrj-95748	233	30	gully	gully	ADJ
esrj-95748	233	31	erosion	erosion	NOUN
esrj-95748	233	32	areas	area	NOUN
esrj-95748	233	33	with	with	ADP
esrj-95748	233	34	high	high	ADJ
esrj-95748	233	35	accuracy	accuracy	NOUN
esrj-95748	233	36	.	.	PUNCT
esrj-95748	234	1	the	the	DET
esrj-95748	234	2	brf	brf	PROPN
esrj-95748	234	3	-	-	PUNCT
esrj-95748	234	4	svm	svm	PROPN
esrj-95748	234	5	was	be	AUX
esrj-95748	234	6	the	the	DET
esrj-95748	234	7	most	most	ADV
esrj-95748	234	8	robust	robust	ADJ
esrj-95748	234	9	model	model	NOUN
esrj-95748	234	10	(	(	PUNCT
esrj-95748	234	11	auc=	auc=	PROPN
esrj-95748	234	12	0.89	0.89	NUM
esrj-95748	234	13	;	;	PUNCT
esrj-95748	234	14	r2=	r2=	NUM
esrj-95748	234	15	0.91	0.91	NUM
esrj-95748	234	16	;	;	PUNCT
esrj-95748	234	17	rmse=	rmse=	ADJ
esrj-95748	234	18	0.23	0.23	NUM
esrj-95748	234	19	)	)	PUNCT
esrj-95748	234	20	,	,	PUNCT
esrj-95748	234	21	illustrating	illustrate	VERB
esrj-95748	234	22	the	the	DET
esrj-95748	234	23	best	good	ADJ
esrj-95748	234	24	prediction	prediction	NOUN
esrj-95748	234	25	rate	rate	NOUN
esrj-95748	234	26	.	.	PUNCT
esrj-95748	235	1	the	the	DET
esrj-95748	235	2	brt	brt	PROPN
esrj-95748	235	3	model	model	NOUN
esrj-95748	235	4	(	(	PUNCT
esrj-95748	235	5	auc=	auc=	PROPN
esrj-95748	235	6	0.85	0.85	NUM
esrj-95748	235	7	;	;	PUNCT
esrj-95748	235	8	r2=	r2=	PROPN
esrj-95748	235	9	0.83	0.83	NUM
esrj-95748	235	10	;	;	PUNCT
esrj-95748	235	11	rmse=	rmse=	ADJ
esrj-95748	235	12	0.29	0.29	NUM
esrj-95748	235	13	)	)	PUNCT
esrj-95748	235	14	was	be	AUX
esrj-95748	235	15	the	the	DET
esrj-95748	235	16	second	second	ADJ
esrj-95748	235	17	optimal	optimal	ADJ
esrj-95748	235	18	model	model	NOUN
esrj-95748	235	19	for	for	ADP
esrj-95748	235	20	predicting	predict	VERB
esrj-95748	235	21	erosion	erosion	NOUN
esrj-95748	235	22	susceptibility	susceptibility	NOUN
esrj-95748	235	23	in	in	ADP
esrj-95748	235	24	the	the	DET
esrj-95748	235	25	region	region	NOUN
esrj-95748	235	26	.	.	PUNCT
esrj-95748	236	1	the	the	DET
esrj-95748	236	2	gully	gully	PROPN
esrj-95748	236	3	erosion	erosion	NOUN
esrj-95748	236	4	susceptibility	susceptibility	NOUN
esrj-95748	236	5	maps	map	NOUN
esrj-95748	236	6	could	could	AUX
esrj-95748	236	7	provide	provide	VERB
esrj-95748	236	8	an	an	DET
esrj-95748	236	9	appropriate	appropriate	ADJ
esrj-95748	236	10	strategy	strategy	NOUN
esrj-95748	236	11	for	for	ADP
esrj-95748	236	12	geo	geo	PROPN
esrj-95748	236	13	-	-	PUNCT
esrj-95748	236	14	conservation	conservation	NOUN
esrj-95748	236	15	and	and	CCONJ
esrj-95748	236	16	restoration	restoration	NOUN
esrj-95748	236	17	efforts	effort	NOUN
esrj-95748	236	18	in	in	ADP
esrj-95748	236	19	gully	gully	ADJ
esrj-95748	236	20	erosion	erosion	NOUN
esrj-95748	236	21	-	-	PUNCT
esrj-95748	236	22	prone	prone	ADJ
esrj-95748	236	23	areas	area	NOUN
esrj-95748	236	24	within	within	ADP
esrj-95748	236	25	the	the	DET
esrj-95748	236	26	study	study	NOUN
esrj-95748	236	27	watershed	watershe	VERB
esrj-95748	236	28	.	.	PUNCT
esrj-95748	237	1	references	reference	NOUN
esrj-95748	237	2	arabameri	arabameri	PROPN
esrj-95748	237	3	,	,	PUNCT
esrj-95748	237	4	a.	a.	NOUN
esrj-95748	237	5	,	,	PUNCT
esrj-95748	237	6	asadi	asadi	NOUN
esrj-95748	237	7	,	,	PUNCT
esrj-95748	237	8	n.	n.	PROPN
esrj-95748	237	9	o.	o.	PROPN
esrj-95748	237	10	,	,	PUNCT
esrj-95748	237	11	saha	saha	PROPN
esrj-95748	237	12	,	,	PUNCT
esrj-95748	237	13	s.	s.	PROPN
esrj-95748	237	14	,	,	PUNCT
esrj-95748	237	15	roy	roy	PROPN
esrj-95748	237	16	,	,	PUNCT
esrj-95748	237	17	j.	j.	PROPN
esrj-95748	237	18	,	,	PUNCT
esrj-95748	237	19	pradhan	pradhan	PROPN
esrj-95748	237	20	,	,	PUNCT
esrj-95748	237	21	b.	b.	PROPN
esrj-95748	237	22	,	,	PUNCT
esrj-95748	237	23	tiefenbacher	tiefenbacher	PROPN
esrj-95748	237	24	,	,	PUNCT
esrj-95748	237	25	j.	j.	PROPN
esrj-95748	237	26	p.	p.	PROPN
esrj-95748	237	27	,	,	PUNCT
esrj-95748	237	28	&	&	CCONJ
esrj-95748	237	29	thi	thi	VERB
esrj-95748	237	30	ngo	ngo	PROPN
esrj-95748	237	31	,	,	PUNCT
esrj-95748	237	32	p.	p.	NOUN
esrj-95748	237	33	t.	t.	PROPN
esrj-95748	237	34	(	(	PUNCT
esrj-95748	237	35	2020	2020	NUM
esrj-95748	237	36	)	)	PUNCT
esrj-95748	237	37	.	.	PUNCT
esrj-95748	238	1	novel	novel	NOUN
esrj-95748	238	2	ensemble	ensemble	ADJ
esrj-95748	238	3	approaches	approach	NOUN
esrj-95748	238	4	of	of	ADP
esrj-95748	238	5	machine	machine	NOUN
esrj-95748	238	6	learning	learn	VERB
esrj-95748	238	7	techniques	technique	NOUN
esrj-95748	238	8	in	in	ADP
esrj-95748	238	9	modeling	model	VERB
esrj-95748	238	10	the	the	DET
esrj-95748	238	11	gully	gully	ADJ
esrj-95748	238	12	erosion	erosion	NOUN
esrj-95748	238	13	susceptibility	susceptibility	NOUN
esrj-95748	238	14	.	.	PUNCT
esrj-95748	239	1	remote	remote	ADJ
esrj-95748	239	2	sensing	sensing	NOUN
esrj-95748	239	3	,	,	PUNCT
esrj-95748	239	4	12(11	12(11	NUM
esrj-95748	239	5	)	)	PUNCT
esrj-95748	239	6	,	,	PUNCT
esrj-95748	239	7	1	1	NUM
esrj-95748	239	8	-	-	SYM
esrj-95748	239	9	31	31	NUM
esrj-95748	239	10	.	.	PUNCT
esrj-95748	240	1	https://doi.org/10.3390/rs12111890	https://doi.org/10.3390/rs12111890	PROPN
esrj-95748	240	2	arabameri	arabameri	NOUN
esrj-95748	240	3	,	,	PUNCT
esrj-95748	240	4	a.	a.	NOUN
esrj-95748	240	5	,	,	PUNCT
esrj-95748	240	6	pradhan	pradhan	PROPN
esrj-95748	240	7	,	,	PUNCT
esrj-95748	240	8	b.	b.	PROPN
esrj-95748	240	9	,	,	PUNCT
esrj-95748	240	10	rezaei	rezaei	PROPN
esrj-95748	240	11	,	,	PUNCT
esrj-95748	240	12	k.	k.	PROPN
esrj-95748	240	13	,	,	PUNCT
esrj-95748	240	14	yamani	yamani	PROPN
esrj-95748	240	15	,	,	PUNCT
esrj-95748	240	16	m.	m.	NOUN
esrj-95748	240	17	,	,	PUNCT
esrj-95748	240	18	pourghasemi	pourghasemi	PROPN
esrj-95748	240	19	,	,	PUNCT
esrj-95748	240	20	h.	h.	PROPN
esrj-95748	240	21	r.	r.	PROPN
esrj-95748	240	22	,	,	PUNCT
esrj-95748	240	23	&	&	CCONJ
esrj-95748	240	24	lombardo	lombardo	PROPN
esrj-95748	240	25	,	,	PUNCT
esrj-95748	240	26	l.	l.	PROPN
esrj-95748	240	27	(	(	PUNCT
esrj-95748	240	28	2018	2018	NUM
esrj-95748	240	29	)	)	PUNCT
esrj-95748	240	30	.	.	PUNCT
esrj-95748	241	1	spatial	spatial	ADJ
esrj-95748	241	2	modelling	modelling	NOUN
esrj-95748	241	3	of	of	ADP
esrj-95748	241	4	gully	gully	ADJ
esrj-95748	241	5	erosion	erosion	NOUN
esrj-95748	241	6	using	use	VERB
esrj-95748	241	7	evidential	evidential	ADJ
esrj-95748	241	8	belief	belief	NOUN
esrj-95748	241	9	function	function	NOUN
esrj-95748	241	10	,	,	PUNCT
esrj-95748	241	11	logistic	logistic	ADJ
esrj-95748	241	12	regression	regression	NOUN
esrj-95748	241	13	,	,	PUNCT
esrj-95748	241	14	and	and	CCONJ
esrj-95748	241	15	a	a	DET
esrj-95748	241	16	new	new	ADJ
esrj-95748	241	17	ensemble	ensemble	NOUN
esrj-95748	241	18	of	of	ADP
esrj-95748	241	19	evidential	evidential	ADJ
esrj-95748	241	20	belief	belief	NOUN
esrj-95748	241	21	function	function	NOUN
esrj-95748	241	22	–	–	PUNCT
esrj-95748	241	23	logistic	logistic	ADJ
esrj-95748	241	24	regression	regression	NOUN
esrj-95748	241	25	algorithm	algorithm	NOUN
esrj-95748	241	26	.	.	PUNCT
esrj-95748	242	1	land	land	NOUN
esrj-95748	242	2	degradation	degradation	NOUN
esrj-95748	242	3	&	&	CCONJ
esrj-95748	242	4	development	development	NOUN
esrj-95748	242	5	,	,	PUNCT
esrj-95748	242	6	29(11	29(11	NUM
esrj-95748	242	7	)	)	PUNCT
esrj-95748	242	8	,	,	PUNCT
esrj-95748	242	9	4035–4049	4035–4049	NUM
esrj-95748	242	10	.	.	PUNCT
esrj-95748	243	1	https://doi.org/10.1002/ldr.3151	https://doi.org/10.1002/ldr.3151	PROPN
esrj-95748	243	2	amiri	amiri	PROPN
esrj-95748	243	3	,	,	PUNCT
esrj-95748	243	4	m.	m.	NOUN
esrj-95748	243	5	,	,	PUNCT
esrj-95748	243	6	pourghasemi	pourghasemi	PROPN
esrj-95748	243	7	,	,	PUNCT
esrj-95748	243	8	h.	h.	PROPN
esrj-95748	243	9	r.	r.	PROPN
esrj-95748	243	10	,	,	PUNCT
esrj-95748	243	11	ghanbarian	ghanbarian	NOUN
esrj-95748	243	12	,	,	PUNCT
esrj-95748	243	13	g.	g.	PROPN
esrj-95748	243	14	a.	a.	PROPN
esrj-95748	243	15	,	,	PUNCT
esrj-95748	243	16	&	&	CCONJ
esrj-95748	243	17	afzali	afzali	PROPN
esrj-95748	243	18	,	,	PUNCT
esrj-95748	243	19	s.	s.	PROPN
esrj-95748	243	20	f.	f.	PROPN
esrj-95748	243	21	(	(	PUNCT
esrj-95748	243	22	2019	2019	NUM
esrj-95748	243	23	)	)	PUNCT
esrj-95748	243	24	.	.	PUNCT
esrj-95748	244	1	assessment	assessment	NOUN
esrj-95748	244	2	of	of	ADP
esrj-95748	244	3	the	the	DET
esrj-95748	244	4	importance	importance	NOUN
esrj-95748	244	5	of	of	ADP
esrj-95748	244	6	gully	gully	ADJ
esrj-95748	244	7	erosion	erosion	NOUN
esrj-95748	244	8	effective	effective	ADJ
esrj-95748	244	9	factors	factor	NOUN
esrj-95748	244	10	using	use	VERB
esrj-95748	244	11	boruta	boruta	NOUN
esrj-95748	244	12	algorithm	algorithm	NOUN
esrj-95748	244	13	and	and	CCONJ
esrj-95748	244	14	its	its	PRON
esrj-95748	244	15	spatial	spatial	ADJ
esrj-95748	244	16	modeling	modeling	NOUN
esrj-95748	244	17	and	and	CCONJ
esrj-95748	244	18	mapping	mapping	NOUN
esrj-95748	244	19	using	use	VERB
esrj-95748	244	20	three	three	NUM
esrj-95748	244	21	machine	machine	NOUN
esrj-95748	244	22	learning	learn	VERB
esrj-95748	244	23	algorithms	algorithm	NOUN
esrj-95748	244	24	.	.	PUNCT
esrj-95748	245	1	geoderma	geoderma	PROPN
esrj-95748	245	2	,	,	PUNCT
esrj-95748	245	3	340	340	NUM
esrj-95748	245	4	,	,	PUNCT
esrj-95748	245	5	55	55	NUM
esrj-95748	245	6	-	-	SYM
esrj-95748	245	7	69	69	NUM
esrj-95748	245	8	.	.	PUNCT
esrj-95748	246	1	https://doi.org/10.1016/j.geoderma.2018.12.042	https://doi.org/10.1016/j.geoderma.2018.12.042	NOUN
esrj-95748	246	2	aertsen	aertsen	ADJ
esrj-95748	246	3	,	,	PUNCT
esrj-95748	246	4	w.	w.	PROPN
esrj-95748	246	5	,	,	PUNCT
esrj-95748	246	6	kint	kint	NOUN
esrj-95748	246	7	,	,	PUNCT
esrj-95748	246	8	v.	v.	ADV
esrj-95748	246	9	,	,	PUNCT
esrj-95748	246	10	orshoven	orshoven	VERB
esrj-95748	246	11	,	,	PUNCT
esrj-95748	246	12	j.	j.	PROPN
esrj-95748	246	13	v.	v.	PROPN
esrj-95748	246	14	,	,	PUNCT
esrj-95748	246	15	özkan	özkan	PROPN
esrj-95748	246	16	,	,	PUNCT
esrj-95748	246	17	k.	k.	PROPN
esrj-95748	246	18	&	&	CCONJ
esrj-95748	246	19	muys	muys	PROPN
esrj-95748	246	20	,	,	PUNCT
esrj-95748	246	21	b.	b.	PROPN
esrj-95748	246	22	(	(	PUNCT
esrj-95748	246	23	2010	2010	NUM
esrj-95748	246	24	)	)	PUNCT
esrj-95748	246	25	.	.	PUNCT
esrj-95748	247	1	comparison	comparison	NOUN
esrj-95748	247	2	and	and	CCONJ
esrj-95748	247	3	ranking	ranking	NOUN
esrj-95748	247	4	of	of	ADP
esrj-95748	247	5	different	different	ADJ
esrj-95748	247	6	modeling	modeling	NOUN
esrj-95748	247	7	techniques	technique	NOUN
esrj-95748	247	8	for	for	ADP
esrj-95748	247	9	prediction	prediction	NOUN
esrj-95748	247	10	of	of	ADP
esrj-95748	247	11	site	site	NOUN
esrj-95748	247	12	index	index	NOUN
esrj-95748	247	13	in	in	ADP
esrj-95748	247	14	mediterranean	mediterranean	PROPN
esrj-95748	247	15	mountain	mountain	NOUN
esrj-95748	247	16	forests	forest	NOUN
esrj-95748	247	17	.	.	PUNCT
esrj-95748	248	1	ecological	ecological	ADJ
esrj-95748	248	2	modelling	modelling	NOUN
esrj-95748	248	3	,	,	PUNCT
esrj-95748	248	4	221(8	221(8	NUM
esrj-95748	248	5	)	)	PUNCT
esrj-95748	248	6	,	,	PUNCT
esrj-95748	248	7	1119–1130	1119–1130	NUM
esrj-95748	248	8	.	.	PUNCT
esrj-95748	249	1	https://doi.org/10.1016/j.ecolmodel.2010.01.007	https://doi.org/10.1016/j.ecolmodel.2010.01.007	ADJ
esrj-95748	249	2	althuwaynee	althuwaynee	NOUN
esrj-95748	249	3	,	,	PUNCT
esrj-95748	249	4	o.	o.	PROPN
esrj-95748	249	5	f.	f.	PROPN
esrj-95748	249	6	,	,	PUNCT
esrj-95748	249	7	pradhan	pradhan	PROPN
esrj-95748	249	8	,	,	PUNCT
esrj-95748	249	9	b.	b.	PROPN
esrj-95748	249	10	,	,	PUNCT
esrj-95748	249	11	park	park	PROPN
esrj-95748	249	12	,	,	PUNCT
esrj-95748	249	13	h.	h.	PROPN
esrj-95748	249	14	j.	j.	PROPN
esrj-95748	249	15	&	&	CCONJ
esrj-95748	249	16	lee	lee	PROPN
esrj-95748	249	17	,	,	PUNCT
esrj-95748	249	18	j.	j.	PROPN
esrj-95748	249	19	h.	h.	PROPN
esrj-95748	249	20	(	(	PUNCT
esrj-95748	249	21	2014	2014	NUM
esrj-95748	249	22	)	)	PUNCT
esrj-95748	249	23	.	.	PUNCT
esrj-95748	250	1	a	a	DET
esrj-95748	250	2	novel	novel	ADJ
esrj-95748	250	3	ensemble	ensemble	ADJ
esrj-95748	250	4	bivariate	bivariate	ADJ
esrj-95748	250	5	statistical	statistical	ADJ
esrj-95748	250	6	evidential	evidential	ADJ
esrj-95748	250	7	belief	belief	NOUN
esrj-95748	250	8	function	function	NOUN
esrj-95748	250	9	with	with	ADP
esrj-95748	250	10	knowledge	knowledge	NOUN
esrj-95748	250	11	-	-	PUNCT
esrj-95748	250	12	based	base	VERB
esrj-95748	250	13	analytical	analytical	ADJ
esrj-95748	250	14	hierarchy	hierarchy	NOUN
esrj-95748	250	15	process	process	NOUN
esrj-95748	250	16	and	and	CCONJ
esrj-95748	250	17	multivariate	multivariate	VERB
esrj-95748	250	18	statistical	statistical	ADJ
esrj-95748	250	19	logistic	logistic	ADJ
esrj-95748	250	20	regression	regression	NOUN
esrj-95748	250	21	for	for	ADP
esrj-95748	250	22	landslide	landslide	NOUN
esrj-95748	250	23	susceptibility	susceptibility	NOUN
esrj-95748	250	24	mapping	mapping	NOUN
esrj-95748	250	25	.	.	PUNCT
esrj-95748	251	1	catena	catena	PROPN
esrj-95748	251	2	,	,	PUNCT
esrj-95748	251	3	114	114	NUM
esrj-95748	251	4	,	,	PUNCT
esrj-95748	251	5	21–36	21–36	NUM
esrj-95748	251	6	.	.	PUNCT
esrj-95748	252	1	https://	https://	PROPN
esrj-95748	252	2	doi.org/10.1016/j.catena.2013.10.011	doi.org/10.1016/j.catena.2013.10.011	PROPN
esrj-95748	252	3	bell	bell	PROPN
esrj-95748	252	4	,	,	PUNCT
esrj-95748	252	5	j.	j.	PROPN
esrj-95748	252	6	c.	c.	PROPN
esrj-95748	252	7	,	,	PUNCT
esrj-95748	252	8	butler	butler	PROPN
esrj-95748	252	9	,	,	PUNCT
esrj-95748	252	10	c.	c.	PROPN
esrj-95748	252	11	a.	a.	PROPN
esrj-95748	252	12	&	&	CCONJ
esrj-95748	252	13	thompson	thompson	PROPN
esrj-95748	252	14	,	,	PUNCT
esrj-95748	252	15	j.	j.	PROPN
esrj-95748	252	16	a.	a.	PROPN
esrj-95748	252	17	(	(	PUNCT
esrj-95748	252	18	1995	1995	NUM
esrj-95748	252	19	)	)	PUNCT
esrj-95748	252	20	.	.	PUNCT
esrj-95748	253	1	soil	soil	NOUN
esrj-95748	253	2	terrain	terrain	NOUN
esrj-95748	253	3	modeling	modeling	NOUN
esrj-95748	253	4	for	for	ADP
esrj-95748	253	5	site	site	NOUN
esrj-95748	253	6	-	-	PUNCT
esrj-95748	253	7	specific	specific	ADJ
esrj-95748	253	8	agricultural	agricultural	ADJ
esrj-95748	253	9	management	management	NOUN
esrj-95748	253	10	.	.	PUNCT
esrj-95748	254	1	in	in	ADP
esrj-95748	254	2	:	:	PUNCT
esrj-95748	254	3	robert	robert	PROPN
esrj-95748	254	4	,	,	PUNCT
esrj-95748	254	5	p.	p.	PROPN
esrj-95748	254	6	c.	c.	PROPN
esrj-95748	254	7	,	,	PUNCT
esrj-95748	254	8	rust	rust	PROPN
esrj-95748	254	9	,	,	PUNCT
esrj-95748	254	10	r.	r.	PROPN
esrj-95748	254	11	h.	h.	PROPN
esrj-95748	254	12	,	,	PUNCT
esrj-95748	254	13	larson	larson	PROPN
esrj-95748	254	14	,	,	PUNCT
esrj-95748	254	15	w.	w.	PROPN
esrj-95748	254	16	e.(eds	e.(ed	NOUN
esrj-95748	254	17	.	.	PUNCT
esrj-95748	254	18	)	)	PUNCT
esrj-95748	254	19	,	,	PUNCT
esrj-95748	254	20	site	site	NOUN
esrj-95748	254	21	-	-	PUNCT
esrj-95748	254	22	specific	specific	ADJ
esrj-95748	254	23	management	management	NOUN
esrj-95748	254	24	for	for	ADP
esrj-95748	254	25	agricultural	agricultural	ADJ
esrj-95748	254	26	systems	system	NOUN
esrj-95748	254	27	.	.	PUNCT
esrj-95748	255	1	american	american	ADJ
esrj-95748	255	2	society	society	PROPN
esrj-95748	255	3	of	of	ADP
esrj-95748	255	4	agronomy	agronomy	NOUN
esrj-95748	255	5	,	,	PUNCT
esrj-95748	255	6	madison	madison	PROPN
esrj-95748	255	7	,	,	PUNCT
esrj-95748	255	8	wi	wi	PROPN
esrj-95748	255	9	,	,	PUNCT
esrj-95748	255	10	p.	p.	NOUN
esrj-95748	255	11	209	209	NUM
esrj-95748	255	12	.	.	PUNCT
esrj-95748	256	1	brown	brown	PROPN
esrj-95748	256	2	,	,	PUNCT
esrj-95748	256	3	d.	d.	PROPN
esrj-95748	256	4	j.	j.	PROPN
esrj-95748	256	5	,	,	PUNCT
esrj-95748	256	6	shepherd	shepherd	PROPN
esrj-95748	256	7	,	,	PUNCT
esrj-95748	256	8	k.	k.	PROPN
esrj-95748	256	9	d.	d.	PROPN
esrj-95748	256	10	,	,	PUNCT
esrj-95748	256	11	walsh	walsh	PROPN
esrj-95748	256	12	,	,	PUNCT
esrj-95748	256	13	m.	m.	NOUN
esrj-95748	256	14	g.	g.	PROPN
esrj-95748	256	15	,	,	PUNCT
esrj-95748	256	16	mays	may	NOUN
esrj-95748	256	17	,	,	PUNCT
esrj-95748	256	18	m.	m.	PROPN
esrj-95748	256	19	d.	d.	PROPN
esrj-95748	256	20	&	&	CCONJ
esrj-95748	256	21	reinsch	reinsch	PROPN
esrj-95748	256	22	,	,	PUNCT
esrj-95748	256	23	t.	t.	PROPN
esrj-95748	256	24	g.	g.	PROPN
esrj-95748	256	25	(	(	PUNCT
esrj-95748	256	26	2006	2006	NUM
esrj-95748	256	27	)	)	PUNCT
esrj-95748	256	28	.	.	PUNCT
esrj-95748	257	1	global	global	ADJ
esrj-95748	257	2	soil	soil	NOUN
esrj-95748	257	3	characterization	characterization	NOUN
esrj-95748	257	4	with	with	ADP
esrj-95748	257	5	vnir	vnir	NOUN
esrj-95748	257	6	diffuses	diffuse	VERB
esrj-95748	257	7	reflectance	reflectance	NOUN
esrj-95748	257	8	spectroscopy	spectroscopy	NOUN
esrj-95748	257	9	.	.	PUNCT
esrj-95748	258	1	geoderma	geoderma	NOUN
esrj-95748	258	2	,	,	PUNCT
esrj-95748	258	3	132(2	132(2	NUM
esrj-95748	258	4	-	-	SYM
esrj-95748	258	5	3	3	NUM
esrj-95748	258	6	)	)	PUNCT
esrj-95748	258	7	,	,	PUNCT
esrj-95748	258	8	273–290	273–290	NUM
esrj-95748	258	9	.	.	PUNCT
esrj-95748	259	1	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
esrj-95748	259	2	.	.	PUNCT
esrj-95748	260	1	geoderma.2005.04.025	geoderma.2005.04.025	PROPN
esrj-95748	260	2	carranza	carranza	PROPN
esrj-95748	260	3	,	,	PUNCT
esrj-95748	260	4	e.	e.	PROPN
esrj-95748	260	5	j.	j.	PROPN
esrj-95748	260	6	m.	m.	PROPN
esrj-95748	260	7	,	,	PUNCT
esrj-95748	260	8	woldai	woldai	PROPN
esrj-95748	260	9	,	,	PUNCT
esrj-95748	260	10	t.	t.	PROPN
esrj-95748	260	11	&	&	CCONJ
esrj-95748	260	12	chikambwe	chikambwe	PROPN
esrj-95748	260	13	,	,	PUNCT
esrj-95748	260	14	e.	e.	PROPN
esrj-95748	260	15	m.	m.	PROPN
esrj-95748	260	16	(	(	PUNCT
esrj-95748	260	17	2005	2005	NUM
esrj-95748	260	18	)	)	PUNCT
esrj-95748	260	19	.	.	PUNCT
esrj-95748	261	1	application	application	NOUN
esrj-95748	261	2	of	of	ADP
esrj-95748	261	3	data	data	NOUN
esrj-95748	261	4	-	-	PUNCT
esrj-95748	261	5	driven	drive	VERB
esrj-95748	261	6	evidential	evidential	ADJ
esrj-95748	261	7	belief	belief	NOUN
esrj-95748	261	8	functions	function	NOUN
esrj-95748	261	9	to	to	ADP
esrj-95748	261	10	prospectivity	prospectivity	NOUN
esrj-95748	261	11	mapping	mapping	NOUN
esrj-95748	261	12	for	for	ADP
esrj-95748	261	13	aquamarine	aquamarine	NOUN
esrj-95748	261	14	-	-	PUNCT
esrj-95748	261	15	bearing	bear	VERB
esrj-95748	261	16	pegmatites	pegmatite	NOUN
esrj-95748	261	17	,	,	PUNCT
esrj-95748	261	18	lundazi	lundazi	NOUN
esrj-95748	261	19	district	district	NOUN
esrj-95748	261	20	,	,	PUNCT
esrj-95748	261	21	zambia	zambia	PROPN
esrj-95748	261	22	.	.	PUNCT
esrj-95748	261	23	natural	natural	ADJ
esrj-95748	261	24	resources	resource	NOUN
esrj-95748	261	25	research	research	NOUN
esrj-95748	261	26	,	,	PUNCT
esrj-95748	261	27	14(1	14(1	NUM
esrj-95748	261	28	)	)	PUNCT
esrj-95748	261	29	,	,	PUNCT
esrj-95748	261	30	47–63	47–63	PROPN
esrj-95748	261	31	.	.	PUNCT
esrj-95748	261	32	https://doi.org/10.1007/s11053-005-4678-9	https://doi.org/10.1007/s11053-005-4678-9	PROPN
esrj-95748	261	33	conoscenti	conoscenti	PROPN
esrj-95748	261	34	,	,	PUNCT
esrj-95748	261	35	c.	c.	NOUN
esrj-95748	261	36	,	,	PUNCT
esrj-95748	261	37	angileri	angileri	PROPN
esrj-95748	261	38	,	,	PUNCT
esrj-95748	261	39	s.	s.	PROPN
esrj-95748	261	40	,	,	PUNCT
esrj-95748	261	41	cappadonia	cappadonia	PROPN
esrj-95748	261	42	,	,	PUNCT
esrj-95748	261	43	c.	c.	PROPN
esrj-95748	261	44	,	,	PUNCT
esrj-95748	261	45	rotigliano	rotigliano	PROPN
esrj-95748	261	46	,	,	PUNCT
esrj-95748	261	47	e.	e.	PROPN
esrj-95748	261	48	,	,	PUNCT
esrj-95748	261	49	agnesi	agnesi	PROPN
esrj-95748	261	50	,	,	PUNCT
esrj-95748	261	51	v.	v.	PROPN
esrj-95748	261	52	&	&	CCONJ
esrj-95748	261	53	märker	märker	PROPN
esrj-95748	261	54	,	,	PUNCT
esrj-95748	261	55	m.	m.	NOUN
esrj-95748	261	56	(	(	PUNCT
esrj-95748	261	57	2014	2014	NUM
esrj-95748	261	58	)	)	PUNCT
esrj-95748	261	59	.	.	PUNCT
esrj-95748	262	1	gully	gully	NOUN
esrj-95748	262	2	erosion	erosion	NOUN
esrj-95748	262	3	susceptibility	susceptibility	NOUN
esrj-95748	262	4	assessment	assessment	NOUN
esrj-95748	262	5	by	by	ADP
esrj-95748	262	6	means	mean	NOUN
esrj-95748	262	7	of	of	ADP
esrj-95748	262	8	gis	gis	NOUN
esrj-95748	262	9	-	-	PUNCT
esrj-95748	262	10	based	base	VERB
esrj-95748	262	11	logistic	logistic	ADJ
esrj-95748	262	12	regression	regression	NOUN
esrj-95748	262	13	:	:	PUNCT
esrj-95748	262	14	a	a	DET
esrj-95748	262	15	case	case	NOUN
esrj-95748	262	16	of	of	ADP
esrj-95748	262	17	sicily	sicily	PROPN
esrj-95748	262	18	(	(	PUNCT
esrj-95748	262	19	italy	italy	PROPN
esrj-95748	262	20	)	)	PUNCT
esrj-95748	262	21	.	.	PUNCT
esrj-95748	263	1	geomorphology	geomorphology	NOUN
esrj-95748	263	2	,	,	PUNCT
esrj-95748	263	3	204(1	204(1	NUM
esrj-95748	263	4	)	)	PUNCT
esrj-95748	263	5	,	,	PUNCT
esrj-95748	263	6	399–411	399–411	NUM
esrj-95748	263	7	.	.	PUNCT
esrj-95748	263	8	https://doi.org/10.1016/j.geomorph.2013.08.021	https://doi.org/10.1016/j.geomorph.2013.08.021	PROPN
esrj-95748	263	9	chaplot	chaplot	PROPN
esrj-95748	263	10	,	,	PUNCT
esrj-95748	263	11	v.	v.	PROPN
esrj-95748	263	12	,	,	PUNCT
esrj-95748	263	13	coadou	coadou	PROPN
esrj-95748	263	14	,	,	PUNCT
esrj-95748	263	15	b.	b.	PROPN
esrj-95748	263	16	e.	e.	PROPN
esrj-95748	263	17	,	,	PUNCT
esrj-95748	263	18	silvera	silvera	PROPN
esrj-95748	263	19	,	,	PUNCT
esrj-95748	263	20	n.	n.	NOUN
esrj-95748	263	21	,	,	PUNCT
esrj-95748	263	22	&	&	CCONJ
esrj-95748	263	23	valentinb	valentinb	PROPN
esrj-95748	263	24	,	,	PUNCT
esrj-95748	263	25	c.	c.	PROPN
esrj-95748	263	26	(	(	PUNCT
esrj-95748	263	27	2005	2005	NUM
esrj-95748	263	28	)	)	PUNCT
esrj-95748	263	29	.	.	PUNCT
esrj-95748	264	1	spatial	spatial	ADJ
esrj-95748	264	2	and	and	CCONJ
esrj-95748	264	3	temporal	temporal	ADJ
esrj-95748	264	4	assessment	assessment	NOUN
esrj-95748	264	5	of	of	ADP
esrj-95748	264	6	linear	linear	ADJ
esrj-95748	264	7	erosion	erosion	NOUN
esrj-95748	264	8	in	in	ADP
esrj-95748	264	9	catchment	catchment	NOUN
esrj-95748	264	10	under	under	ADP
esrj-95748	264	11	sloping	slope	VERB
esrj-95748	264	12	lands	land	NOUN
esrj-95748	264	13	of	of	ADP
esrj-95748	264	14	northern	northern	ADJ
esrj-95748	264	15	laos	laos	PROPN
esrj-95748	264	16	.	.	PUNCT
esrj-95748	265	1	catena	catena	PROPN
esrj-95748	265	2	,	,	PUNCT
esrj-95748	265	3	63(2	63(2	NOUN
esrj-95748	265	4	-	-	PUNCT
esrj-95748	265	5	3	3	NUM
esrj-95748	265	6	)	)	PUNCT
esrj-95748	265	7	,	,	PUNCT
esrj-95748	265	8	167–184	167–184	NUM
esrj-95748	265	9	.	.	PUNCT
esrj-95748	266	1	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
esrj-95748	266	2	.	.	PUNCT
esrj-95748	266	3	catena.2005.06.003	catena.2005.06.003	PUNCT
esrj-95748	267	1	chen	chen	PROPN
esrj-95748	267	2	,	,	PUNCT
esrj-95748	267	3	w.	w.	PROPN
esrj-95748	267	4	,	,	PUNCT
esrj-95748	267	5	lei	lei	PROPN
esrj-95748	267	6	,	,	PUNCT
esrj-95748	267	7	x.	x.	PROPN
esrj-95748	267	8	,	,	PUNCT
esrj-95748	267	9	chakrabortty	chakrabortty	PROPN
esrj-95748	267	10	,	,	PUNCT
esrj-95748	267	11	r.	r.	PROPN
esrj-95748	267	12	,	,	PUNCT
esrj-95748	267	13	pal	pal	NOUN
esrj-95748	267	14	,	,	PUNCT
esrj-95748	267	15	s.	s.	PROPN
esrj-95748	267	16	c.	c.	PROPN
esrj-95748	267	17	,	,	PUNCT
esrj-95748	267	18	sahana	sahana	PROPN
esrj-95748	267	19	,	,	PUNCT
esrj-95748	267	20	m.	m.	NOUN
esrj-95748	267	21	&	&	CCONJ
esrj-95748	267	22	janizadeh	janizadeh	PROPN
esrj-95748	267	23	,	,	PUNCT
esrj-95748	267	24	s.	s.	PROPN
esrj-95748	267	25	(	(	PUNCT
esrj-95748	267	26	2021	2021	NUM
esrj-95748	267	27	)	)	PUNCT
esrj-95748	267	28	.	.	PUNCT
esrj-95748	268	1	evaluation	evaluation	NOUN
esrj-95748	268	2	of	of	ADP
esrj-95748	268	3	different	different	ADJ
esrj-95748	268	4	boosting	boost	VERB
esrj-95748	268	5	ensemble	ensemble	ADJ
esrj-95748	268	6	machine	machine	NOUN
esrj-95748	268	7	learning	learning	NOUN
esrj-95748	268	8	models	model	NOUN
esrj-95748	268	9	and	and	CCONJ
esrj-95748	268	10	novel	novel	ADJ
esrj-95748	268	11	deep	deep	ADJ
esrj-95748	268	12	learning	learning	NOUN
esrj-95748	268	13	and	and	CCONJ
esrj-95748	268	14	boosting	boost	VERB
esrj-95748	268	15	framework	framework	NOUN
esrj-95748	268	16	for	for	ADP
esrj-95748	268	17	head	head	NOUN
esrj-95748	268	18	-	-	PUNCT
esrj-95748	268	19	cut	cut	VERB
esrj-95748	268	20	gully	gully	ADJ
esrj-95748	268	21	erosion	erosion	NOUN
esrj-95748	268	22	susceptibility	susceptibility	NOUN
esrj-95748	268	23	.	.	PUNCT
esrj-95748	269	1	journal	journal	PROPN
esrj-95748	269	2	of	of	ADP
esrj-95748	269	3	environmental	environmental	ADJ
esrj-95748	269	4	management	management	NOUN
esrj-95748	269	5	,	,	PUNCT
esrj-95748	269	6	284	284	NUM
esrj-95748	269	7	,	,	PUNCT
esrj-95748	269	8	112015	112015	NUM
esrj-95748	269	9	-	-	SYM
esrj-95748	269	10	112015	112015	NUM
esrj-95748	269	11	.	.	PUNCT
esrj-95748	270	1	https://doi.org/10.1016/j.jenvman.2021.112015	https://doi.org/10.1016/j.jenvman.2021.112015	PROPN
esrj-95748	270	2	dempster	dempster	PROPN
esrj-95748	270	3	,	,	PUNCT
esrj-95748	270	4	a.	a.	NOUN
esrj-95748	270	5	p.	p.	NOUN
esrj-95748	270	6	(	(	PUNCT
esrj-95748	270	7	1967	1967	NUM
esrj-95748	270	8	)	)	PUNCT
esrj-95748	270	9	.	.	PUNCT
esrj-95748	271	1	upper	upper	ADJ
esrj-95748	271	2	and	and	CCONJ
esrj-95748	271	3	lower	low	ADJ
esrj-95748	271	4	probabilities	probability	NOUN
esrj-95748	271	5	induced	induce	VERB
esrj-95748	271	6	by	by	ADP
esrj-95748	271	7	a	a	DET
esrj-95748	271	8	multivalued	multivalue	VERB
esrj-95748	271	9	mapping	mapping	NOUN
esrj-95748	271	10	.	.	PUNCT
esrj-95748	272	1	springer	springer	NOUN
esrj-95748	272	2	,	,	PUNCT
esrj-95748	272	3	berlin	berlin	PROPN
esrj-95748	272	4	,	,	PUNCT
esrj-95748	272	5	heidelberg	heidelberg	NOUN
esrj-95748	272	6	,	,	PUNCT
esrj-95748	272	7	38(2	38(2	NOUN
esrj-95748	272	8	)	)	PUNCT
esrj-95748	272	9	,	,	PUNCT
esrj-95748	272	10	325–339	325–339	NUM
esrj-95748	272	11	.	.	PUNCT
esrj-95748	273	1	elith	elith	PROPN
esrj-95748	273	2	,	,	PUNCT
esrj-95748	273	3	j.	j.	PROPN
esrj-95748	273	4	,	,	PUNCT
esrj-95748	273	5	leathwick	leathwick	PROPN
esrj-95748	273	6	,	,	PUNCT
esrj-95748	273	7	j.	j.	PROPN
esrj-95748	273	8	r.	r.	PROPN
esrj-95748	273	9	,	,	PUNCT
esrj-95748	273	10	&	&	CCONJ
esrj-95748	273	11	hastie	hastie	PROPN
esrj-95748	273	12	,	,	PUNCT
esrj-95748	273	13	t.	t.	PROPN
esrj-95748	273	14	(	(	PUNCT
esrj-95748	273	15	2008	2008	NUM
esrj-95748	273	16	)	)	PUNCT
esrj-95748	273	17	.	.	PUNCT
esrj-95748	274	1	a	a	DET
esrj-95748	274	2	working	work	VERB
esrj-95748	274	3	guide	guide	NOUN
esrj-95748	274	4	to	to	PART
esrj-95748	274	5	boosted	boost	VERB
esrj-95748	274	6	regression	regression	NOUN
esrj-95748	274	7	trees	tree	NOUN
esrj-95748	274	8	.	.	PUNCT
esrj-95748	275	1	journal	journal	PROPN
esrj-95748	275	2	of	of	ADP
esrj-95748	275	3	animal	animal	NOUN
esrj-95748	275	4	ecology	ecology	NOUN
esrj-95748	275	5	,	,	PUNCT
esrj-95748	275	6	77	77	NUM
esrj-95748	275	7	(	(	PUNCT
esrj-95748	275	8	4	4	NUM
esrj-95748	275	9	)	)	PUNCT
esrj-95748	275	10	,	,	PUNCT
esrj-95748	275	11	802–813	802–813	NUM
esrj-95748	275	12	.	.	PUNCT
esrj-95748	276	1	http://dx	http://dx	NOUN
esrj-95748	276	2	.	.	PUNCT
esrj-95748	277	1	doi.org/10.1111/j.1365-2656.2008.01390.x	doi.org/10.1111/j.1365-2656.2008.01390.x	PROPN
esrj-95748	277	2	ekholm	ekholm	PROPN
esrj-95748	277	3	,	,	PUNCT
esrj-95748	277	4	p.	p.	NOUN
esrj-95748	277	5	,	,	PUNCT
esrj-95748	277	6	&	&	CCONJ
esrj-95748	277	7	lehtoranta	lehtoranta	PROPN
esrj-95748	277	8	,	,	PUNCT
esrj-95748	277	9	j.	j.	PROPN
esrj-95748	277	10	(	(	PUNCT
esrj-95748	277	11	2012	2012	NUM
esrj-95748	277	12	)	)	PUNCT
esrj-95748	277	13	.	.	PUNCT
esrj-95748	278	1	does	do	AUX
esrj-95748	278	2	control	control	NOUN
esrj-95748	278	3	of	of	ADP
esrj-95748	278	4	soil	soil	NOUN
esrj-95748	278	5	erosion	erosion	NOUN
esrj-95748	278	6	inhibit	inhibit	VERB
esrj-95748	278	7	aquatic	aquatic	ADJ
esrj-95748	278	8	eutrophication	eutrophication	NOUN
esrj-95748	278	9	.	.	PUNCT
esrj-95748	279	1	journal	journal	NOUN
esrj-95748	279	2	of	of	ADP
esrj-95748	279	3	environmental	environmental	ADJ
esrj-95748	279	4	management	management	NOUN
esrj-95748	279	5	,	,	PUNCT
esrj-95748	279	6	93(1	93(1	NUM
esrj-95748	279	7	)	)	PUNCT
esrj-95748	279	8	,	,	PUNCT
esrj-95748	279	9	140	140	NUM
esrj-95748	279	10	–	–	SYM
esrj-95748	279	11	146	146	NUM
esrj-95748	279	12	.	.	PUNCT
esrj-95748	279	13	https://doi.org/10.1016/j.jenvman.2011.09.010	https://doi.org/10.1016/j.jenvman.2011.09.010	NOUN
esrj-95748	279	14	fox	fox	PROPN
esrj-95748	279	15	,	,	PUNCT
esrj-95748	279	16	g.	g.	PROPN
esrj-95748	279	17	a.	a.	PROPN
esrj-95748	279	18	,	,	PUNCT
esrj-95748	279	19	sheshukov	sheshukov	PROPN
esrj-95748	279	20	,	,	PUNCT
esrj-95748	279	21	a.	a.	PROPN
esrj-95748	279	22	,	,	PUNCT
esrj-95748	279	23	cruse	cruse	PROPN
esrj-95748	279	24	,	,	PUNCT
esrj-95748	279	25	r.	r.	PROPN
esrj-95748	279	26	,	,	PUNCT
esrj-95748	279	27	kolar	kolar	PROPN
esrj-95748	279	28	,	,	PUNCT
esrj-95748	279	29	r.	r.	PROPN
esrj-95748	279	30	l.	l.	PROPN
esrj-95748	279	31	,	,	PUNCT
esrj-95748	279	32	guertault	guertault	PROPN
esrj-95748	279	33	,	,	PUNCT
esrj-95748	279	34	l.	l.	PROPN
esrj-95748	279	35	,	,	PUNCT
esrj-95748	279	36	gesch	gesch	PROPN
esrj-95748	279	37	,	,	PUNCT
esrj-95748	279	38	k.	k.	PROPN
esrj-95748	279	39	r.	r.	PROPN
esrj-95748	279	40	,	,	PUNCT
esrj-95748	279	41	&	&	CCONJ
esrj-95748	279	42	dutnell	dutnell	PROPN
esrj-95748	279	43	,	,	PUNCT
esrj-95748	279	44	r.	r.	PROPN
esrj-95748	279	45	c.	c.	PROPN
esrj-95748	279	46	(	(	PUNCT
esrj-95748	279	47	2016	2016	NUM
esrj-95748	279	48	)	)	PUNCT
esrj-95748	279	49	.	.	PUNCT
esrj-95748	280	1	reservoir	reservoir	PROPN
esrj-95748	280	2	sedimentation	sedimentation	NOUN
esrj-95748	280	3	and	and	CCONJ
esrj-95748	280	4	upstream	upstream	ADJ
esrj-95748	280	5	sediment	sediment	NOUN
esrj-95748	280	6	sources	source	NOUN
esrj-95748	280	7	:	:	PUNCT
esrj-95748	280	8	perspectives	perspective	NOUN
esrj-95748	280	9	and	and	CCONJ
esrj-95748	280	10	future	future	ADJ
esrj-95748	280	11	research	research	NOUN
esrj-95748	280	12	needs	need	VERB
esrj-95748	280	13	on	on	ADP
esrj-95748	280	14	stream	stream	PROPN
esrj-95748	280	15	bank	bank	PROPN
esrj-95748	280	16	and	and	CCONJ
esrj-95748	280	17	gully	gully	NOUN
esrj-95748	280	18	erosion	erosion	NOUN
esrj-95748	280	19	.	.	PUNCT
esrj-95748	281	1	journal	journal	NOUN
esrj-95748	281	2	of	of	ADP
esrj-95748	281	3	environmental	environmental	ADJ
esrj-95748	281	4	management	management	NOUN
esrj-95748	281	5	,	,	PUNCT
esrj-95748	281	6	57(5	57(5	NOUN
esrj-95748	281	7	)	)	PUNCT
esrj-95748	281	8	,	,	PUNCT
esrj-95748	281	9	945–955	945–955	NUM
esrj-95748	281	10	.	.	PUNCT
esrj-95748	282	1	https://doi.org/10.1007/s00267-016-0671-9	https://doi.org/10.1007/s00267-016-0671-9	NUM
esrj-95748	282	2	gayen	gayen	NOUN
esrj-95748	282	3	,	,	PUNCT
esrj-95748	282	4	a.	a.	NOUN
esrj-95748	282	5	,	,	PUNCT
esrj-95748	282	6	pourghasemi	pourghasemi	PROPN
esrj-95748	282	7	,	,	PUNCT
esrj-95748	282	8	h.	h.	PROPN
esrj-95748	282	9	r.	r.	PROPN
esrj-95748	282	10	,	,	PUNCT
esrj-95748	282	11	saha	saha	PROPN
esrj-95748	282	12	,	,	PUNCT
esrj-95748	282	13	s.	s.	PROPN
esrj-95748	282	14	,	,	PUNCT
esrj-95748	282	15	keesstra	keesstra	PROPN
esrj-95748	282	16	,	,	PUNCT
esrj-95748	282	17	s.	s.	PROPN
esrj-95748	282	18	&	&	CCONJ
esrj-95748	282	19	bai	bai	PROPN
esrj-95748	282	20	,	,	PUNCT
esrj-95748	282	21	s.	s.	PROPN
esrj-95748	282	22	(	(	PUNCT
esrj-95748	282	23	2019	2019	NUM
esrj-95748	282	24	)	)	PUNCT
esrj-95748	282	25	.	.	PUNCT
esrj-95748	283	1	gully	gully	NOUN
esrj-95748	283	2	erosion	erosion	NOUN
esrj-95748	283	3	susceptibility	susceptibility	NOUN
esrj-95748	283	4	assessment	assessment	NOUN
esrj-95748	283	5	and	and	CCONJ
esrj-95748	283	6	management	management	NOUN
esrj-95748	283	7	of	of	ADP
esrj-95748	283	8	hazard	hazard	NOUN
esrj-95748	283	9	-	-	PUNCT
esrj-95748	283	10	prone	prone	ADJ
esrj-95748	283	11	areas	area	NOUN
esrj-95748	283	12	in	in	ADP
esrj-95748	283	13	india	india	PROPN
esrj-95748	283	14	using	use	VERB
esrj-95748	283	15	different	different	ADJ
esrj-95748	283	16	machine	machine	NOUN
esrj-95748	283	17	learning	learn	VERB
esrj-95748	283	18	algorithms	algorithm	NOUN
esrj-95748	283	19	.	.	PUNCT
esrj-95748	284	1	science	science	NOUN
esrj-95748	284	2	of	of	ADP
esrj-95748	284	3	the	the	DET
esrj-95748	284	4	total	total	ADJ
esrj-95748	284	5	environment	environment	NOUN
esrj-95748	284	6	,	,	PUNCT
esrj-95748	284	7	668	668	NUM
esrj-95748	284	8	,	,	PUNCT
esrj-95748	284	9	124	124	NUM
esrj-95748	284	10	-	-	SYM
esrj-95748	284	11	138	138	NUM
esrj-95748	284	12	.	.	PUNCT
esrj-95748	285	1	https://doi.org/10.1016/j.scitotenv.2019.02.436	https://doi.org/10.1016/j.scitotenv.2019.02.436	NOUN
esrj-95748	285	2	garosi	garosi	NOUN
esrj-95748	285	3	,	,	PUNCT
esrj-95748	285	4	y.	y.	PROPN
esrj-95748	285	5	,	,	PUNCT
esrj-95748	285	6	sheklabadi	sheklabadi	NOUN
esrj-95748	285	7	,	,	PUNCT
esrj-95748	285	8	m.	m.	NOUN
esrj-95748	285	9	,	,	PUNCT
esrj-95748	285	10	conoscenti	conoscenti	PROPN
esrj-95748	285	11	,	,	PUNCT
esrj-95748	285	12	c.	c.	PROPN
esrj-95748	285	13	,	,	PUNCT
esrj-95748	285	14	pourghasemi	pourghasemi	PROPN
esrj-95748	285	15	,	,	PUNCT
esrj-95748	285	16	h.	h.	PROPN
esrj-95748	285	17	r.	r.	PROPN
esrj-95748	285	18	,	,	PUNCT
esrj-95748	285	19	&	&	CCONJ
esrj-95748	285	20	van	van	PROPN
esrj-95748	285	21	oost	oost	PROPN
esrj-95748	285	22	,	,	PUNCT
esrj-95748	285	23	k.	k.	PROPN
esrj-95748	285	24	,	,	PUNCT
esrj-95748	285	25	(	(	PUNCT
esrj-95748	285	26	2019	2019	NUM
esrj-95748	285	27	)	)	PUNCT
esrj-95748	285	28	.	.	PUNCT
esrj-95748	286	1	assessing	assess	VERB
esrj-95748	286	2	the	the	DET
esrj-95748	286	3	performance	performance	NOUN
esrj-95748	286	4	of	of	ADP
esrj-95748	286	5	gis	gis	NOUN
esrj-95748	286	6	-	-	PUNCT
esrj-95748	286	7	based	base	VERB
esrj-95748	286	8	machine	machine	NOUN
esrj-95748	286	9	learning	learning	NOUN
esrj-95748	286	10	models	model	NOUN
esrj-95748	286	11	with	with	ADP
esrj-95748	286	12	different	different	ADJ
esrj-95748	286	13	accuracy	accuracy	NOUN
esrj-95748	286	14	measures	measure	NOUN
esrj-95748	286	15	for	for	ADP
esrj-95748	286	16	determining	determine	VERB
esrj-95748	286	17	susceptibility	susceptibility	NOUN
esrj-95748	286	18	to	to	ADP
esrj-95748	286	19	gully	gully	NOUN
esrj-95748	286	20	erosion	erosion	NOUN
esrj-95748	286	21	.	.	PUNCT
esrj-95748	287	1	science	science	NOUN
esrj-95748	287	2	of	of	ADP
esrj-95748	287	3	the	the	DET
esrj-95748	287	4	total	total	ADJ
esrj-95748	287	5	environment	environment	NOUN
esrj-95748	287	6	,	,	PUNCT
esrj-95748	287	7	664	664	NUM
esrj-95748	287	8	,	,	PUNCT
esrj-95748	287	9	1117	1117	NUM
esrj-95748	287	10	-	-	SYM
esrj-95748	287	11	1132	1132	NUM
esrj-95748	287	12	.	.	PUNCT
esrj-95748	288	1	https://doi.org/10.1016/j.scitotenv.2019.02.093	https://doi.org/10.1016/j.scitotenv.2019.02.093	ADJ
esrj-95748	288	2	kalantar	kalantar	NOUN
esrj-95748	288	3	,	,	PUNCT
esrj-95748	288	4	b.	b.	PROPN
esrj-95748	288	5	,	,	PUNCT
esrj-95748	288	6	pradhan	pradhan	PROPN
esrj-95748	288	7	,	,	PUNCT
esrj-95748	288	8	b.	b.	PROPN
esrj-95748	288	9	,	,	PUNCT
esrj-95748	288	10	naghibi	naghibi	ADJ
esrj-95748	288	11	,	,	PUNCT
esrj-95748	288	12	s.a	s.a	PROPN
esrj-95748	288	13	.	.	PROPN
esrj-95748	288	14	,	,	PUNCT
esrj-95748	288	15	motevalli	motevalli	PROPN
esrj-95748	288	16	,	,	PUNCT
esrj-95748	288	17	a.	a.	PROPN
esrj-95748	288	18	,	,	PUNCT
esrj-95748	288	19	&	&	CCONJ
esrj-95748	288	20	mansor	mansor	PROPN
esrj-95748	288	21	,	,	PUNCT
esrj-95748	288	22	s.	s.	PROPN
esrj-95748	288	23	(	(	PUNCT
esrj-95748	288	24	2017	2017	NUM
esrj-95748	288	25	)	)	PUNCT
esrj-95748	288	26	.	.	PUNCT
esrj-95748	289	1	assessment	assessment	NOUN
esrj-95748	289	2	of	of	ADP
esrj-95748	289	3	the	the	DET
esrj-95748	289	4	effects	effect	NOUN
esrj-95748	289	5	of	of	ADP
esrj-95748	289	6	training	training	NOUN
esrj-95748	289	7	data	datum	NOUN
esrj-95748	289	8	selection	selection	NOUN
esrj-95748	289	9	on	on	ADP
esrj-95748	289	10	the	the	DET
esrj-95748	289	11	landslide	landslide	NOUN
esrj-95748	289	12	susceptibility	susceptibility	NOUN
esrj-95748	289	13	mapping	mapping	NOUN
esrj-95748	289	14	:	:	PUNCT
esrj-95748	289	15	a	a	DET
esrj-95748	289	16	comparison	comparison	NOUN
esrj-95748	289	17	between	between	ADP
esrj-95748	289	18	support	support	NOUN
esrj-95748	289	19	vector	vector	NOUN
esrj-95748	289	20	machine	machine	NOUN
esrj-95748	289	21	(	(	PUNCT
esrj-95748	289	22	svm	svm	PROPN
esrj-95748	289	23	)	)	PUNCT
esrj-95748	289	24	,	,	PUNCT
esrj-95748	289	25	logistic	logistic	ADJ
esrj-95748	289	26	regression	regression	NOUN
esrj-95748	289	27	(	(	PUNCT
esrj-95748	289	28	lr	lr	NOUN
esrj-95748	289	29	)	)	PUNCT
esrj-95748	289	30	and	and	CCONJ
esrj-95748	289	31	artificial	artificial	ADJ
esrj-95748	289	32	neural	neural	ADJ
esrj-95748	289	33	networks	network	NOUN
esrj-95748	289	34	(	(	PUNCT
esrj-95748	289	35	ann	ann	PROPN
esrj-95748	289	36	)	)	PUNCT
esrj-95748	289	37	.	.	PUNCT
esrj-95748	290	1	geomatics	geomatics	PROPN
esrj-95748	290	2	,	,	PUNCT
esrj-95748	290	3	natural	natural	ADJ
esrj-95748	290	4	hazards	hazard	NOUN
esrj-95748	290	5	and	and	CCONJ
esrj-95748	290	6	risk	risk	NOUN
esrj-95748	290	7	,	,	PUNCT
esrj-95748	290	8	9(1	9(1	NUM
esrj-95748	290	9	)	)	PUNCT
esrj-95748	290	10	,	,	PUNCT
esrj-95748	290	11	49–69	49–69	NUM
esrj-95748	290	12	.	.	PUNCT
esrj-95748	291	1	https://doi.org/10.1	https://doi.org/10.1	PROPN
esrj-95748	291	2	080/19475705.2017.1407368	080/19475705.2017.1407368	NUM
esrj-95748	291	3	kavzoglu	kavzoglu	PROPN
esrj-95748	291	4	,	,	PUNCT
esrj-95748	291	5	t.	t.	PROPN
esrj-95748	291	6	,	,	PUNCT
esrj-95748	291	7	sahin	sahin	PROPN
esrj-95748	291	8	,	,	PUNCT
esrj-95748	291	9	e.k	e.k	PROPN
esrj-95748	291	10	.	.	PROPN
esrj-95748	291	11	&	&	CCONJ
esrj-95748	291	12	colkesen	colkesen	PROPN
esrj-95748	291	13	,	,	PUNCT
esrj-95748	291	14	i.	i.	NOUN
esrj-95748	291	15	(	(	PUNCT
esrj-95748	291	16	2013	2013	NUM
esrj-95748	291	17	)	)	PUNCT
esrj-95748	291	18	.	.	PUNCT
esrj-95748	292	1	landslide	landslide	NOUN
esrj-95748	292	2	susceptibility	susceptibility	NOUN
esrj-95748	292	3	mapping	mapping	NOUN
esrj-95748	292	4	using	use	VERB
esrj-95748	292	5	gis	gis	NOUN
esrj-95748	292	6	-	-	PUNCT
esrj-95748	292	7	based	base	VERB
esrj-95748	292	8	multi	multi	ADJ
esrj-95748	292	9	-	-	ADJ
esrj-95748	292	10	criteria	criterion	NOUN
esrj-95748	292	11	decision	decision	NOUN
esrj-95748	292	12	analysis	analysis	NOUN
esrj-95748	292	13	,	,	PUNCT
esrj-95748	292	14	support	support	NOUN
esrj-95748	292	15	vector	vector	NOUN
esrj-95748	292	16	machines	machine	NOUN
esrj-95748	292	17	,	,	PUNCT
esrj-95748	292	18	and	and	CCONJ
esrj-95748	292	19	logistic	logistic	ADJ
esrj-95748	292	20	regression	regression	NOUN
esrj-95748	292	21	.	.	PUNCT
esrj-95748	293	1	landslides	landslide	NOUN
esrj-95748	293	2	,	,	PUNCT
esrj-95748	293	3	11(3	11(3	NUM
esrj-95748	293	4	)	)	PUNCT
esrj-95748	293	5	,	,	PUNCT
esrj-95748	293	6	425–439	425–439	NUM
esrj-95748	293	7	.	.	PUNCT
esrj-95748	294	1	https://	https://	PROPN
esrj-95748	294	2	doi.org/10.1007/s10346-013-0391-7	doi.org/10.1007/s10346-013-0391-7	PROPN
esrj-95748	294	3	https://doi.org/10.3390/rs12111890	https://doi.org/10.3390/rs12111890	PROPN
esrj-95748	295	1	https://doi.org/10.1002/ldr.3151	https://doi.org/10.1002/ldr.3151	PROPN
esrj-95748	295	2	https://doi.org/10.1016/j.geoderma.2018.12.042	https://doi.org/10.1016/j.geoderma.2018.12.042	PROPN
esrj-95748	295	3	https://doi.org/10.1016/j.geoderma.2018.12.042	https://doi.org/10.1016/j.geoderma.2018.12.042	NUM
esrj-95748	295	4	http://dx.doi.org/10.1016/j.ecolmodel.2010.01.007	http://dx.doi.org/10.1016/j.ecolmodel.2010.01.007	PROPN
esrj-95748	295	5	https://doi.org/10.1016/j.catena.2013.10.011	https://doi.org/10.1016/j.catena.2013.10.011	PROPN
esrj-95748	295	6	https://doi.org/10.1016/j.catena.2013.10.011	https://doi.org/10.1016/j.catena.2013.10.011	PROPN
esrj-95748	295	7	https://doi.org/10.1016/j.geoderma.2005.04.025	https://doi.org/10.1016/j.geoderma.2005.04.025	PROPN
esrj-95748	295	8	https://doi.org/10.1016/j.geoderma.2005.04.025	https://doi.org/10.1016/j.geoderma.2005.04.025	PROPN
esrj-95748	295	9	http://dx.doi.org/10.1007/s11053-005-4678-9	http://dx.doi.org/10.1007/s11053-005-4678-9	PROPN
esrj-95748	295	10	https://doi.org/10.1016/j.geomorph.2013.08.021	https://doi.org/10.1016/j.geomorph.2013.08.021	PROPN
esrj-95748	295	11	https://doi.org/10.1016/j.catena.2005.06.003	https://doi.org/10.1016/j.catena.2005.06.003	PROPN
esrj-95748	295	12	https://doi.org/10.1016/j.catena.2005.06.003	https://doi.org/10.1016/j.catena.2005.06.003	PROPN
esrj-95748	295	13	https://doi.org/10.1016/j.jenvman.2021.112015	https://doi.org/10.1016/j.jenvman.2021.112015	PROPN
esrj-95748	295	14	http://dx.doi.org/10.1111/j.1365-2656.2008.01390.x	http://dx.doi.org/10.1111/j.1365-2656.2008.01390.x	NOUN
esrj-95748	295	15	http://dx.doi.org/10.1111/j.1365-2656.2008.01390.x	http://dx.doi.org/10.1111/j.1365-2656.2008.01390.x	NOUN
esrj-95748	295	16	https://doi.org/10.1016/j.jenvman.2011.09.010	https://doi.org/10.1016/j.jenvman.2011.09.010	NOUN
esrj-95748	295	17	https://doi.org/10.1007/s00267-016-0671-9	https://doi.org/10.1007/s00267-016-0671-9	NUM
esrj-95748	295	18	https://doi.org/10.1016/j.scitotenv.2019.02.436	https://doi.org/10.1016/j.scitotenv.2019.02.436	NOUN
esrj-95748	295	19	https://doi.org/10.1016/j.scitotenv.2019.02.436	https://doi.org/10.1016/j.scitotenv.2019.02.436	NOUN
esrj-95748	295	20	https://doi.org/10.1016/j.scitotenv.2019.02.093	https://doi.org/10.1016/j.scitotenv.2019.02.093	PROPN
esrj-95748	295	21	https://doi.org/10.1016/j.scitotenv.2019.02.093	https://doi.org/10.1016/j.scitotenv.2019.02.093	PROPN
esrj-95748	295	22	https://doi.org/10.1080/19475705.2017.1407368	https://doi.org/10.1080/19475705.2017.1407368	PUNCT
esrj-95748	296	1	https://doi.org/10.1080/19475705.2017.1407368	https://doi.org/10.1080/19475705.2017.1407368	PROPN
esrj-95748	297	1	https://doi.org/10.1007/s10346-013-0391-7	https://doi.org/10.1007/s10346-013-0391-7	NUM
esrj-95748	297	2	https://doi.org/10.1007/s10346-013-0391-7	https://doi.org/10.1007/s10346-013-0391-7	NUM
esrj-95748	297	3	432	432	NUM
esrj-95748	297	4	mahdieh	mahdieh	PROPN
esrj-95748	297	5	valipour	valipour	ADJ
esrj-95748	297	6	,	,	PUNCT
esrj-95748	297	7	neda	neda	PROPN
esrj-95748	297	8	mohseni	mohseni	NOUN
esrj-95748	297	9	,	,	PUNCT
esrj-95748	297	10	seyed	seyed	PROPN
esrj-95748	297	11	reza	reza	PROPN
esrj-95748	297	12	hosseinzadeh	hosseinzadeh	PROPN
esrj-95748	297	13	kursa	kursa	PROPN
esrj-95748	297	14	,	,	PUNCT
esrj-95748	297	15	m.	m.	PROPN
esrj-95748	297	16	b.	b.	PROPN
esrj-95748	297	17	,	,	PUNCT
esrj-95748	297	18	jankowski	jankowski	PROPN
esrj-95748	297	19	,	,	PUNCT
esrj-95748	297	20	a.	a.	PROPN
esrj-95748	297	21	,	,	PUNCT
esrj-95748	297	22	&	&	CCONJ
esrj-95748	297	23	rudnicki	rudnicki	PROPN
esrj-95748	297	24	,	,	PUNCT
esrj-95748	297	25	w.	w.	PROPN
esrj-95748	297	26	r.	r.	PROPN
esrj-95748	297	27	(	(	PUNCT
esrj-95748	297	28	2010	2010	NUM
esrj-95748	297	29	)	)	PUNCT
esrj-95748	297	30	.	.	PUNCT
esrj-95748	298	1	boruta	boruta	PROPN
esrj-95748	298	2	–	–	PUNCT
esrj-95748	298	3	a	a	DET
esrj-95748	298	4	system	system	NOUN
esrj-95748	298	5	for	for	ADP
esrj-95748	298	6	feature	feature	NOUN
esrj-95748	298	7	selection	selection	NOUN
esrj-95748	298	8	.	.	PUNCT
esrj-95748	299	1	fundamenta	fundamenta	PROPN
esrj-95748	299	2	informaticae	informaticae	PROPN
esrj-95748	299	3	,	,	PUNCT
esrj-95748	299	4	101(4	101(4	NUM
esrj-95748	299	5	)	)	PUNCT
esrj-95748	299	6	,	,	PUNCT
esrj-95748	299	7	271–285	271–285	NUM
esrj-95748	299	8	.	.	PUNCT
esrj-95748	300	1	https://	https://	PROPN
esrj-95748	300	2	doi.org/10.3233/fi-2010-288	doi.org/10.3233/fi-2010-288	PROPN
esrj-95748	300	3	liaw	liaw	PROPN
esrj-95748	300	4	,	,	PUNCT
esrj-95748	300	5	a.	a.	NOUN
esrj-95748	300	6	,	,	PUNCT
esrj-95748	300	7	&	&	CCONJ
esrj-95748	300	8	wiener	wiener	NOUN
esrj-95748	300	9	,	,	PUNCT
esrj-95748	300	10	m.	m.	NOUN
esrj-95748	300	11	(	(	PUNCT
esrj-95748	300	12	2002	2002	NUM
esrj-95748	300	13	)	)	PUNCT
esrj-95748	300	14	.	.	PUNCT
esrj-95748	301	1	classification	classification	NOUN
esrj-95748	301	2	and	and	CCONJ
esrj-95748	301	3	regression	regression	NOUN
esrj-95748	301	4	by	by	ADP
esrj-95748	301	5	randomforest	randomfor	ADJ
esrj-95748	301	6	.	.	PUNCT
esrj-95748	302	1	forest	forest	NOUN
esrj-95748	302	2	,	,	PUNCT
esrj-95748	302	3	2(3	2(3	NUM
esrj-95748	302	4	)	)	PUNCT
esrj-95748	302	5	,	,	PUNCT
esrj-95748	302	6	18–22	18–22	NUM
esrj-95748	302	7	.	.	PUNCT
esrj-95748	302	8	lei	lei	PROPN
esrj-95748	302	9	,	,	PUNCT
esrj-95748	302	10	x.	x.	PROPN
esrj-95748	302	11	,	,	PUNCT
esrj-95748	302	12	chen	chen	PROPN
esrj-95748	302	13	,	,	PUNCT
esrj-95748	302	14	w.	w.	PROPN
esrj-95748	302	15	,	,	PUNCT
esrj-95748	302	16	avand	avand	PROPN
esrj-95748	302	17	,	,	PUNCT
esrj-95748	302	18	m.	m.	NOUN
esrj-95748	302	19	,	,	PUNCT
esrj-95748	302	20	janizadeh	janizadeh	PROPN
esrj-95748	302	21	,	,	PUNCT
esrj-95748	302	22	s.	s.	PROPN
esrj-95748	302	23	,	,	PUNCT
esrj-95748	302	24	kariminejad	kariminejad	PROPN
esrj-95748	302	25	,	,	PUNCT
esrj-95748	302	26	n.	n.	NOUN
esrj-95748	302	27	,	,	PUNCT
esrj-95748	302	28	shahabi	shahabi	NOUN
esrj-95748	302	29	,	,	PUNCT
esrj-95748	302	30	h.	h.	PROPN
esrj-95748	302	31	,	,	PUNCT
esrj-95748	302	32	&	&	CCONJ
esrj-95748	302	33	mosavi	mosavi	PROPN
esrj-95748	302	34	,	,	PUNCT
esrj-95748	302	35	a.	a.	NOUN
esrj-95748	302	36	(	(	PUNCT
esrj-95748	302	37	2020	2020	NUM
esrj-95748	302	38	)	)	PUNCT
esrj-95748	302	39	.	.	PUNCT
esrj-95748	303	1	gis	gis	NOUN
esrj-95748	303	2	-	-	PUNCT
esrj-95748	303	3	based	base	VERB
esrj-95748	303	4	machine	machine	NOUN
esrj-95748	303	5	learning	learn	VERB
esrj-95748	303	6	algorithms	algorithm	NOUN
esrj-95748	303	7	for	for	ADP
esrj-95748	303	8	gully	gully	NOUN
esrj-95748	303	9	erosion	erosion	NOUN
esrj-95748	303	10	susceptibility	susceptibility	NOUN
esrj-95748	303	11	mapping	mapping	NOUN
esrj-95748	303	12	in	in	ADP
esrj-95748	303	13	a	a	DET
esrj-95748	303	14	semi	semi	ADJ
esrj-95748	303	15	-	-	ADJ
esrj-95748	303	16	arid	arid	ADJ
esrj-95748	303	17	region	region	NOUN
esrj-95748	303	18	of	of	ADP
esrj-95748	303	19	iran	iran	PROPN
esrj-95748	303	20	.	.	PUNCT
esrj-95748	304	1	remote	remote	ADJ
esrj-95748	304	2	sensing	sensing	NOUN
esrj-95748	304	3	,	,	PUNCT
esrj-95748	304	4	12	12	NUM
esrj-95748	304	5	,	,	PUNCT
esrj-95748	304	6	1	1	NUM
esrj-95748	304	7	-	-	SYM
esrj-95748	304	8	25	25	NUM
esrj-95748	304	9	.	.	PUNCT
esrj-95748	305	1	https://doi.org/10.3390/rs12152478	https://doi.org/10.3390/rs12152478	PROPN
esrj-95748	305	2	lee	lee	PROPN
esrj-95748	305	3	,	,	PUNCT
esrj-95748	305	4	m.	m.	PROPN
esrj-95748	305	5	j.	j.	PROPN
esrj-95748	305	6	,	,	PUNCT
esrj-95748	305	7	choi	choi	PROPN
esrj-95748	305	8	,	,	PUNCT
esrj-95748	305	9	j.	j.	PROPN
esrj-95748	305	10	w.	w.	PROPN
esrj-95748	305	11	,	,	PUNCT
esrj-95748	305	12	oh	oh	INTJ
esrj-95748	305	13	,	,	PUNCT
esrj-95748	305	14	h.	h.	PROPN
esrj-95748	305	15	j.	j.	PROPN
esrj-95748	305	16	,	,	PUNCT
esrj-95748	305	17	won	win	VERB
esrj-95748	305	18	,	,	PUNCT
esrj-95748	305	19	j.	j.	PROPN
esrj-95748	305	20	s.	s.	PROPN
esrj-95748	305	21	,	,	PUNCT
esrj-95748	305	22	park	park	PROPN
esrj-95748	305	23	,	,	PUNCT
esrj-95748	305	24	i.	i.	PROPN
esrj-95748	305	25	,	,	PUNCT
esrj-95748	305	26	&	&	CCONJ
esrj-95748	305	27	lee	lee	PROPN
esrj-95748	305	28	,	,	PUNCT
esrj-95748	305	29	s.	s.	PROPN
esrj-95748	305	30	(	(	PUNCT
esrj-95748	305	31	2012	2012	NUM
esrj-95748	305	32	)	)	PUNCT
esrj-95748	305	33	.	.	PUNCT
esrj-95748	306	1	ensemble	ensemble	ADJ
esrj-95748	306	2	based	base	VERB
esrj-95748	306	3	landslide	landslide	NOUN
esrj-95748	306	4	susceptibility	susceptibility	NOUN
esrj-95748	306	5	maps	map	NOUN
esrj-95748	306	6	in	in	ADP
esrj-95748	306	7	jinbu	jinbu	PROPN
esrj-95748	306	8	area	area	PROPN
esrj-95748	306	9	,	,	PUNCT
esrj-95748	306	10	korea	korea	PROPN
esrj-95748	306	11	.	.	PUNCT
esrj-95748	307	1	environmental	environmental	ADJ
esrj-95748	307	2	earth	earth	PROPN
esrj-95748	307	3	sciences	sciences	PROPN
esrj-95748	307	4	,	,	PUNCT
esrj-95748	307	5	67	67	NUM
esrj-95748	307	6	,	,	PUNCT
esrj-95748	307	7	23–37	23–37	NOUN
esrj-95748	307	8	.	.	PUNCT
esrj-95748	308	1	https://doi.org/10.1007/s12665-011-1477-y	https://doi.org/10.1007/s12665-011-1477-y	PROPN
esrj-95748	308	2	micheletti	micheletti	ADJ
esrj-95748	308	3	,	,	PUNCT
esrj-95748	308	4	n.	n.	NOUN
esrj-95748	308	5	,	,	PUNCT
esrj-95748	308	6	foresti	foresti	NOUN
esrj-95748	308	7	,	,	PUNCT
esrj-95748	308	8	l.	l.	PROPN
esrj-95748	308	9	,	,	PUNCT
esrj-95748	308	10	robert	robert	PROPN
esrj-95748	308	11	,	,	PUNCT
esrj-95748	308	12	s.	s.	PROPN
esrj-95748	308	13	,	,	PUNCT
esrj-95748	308	14	leuenberger	leuenberger	ADV
esrj-95748	308	15	,	,	PUNCT
esrj-95748	308	16	m.	m.	NOUN
esrj-95748	308	17	,	,	PUNCT
esrj-95748	308	18	pedrazzini	pedrazzini	NOUN
esrj-95748	308	19	,	,	PUNCT
esrj-95748	308	20	a.	a.	NOUN
esrj-95748	308	21	,	,	PUNCT
esrj-95748	308	22	jaboyedoff	jaboyedoff	PROPN
esrj-95748	308	23	,	,	PUNCT
esrj-95748	308	24	m.	m.	NOUN
esrj-95748	308	25	,	,	PUNCT
esrj-95748	308	26	&	&	CCONJ
esrj-95748	308	27	kanevski	kanevski	PROPN
esrj-95748	308	28	,	,	PUNCT
esrj-95748	308	29	m.	m.	NOUN
esrj-95748	308	30	(	(	PUNCT
esrj-95748	308	31	2014	2014	NUM
esrj-95748	308	32	)	)	PUNCT
esrj-95748	308	33	.	.	PUNCT
esrj-95748	309	1	machine	machine	NOUN
esrj-95748	309	2	learning	learn	VERB
esrj-95748	309	3	feature	feature	NOUN
esrj-95748	309	4	selection	selection	NOUN
esrj-95748	309	5	methods	method	NOUN
esrj-95748	309	6	for	for	ADP
esrj-95748	309	7	landslide	landslide	NOUN
esrj-95748	309	8	susceptibility	susceptibility	NOUN
esrj-95748	309	9	mapping	mapping	NOUN
esrj-95748	309	10	.	.	PUNCT
esrj-95748	310	1	mathematical	mathematical	ADJ
esrj-95748	310	2	geosciences	geoscience	NOUN
esrj-95748	310	3	,	,	PUNCT
esrj-95748	310	4	46(1	46(1	PROPN
esrj-95748	310	5	)	)	PUNCT
esrj-95748	310	6	,	,	PUNCT
esrj-95748	310	7	33–57	33–57	NUM
esrj-95748	310	8	.	.	PUNCT
esrj-95748	311	1	http://dx.doi.org/10.1007/s11004-013-9511-0	http://dx.doi.org/10.1007/s11004-013-9511-0	PROPN
esrj-95748	311	2	moore	moore	PROPN
esrj-95748	311	3	,	,	PUNCT
esrj-95748	311	4	i.	i.	PROPN
esrj-95748	311	5	d.	d.	PROPN
esrj-95748	311	6	,	,	PUNCT
esrj-95748	311	7	gessler	gessler	NOUN
esrj-95748	311	8	,	,	PUNCT
esrj-95748	311	9	p.	p.	PROPN
esrj-95748	311	10	e.	e.	PROPN
esrj-95748	311	11	,	,	PUNCT
esrj-95748	311	12	nielsen	nielsen	PROPN
esrj-95748	311	13	,	,	PUNCT
esrj-95748	311	14	g.	g.	PROPN
esrj-95748	311	15	a.	a.	PROPN
esrj-95748	311	16	e.	e.	PROPN
esrj-95748	311	17	&	&	CCONJ
esrj-95748	311	18	peterson	peterson	PROPN
esrj-95748	311	19	,	,	PUNCT
esrj-95748	311	20	g.	g.	PROPN
esrj-95748	311	21	a.	a.	PROPN
esrj-95748	311	22	(	(	PUNCT
esrj-95748	311	23	1993	1993	NUM
esrj-95748	311	24	)	)	PUNCT
esrj-95748	311	25	.	.	PUNCT
esrj-95748	312	1	soil	soil	NOUN
esrj-95748	312	2	attribute	attribute	NOUN
esrj-95748	312	3	prediction	prediction	NOUN
esrj-95748	312	4	using	use	VERB
esrj-95748	312	5	terrain	terrain	NOUN
esrj-95748	312	6	analysis	analysis	NOUN
esrj-95748	312	7	.	.	PUNCT
esrj-95748	313	1	soil	soil	NOUN
esrj-95748	313	2	science	science	PROPN
esrj-95748	313	3	society	society	PROPN
esrj-95748	313	4	of	of	ADP
esrj-95748	313	5	america	america	PROPN
esrj-95748	313	6	journal	journal	PROPN
esrj-95748	313	7	,	,	PUNCT
esrj-95748	313	8	57(2	57(2	NUM
esrj-95748	313	9	)	)	PUNCT
esrj-95748	313	10	,	,	PUNCT
esrj-95748	313	11	443–452	443–452	NUM
esrj-95748	313	12	.	.	PUNCT
esrj-95748	314	1	https://doi.org/10.2136/sssaj1993.03615995005700020026x	https://doi.org/10.2136/sssaj1993.03615995005700020026x	NOUN
esrj-95748	314	2	marjanović	marjanović	NOUN
esrj-95748	314	3	,	,	PUNCT
esrj-95748	314	4	m.	m.	NOUN
esrj-95748	314	5	,	,	PUNCT
esrj-95748	314	6	kovačević	kovačević	NOUN
esrj-95748	314	7	,	,	PUNCT
esrj-95748	314	8	m.	m.	NOUN
esrj-95748	314	9	,	,	PUNCT
esrj-95748	314	10	bajat	bajat	PROPN
esrj-95748	314	11	,	,	PUNCT
esrj-95748	314	12	b.	b.	PROPN
esrj-95748	314	13	&	&	CCONJ
esrj-95748	314	14	voženílek	voženílek	PROPN
esrj-95748	314	15	,	,	PUNCT
esrj-95748	314	16	v.	v.	PROPN
esrj-95748	314	17	(	(	PUNCT
esrj-95748	314	18	2011	2011	NUM
esrj-95748	314	19	)	)	PUNCT
esrj-95748	314	20	.	.	PUNCT
esrj-95748	315	1	landslide	landslide	NOUN
esrj-95748	315	2	susceptibility	susceptibility	NOUN
esrj-95748	315	3	assessment	assessment	NOUN
esrj-95748	315	4	using	use	VERB
esrj-95748	315	5	svm	svm	ADJ
esrj-95748	315	6	machine	machine	NOUN
esrj-95748	315	7	learning	learning	NOUN
esrj-95748	315	8	algorithm	algorithm	NOUN
esrj-95748	315	9	.	.	PUNCT
esrj-95748	316	1	engineering	engineering	NOUN
esrj-95748	316	2	geology	geology	NOUN
esrj-95748	316	3	,	,	PUNCT
esrj-95748	316	4	123(3	123(3	NUM
esrj-95748	316	5	)	)	PUNCT
esrj-95748	316	6	,	,	PUNCT
esrj-95748	316	7	225–234	225–234	NUM
esrj-95748	316	8	.	.	PUNCT
esrj-95748	317	1	https://doi.org/10.1016/j.enggeo.2011.09.006	https://doi.org/10.1016/j.enggeo.2011.09.006	NOUN
esrj-95748	317	2	naghibi	naghibi	ADJ
esrj-95748	317	3	,	,	PUNCT
esrj-95748	317	4	s.	s.	PROPN
esrj-95748	317	5	a.	a.	PROPN
esrj-95748	317	6	,	,	PUNCT
esrj-95748	317	7	pourghasemi	pourghasemi	PROPN
esrj-95748	317	8	,	,	PUNCT
esrj-95748	317	9	h.	h.	PROPN
esrj-95748	317	10	r.	r.	PROPN
esrj-95748	317	11	&	&	CCONJ
esrj-95748	317	12	dixon	dixon	PROPN
esrj-95748	317	13	,	,	PUNCT
esrj-95748	317	14	b.	b.	PROPN
esrj-95748	317	15	(	(	PUNCT
esrj-95748	317	16	2015	2015	NUM
esrj-95748	317	17	)	)	PUNCT
esrj-95748	317	18	.	.	PUNCT
esrj-95748	318	1	gis	gis	NOUN
esrj-95748	318	2	-	-	PUNCT
esrj-95748	318	3	based	base	VERB
esrj-95748	318	4	groundwater	groundwater	NOUN
esrj-95748	318	5	potential	potential	ADJ
esrj-95748	318	6	mapping	mapping	NOUN
esrj-95748	318	7	using	use	VERB
esrj-95748	318	8	boosted	boost	VERB
esrj-95748	318	9	regression	regression	NOUN
esrj-95748	318	10	tree	tree	NOUN
esrj-95748	318	11	,	,	PUNCT
esrj-95748	318	12	classification	classification	NOUN
esrj-95748	318	13	and	and	CCONJ
esrj-95748	318	14	regression	regression	NOUN
esrj-95748	318	15	tree	tree	NOUN
esrj-95748	318	16	,	,	PUNCT
esrj-95748	318	17	and	and	CCONJ
esrj-95748	318	18	random	random	ADJ
esrj-95748	318	19	forest	forest	NOUN
esrj-95748	318	20	machine	machine	NOUN
esrj-95748	318	21	learning	learning	NOUN
esrj-95748	318	22	models	model	NOUN
esrj-95748	318	23	in	in	ADP
esrj-95748	318	24	iran	iran	PROPN
esrj-95748	318	25	.	.	PUNCT
esrj-95748	319	1	environmental	environmental	ADJ
esrj-95748	319	2	monitoring	monitoring	NOUN
esrj-95748	319	3	and	and	CCONJ
esrj-95748	319	4	assessment	assessment	NOUN
esrj-95748	319	5	,	,	PUNCT
esrj-95748	319	6	188(1	188(1	NUM
esrj-95748	319	7	)	)	PUNCT
esrj-95748	319	8	,	,	PUNCT
esrj-95748	319	9	1	1	NUM
esrj-95748	319	10	-	-	SYM
esrj-95748	319	11	27	27	NUM
esrj-95748	319	12	.	.	PUNCT
esrj-95748	320	1	https://dx.doi	https://dx.doi	NOUN
esrj-95748	320	2	.	.	PUNCT
esrj-95748	321	1	org/10.1007	org/10.1007	PROPN
esrj-95748	321	2	/	/	SYM
esrj-95748	321	3	s10661	s10661	PROPN
esrj-95748	321	4	-	-	PUNCT
esrj-95748	321	5	015	015	NUM
esrj-95748	321	6	-	-	PUNCT
esrj-95748	321	7	5049	5049	NUM
esrj-95748	321	8	-	-	SYM
esrj-95748	321	9	6	6	NUM
esrj-95748	321	10	ollobarren	ollobarren	NOUN
esrj-95748	321	11	,	,	PUNCT
esrj-95748	321	12	p.	p.	PROPN
esrj-95748	321	13	,	,	PUNCT
esrj-95748	321	14	capra	capra	PROPN
esrj-95748	321	15	,	,	PUNCT
esrj-95748	321	16	a.	a.	NOUN
esrj-95748	321	17	,	,	PUNCT
esrj-95748	321	18	gelsomino	gelsomino	NOUN
esrj-95748	321	19	,	,	PUNCT
esrj-95748	321	20	a.	a.	NOUN
esrj-95748	321	21	,	,	PUNCT
esrj-95748	321	22	&	&	CCONJ
esrj-95748	321	23	la	la	PROPN
esrj-95748	321	24	spada	spada	PROPN
esrj-95748	321	25	,	,	PUNCT
esrj-95748	321	26	c.	c.	PROPN
esrj-95748	321	27	,	,	PUNCT
esrj-95748	321	28	(	(	PUNCT
esrj-95748	321	29	2016	2016	NUM
esrj-95748	321	30	)	)	PUNCT
esrj-95748	321	31	.	.	PUNCT
esrj-95748	322	1	effects	effect	NOUN
esrj-95748	322	2	of	of	ADP
esrj-95748	322	3	ephemeral	ephemeral	ADJ
esrj-95748	322	4	gully	gully	NOUN
esrj-95748	322	5	erosion	erosion	NOUN
esrj-95748	322	6	on	on	ADP
esrj-95748	322	7	soil	soil	NOUN
esrj-95748	322	8	degradation	degradation	NOUN
esrj-95748	322	9	in	in	ADP
esrj-95748	322	10	a	a	DET
esrj-95748	322	11	cultivated	cultivate	VERB
esrj-95748	322	12	area	area	NOUN
esrj-95748	322	13	in	in	ADP
esrj-95748	322	14	sicily	sicily	PROPN
esrj-95748	322	15	(	(	PUNCT
esrj-95748	322	16	italy	italy	PROPN
esrj-95748	322	17	)	)	PUNCT
esrj-95748	322	18	.	.	PUNCT
esrj-95748	323	1	catena	catena	PROPN
esrj-95748	323	2	,	,	PUNCT
esrj-95748	323	3	145	145	NUM
esrj-95748	323	4	,	,	PUNCT
esrj-95748	323	5	334	334	NUM
esrj-95748	323	6	-	-	SYM
esrj-95748	323	7	345	345	NUM
esrj-95748	323	8	.	.	PUNCT
esrj-95748	324	1	https://doi.org/10.1016/j.catena.2016.06.031	https://doi.org/10.1016/j.catena.2016.06.031	ADJ
esrj-95748	324	2	park	park	NOUN
esrj-95748	324	3	,	,	PUNCT
esrj-95748	324	4	n.	n.	PROPN
esrj-95748	324	5	w.	w.	PROPN
esrj-95748	324	6	(	(	PUNCT
esrj-95748	324	7	2011	2011	NUM
esrj-95748	324	8	)	)	PUNCT
esrj-95748	324	9	.	.	PUNCT
esrj-95748	325	1	application	application	NOUN
esrj-95748	325	2	of	of	ADP
esrj-95748	325	3	dempster	dempster	PROPN
esrj-95748	325	4	-	-	PUNCT
esrj-95748	325	5	shafer	shafer	PROPN
esrj-95748	325	6	theory	theory	NOUN
esrj-95748	325	7	of	of	ADP
esrj-95748	325	8	evidence	evidence	NOUN
esrj-95748	325	9	to	to	ADP
esrj-95748	325	10	gis	gis	NOUN
esrj-95748	325	11	-	-	PUNCT
esrj-95748	325	12	based	base	VERB
esrj-95748	325	13	land	land	NOUN
esrj-95748	325	14	slide	slide	NOUN
esrj-95748	325	15	susceptibility	susceptibility	NOUN
esrj-95748	325	16	analysis	analysis	NOUN
esrj-95748	325	17	.	.	PUNCT
esrj-95748	326	1	environmental	environmental	ADJ
esrj-95748	326	2	earth	earth	NOUN
esrj-95748	326	3	sciences	sciences	PROPN
esrj-95748	326	4	,	,	PUNCT
esrj-95748	326	5	62(2	62(2	NOUN
esrj-95748	326	6	)	)	PUNCT
esrj-95748	326	7	,	,	PUNCT
esrj-95748	326	8	367–376	367–376	NUM
esrj-95748	326	9	.	.	PUNCT
esrj-95748	327	1	https://doi.org/10.1007/s12665-010-0531-5	https://doi.org/10.1007/s12665-010-0531-5	NUM
esrj-95748	327	2	pradhan	pradhan	PROPN
esrj-95748	327	3	,	,	PUNCT
esrj-95748	327	4	b.	b.	PROPN
esrj-95748	327	5	(	(	PUNCT
esrj-95748	327	6	2013	2013	NUM
esrj-95748	327	7	)	)	PUNCT
esrj-95748	327	8	.	.	PUNCT
esrj-95748	328	1	a	a	DET
esrj-95748	328	2	comparative	comparative	ADJ
esrj-95748	328	3	study	study	NOUN
esrj-95748	328	4	on	on	ADP
esrj-95748	328	5	the	the	DET
esrj-95748	328	6	predictive	predictive	ADJ
esrj-95748	328	7	ability	ability	NOUN
esrj-95748	328	8	of	of	ADP
esrj-95748	328	9	the	the	DET
esrj-95748	328	10	decision	decision	NOUN
esrj-95748	328	11	tree	tree	NOUN
esrj-95748	328	12	,	,	PUNCT
esrj-95748	328	13	support	support	VERB
esrj-95748	328	14	vector	vector	NOUN
esrj-95748	328	15	machine	machine	NOUN
esrj-95748	328	16	and	and	CCONJ
esrj-95748	328	17	neuro	neuro	NOUN
esrj-95748	328	18	-	-	PUNCT
esrj-95748	328	19	fuzzy	fuzzy	ADJ
esrj-95748	328	20	models	model	NOUN
esrj-95748	328	21	in	in	ADP
esrj-95748	328	22	landslide	landslide	NOUN
esrj-95748	328	23	susceptibility	susceptibility	NOUN
esrj-95748	328	24	mapping	mapping	NOUN
esrj-95748	328	25	using	use	VERB
esrj-95748	328	26	gis	gis	PROPN
esrj-95748	328	27	.	.	PUNCT
esrj-95748	329	1	computers	computer	NOUN
esrj-95748	329	2	&	&	CCONJ
esrj-95748	329	3	geosciences	geoscience	NOUN
esrj-95748	329	4	,	,	PUNCT
esrj-95748	329	5	51	51	NUM
esrj-95748	329	6	,	,	PUNCT
esrj-95748	329	7	350–365	350–365	NUM
esrj-95748	329	8	.	.	PUNCT
esrj-95748	330	1	https://doi.org/10.1016/j.cageo.2012.08.023	https://doi.org/10.1016/j.cageo.2012.08.023	NOUN
esrj-95748	330	2	pourghasemi	pourghasemi	NOUN
esrj-95748	330	3	,	,	PUNCT
esrj-95748	330	4	h.	h.	PROPN
esrj-95748	330	5	r.	r.	PROPN
esrj-95748	330	6	,	,	PUNCT
esrj-95748	330	7	yousefi	yousefi	PROPN
esrj-95748	330	8	,	,	PUNCT
esrj-95748	330	9	s.	s.	PROPN
esrj-95748	330	10	,	,	PUNCT
esrj-95748	330	11	kornejady	kornejady	PROPN
esrj-95748	330	12	,	,	PUNCT
esrj-95748	330	13	a.	a.	PROPN
esrj-95748	330	14	&	&	CCONJ
esrj-95748	330	15	cerda	cerda	PROPN
esrj-95748	330	16	,	,	PUNCT
esrj-95748	330	17	a.	a.	NOUN
esrj-95748	330	18	(	(	PUNCT
esrj-95748	330	19	2017	2017	NUM
esrj-95748	330	20	)	)	PUNCT
esrj-95748	330	21	.	.	PUNCT
esrj-95748	331	1	applying	apply	VERB
esrj-95748	331	2	different	different	ADJ
esrj-95748	331	3	new	new	ADJ
esrj-95748	331	4	ensemble	ensemble	ADJ
esrj-95748	331	5	data	datum	NOUN
esrj-95748	331	6	mining	mining	NOUN
esrj-95748	331	7	techniques	technique	NOUN
esrj-95748	331	8	for	for	ADP
esrj-95748	331	9	gully	gully	ADJ
esrj-95748	331	10	erosion	erosion	NOUN
esrj-95748	331	11	mapping	mapping	NOUN
esrj-95748	331	12	with	with	ADP
esrj-95748	331	13	geographical	geographical	ADJ
esrj-95748	331	14	information	information	NOUN
esrj-95748	331	15	systems	system	NOUN
esrj-95748	331	16	.	.	PUNCT
esrj-95748	332	1	science	science	NOUN
esrj-95748	332	2	of	of	ADP
esrj-95748	332	3	the	the	DET
esrj-95748	332	4	total	total	ADJ
esrj-95748	332	5	environment	environment	NOUN
esrj-95748	332	6	,	,	PUNCT
esrj-95748	332	7	609	609	NUM
esrj-95748	332	8	,	,	PUNCT
esrj-95748	332	9	764–775	764–775	NUM
esrj-95748	332	10	.	.	PUNCT
esrj-95748	333	1	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
esrj-95748	333	2	.	.	PUNCT
esrj-95748	334	1	scitotenv.2017.07.198	scitotenv.2017.07.198	ADJ
esrj-95748	334	2	pourghasemi	pourghasemi	NOUN
esrj-95748	334	3	,	,	PUNCT
esrj-95748	334	4	h.	h.	PROPN
esrj-95748	334	5	r.	r.	PROPN
esrj-95748	334	6	,	,	PUNCT
esrj-95748	334	7	sadhasivam	sadhasivam	NOUN
esrj-95748	334	8	,	,	PUNCT
esrj-95748	334	9	n.	n.	NOUN
esrj-95748	334	10	,	,	PUNCT
esrj-95748	334	11	kariminejad	kariminejad	PROPN
esrj-95748	334	12	,	,	PUNCT
esrj-95748	334	13	n.	n.	NOUN
esrj-95748	334	14	,	,	PUNCT
esrj-95748	334	15	&	&	CCONJ
esrj-95748	334	16	collins	collins	PROPN
esrj-95748	334	17	,	,	PUNCT
esrj-95748	334	18	a.	a.	PROPN
esrj-95748	334	19	l.	l.	PROPN
esrj-95748	334	20	(	(	PUNCT
esrj-95748	334	21	2020	2020	NUM
esrj-95748	334	22	)	)	PUNCT
esrj-95748	334	23	.	.	PUNCT
esrj-95748	335	1	gully	gully	PROPN
esrj-95748	335	2	erosion	erosion	NOUN
esrj-95748	335	3	spatial	spatial	ADJ
esrj-95748	335	4	modelling	modelling	NOUN
esrj-95748	335	5	:	:	PUNCT
esrj-95748	335	6	role	role	NOUN
esrj-95748	335	7	of	of	ADP
esrj-95748	335	8	machine	machine	NOUN
esrj-95748	335	9	learning	learn	VERB
esrj-95748	335	10	algorithms	algorithm	NOUN
esrj-95748	335	11	in	in	ADP
esrj-95748	335	12	selection	selection	NOUN
esrj-95748	335	13	of	of	ADP
esrj-95748	335	14	the	the	DET
esrj-95748	335	15	best	good	ADJ
esrj-95748	335	16	controlling	control	VERB
esrj-95748	335	17	factors	factor	NOUN
esrj-95748	335	18	and	and	CCONJ
esrj-95748	335	19	modelling	modelling	NOUN
esrj-95748	335	20	process	process	NOUN
esrj-95748	335	21	.	.	PUNCT
esrj-95748	336	1	geoscience	geoscience	NOUN
esrj-95748	336	2	frontiers	frontier	NOUN
esrj-95748	336	3	,	,	PUNCT
esrj-95748	336	4	11	11	NUM
esrj-95748	336	5	,	,	PUNCT
esrj-95748	336	6	2207	2207	NUM
esrj-95748	336	7	-	-	SYM
esrj-95748	336	8	2219	2219	NUM
esrj-95748	336	9	.	.	PUNCT
esrj-95748	337	1	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
esrj-95748	337	2	.	.	PUNCT
esrj-95748	338	1	gsf.2020.03.005	gsf.2020.03.005	PROPN
esrj-95748	338	2	poesen	poesen	PROPN
esrj-95748	338	3	,	,	PUNCT
esrj-95748	338	4	j.	j.	PROPN
esrj-95748	338	5	,	,	PUNCT
esrj-95748	338	6	vandekerckhove	vandekerckhove	NOUN
esrj-95748	338	7	,	,	PUNCT
esrj-95748	338	8	l.	l.	PROPN
esrj-95748	338	9	,	,	PUNCT
esrj-95748	338	10	nachtergaele	nachtergaele	PROPN
esrj-95748	338	11	,	,	PUNCT
esrj-95748	338	12	j.	j.	PROPN
esrj-95748	338	13	,	,	PUNCT
esrj-95748	338	14	oostwoud	oostwoud	PROPN
esrj-95748	338	15	wijdenes	wijdene	NOUN
esrj-95748	338	16	,	,	PUNCT
esrj-95748	338	17	d.	d.	PROPN
esrj-95748	338	18	,	,	PUNCT
esrj-95748	338	19	verstraeten	verstraeten	VERB
esrj-95748	338	20	,	,	PUNCT
esrj-95748	338	21	g.	g.	PROPN
esrj-95748	338	22	&	&	CCONJ
esrj-95748	338	23	van	van	PROPN
esrj-95748	338	24	wesemael	wesemael	PROPN
esrj-95748	338	25	,	,	PUNCT
esrj-95748	338	26	b.	b.	PROPN
esrj-95748	338	27	(	(	PUNCT
esrj-95748	338	28	2002	2002	NUM
esrj-95748	338	29	)	)	PUNCT
esrj-95748	338	30	.	.	PUNCT
esrj-95748	339	1	gully	gully	PROPN
esrj-95748	339	2	erosion	erosion	NOUN
esrj-95748	339	3	in	in	ADP
esrj-95748	339	4	dryland	dryland	NOUN
esrj-95748	339	5	environments	environment	NOUN
esrj-95748	339	6	.	.	PUNCT
esrj-95748	340	1	in	in	ADP
esrj-95748	340	2	:	:	PUNCT
esrj-95748	340	3	bull	bull	NOUN
esrj-95748	340	4	,	,	PUNCT
esrj-95748	340	5	l.	l.	PROPN
esrj-95748	340	6	j.	j.	PROPN
esrj-95748	340	7	,	,	PUNCT
esrj-95748	340	8	kirkby	kirkby	NOUN
esrj-95748	340	9	,	,	PUNCT
esrj-95748	340	10	m.	m.	NOUN
esrj-95748	340	11	j.	j.	PROPN
esrj-95748	340	12	(	(	PUNCT
esrj-95748	340	13	eds	eds	PROPN
esrj-95748	340	14	.	.	PUNCT
esrj-95748	340	15	)	)	PUNCT
esrj-95748	340	16	.	.	PUNCT
esrj-95748	341	1	dryland	dryland	NOUN
esrj-95748	341	2	rivers	river	NOUN
esrj-95748	341	3	.	.	PUNCT
esrj-95748	342	1	hydrology	hydrology	NOUN
esrj-95748	342	2	and	and	CCONJ
esrj-95748	342	3	geomorphology	geomorphology	NOUN
esrj-95748	342	4	of	of	ADP
esrj-95748	342	5	semi	semi	ADJ
esrj-95748	342	6	-	-	ADJ
esrj-95748	342	7	arid	arid	ADJ
esrj-95748	342	8	channels	channel	NOUN
esrj-95748	342	9	.	.	PUNCT
esrj-95748	343	1	wiley	wiley	PROPN
esrj-95748	343	2	,	,	PUNCT
esrj-95748	343	3	chichester	chichester	PROPN
esrj-95748	343	4	,	,	PUNCT
esrj-95748	343	5	pp	pp	X
esrj-95748	343	6	,	,	PUNCT
esrj-95748	343	7	229–262	229–262	NUM
esrj-95748	343	8	.	.	PUNCT
esrj-95748	344	1	rahmati	rahmati	NOUN
esrj-95748	344	2	,	,	PUNCT
esrj-95748	344	3	o.	o.	PROPN
esrj-95748	344	4	,	,	PUNCT
esrj-95748	344	5	tahmasebipour	tahmasebipour	ADJ
esrj-95748	344	6	,	,	PUNCT
esrj-95748	344	7	n.	n.	ADJ
esrj-95748	344	8	,	,	PUNCT
esrj-95748	344	9	haghizadeh	haghizadeh	NOUN
esrj-95748	344	10	,	,	PUNCT
esrj-95748	344	11	a.	a.	NOUN
esrj-95748	344	12	,	,	PUNCT
esrj-95748	344	13	pourghasemi	pourghasemi	PROPN
esrj-95748	344	14	,	,	PUNCT
esrj-95748	344	15	h.	h.	PROPN
esrj-95748	344	16	r.	r.	PROPN
esrj-95748	344	17	&	&	CCONJ
esrj-95748	344	18	feizizadeh	feizizadeh	PROPN
esrj-95748	344	19	,	,	PUNCT
esrj-95748	344	20	b.	b.	PROPN
esrj-95748	344	21	(	(	PUNCT
esrj-95748	344	22	2017	2017	NUM
esrj-95748	344	23	)	)	PUNCT
esrj-95748	344	24	.	.	PUNCT
esrj-95748	345	1	evaluation	evaluation	NOUN
esrj-95748	345	2	of	of	ADP
esrj-95748	345	3	different	different	ADJ
esrj-95748	345	4	machine	machine	NOUN
esrj-95748	345	5	learning	learning	NOUN
esrj-95748	345	6	models	model	NOUN
esrj-95748	345	7	for	for	ADP
esrj-95748	345	8	predicting	predict	VERB
esrj-95748	345	9	and	and	CCONJ
esrj-95748	345	10	mapping	map	VERB
esrj-95748	345	11	the	the	DET
esrj-95748	345	12	susceptibility	susceptibility	NOUN
esrj-95748	345	13	of	of	ADP
esrj-95748	345	14	gully	gully	ADJ
esrj-95748	345	15	erosion	erosion	NOUN
esrj-95748	345	16	.	.	PUNCT
esrj-95748	346	1	geomorphology	geomorphology	NOUN
esrj-95748	346	2	,	,	PUNCT
esrj-95748	346	3	298	298	NUM
esrj-95748	346	4	,	,	PUNCT
esrj-95748	346	5	118–137	118–137	NUM
esrj-95748	346	6	.	.	PUNCT
esrj-95748	347	1	https://doi.org/10.1016/j.geomorph.2017.09.006	https://doi.org/10.1016/j.geomorph.2017.09.006	NOUN
esrj-95748	347	2	razavi	razavi	NOUN
esrj-95748	347	3	-	-	PUNCT
esrj-95748	347	4	termeh	termeh	NOUN
esrj-95748	347	5	,	,	PUNCT
esrj-95748	347	6	s.	s.	PROPN
esrj-95748	347	7	v.	v.	PROPN
esrj-95748	347	8	,	,	PUNCT
esrj-95748	347	9	sadeghi	sadeghi	PROPN
esrj-95748	347	10	-	-	PUNCT
esrj-95748	347	11	niaraki	niaraki	PROPN
esrj-95748	347	12	,	,	PUNCT
esrj-95748	347	13	a.	a.	NOUN
esrj-95748	347	14	&	&	CCONJ
esrj-95748	347	15	choi	choi	PROPN
esrj-95748	347	16	,	,	PUNCT
esrj-95748	347	17	s.	s.	PROPN
esrj-95748	347	18	m.	m.	PROPN
esrj-95748	347	19	(	(	PUNCT
esrj-95748	347	20	2020	2020	NUM
esrj-95748	347	21	)	)	PUNCT
esrj-95748	347	22	.	.	PUNCT
esrj-95748	348	1	gully	gully	NOUN
esrj-95748	348	2	erosion	erosion	NOUN
esrj-95748	348	3	susceptibility	susceptibility	NOUN
esrj-95748	348	4	mapping	mapping	NOUN
esrj-95748	348	5	using	use	VERB
esrj-95748	348	6	artificial	artificial	ADJ
esrj-95748	348	7	intelligence	intelligence	NOUN
esrj-95748	348	8	and	and	CCONJ
esrj-95748	348	9	statistical	statistical	ADJ
esrj-95748	348	10	models	model	NOUN
esrj-95748	348	11	.	.	PUNCT
esrj-95748	349	1	geomatics	geomatic	NOUN
esrj-95748	349	2	,	,	PUNCT
esrj-95748	349	3	natural	natural	ADJ
esrj-95748	349	4	hazards	hazard	NOUN
esrj-95748	349	5	and	and	CCONJ
esrj-95748	349	6	risk	risk	NOUN
esrj-95748	349	7	,	,	PUNCT
esrj-95748	349	8	11	11	NUM
esrj-95748	349	9	,	,	PUNCT
esrj-95748	349	10	821–845	821–845	NUM
esrj-95748	349	11	.	.	PUNCT
esrj-95748	350	1	https://doi.or	https://doi.or	PROPN
esrj-95748	350	2	g/10.1080/19475705.2020.1753824	g/10.1080/19475705.2020.1753824	PROPN
esrj-95748	350	3	raduła	raduła	PROPN
esrj-95748	350	4	,	,	PUNCT
esrj-95748	350	5	m.	m.	PROPN
esrj-95748	350	6	w.	w.	PROPN
esrj-95748	350	7	,	,	PUNCT
esrj-95748	350	8	szymura	szymura	PROPN
esrj-95748	350	9	,	,	PUNCT
esrj-95748	350	10	t.	t.	PROPN
esrj-95748	350	11	h.	h.	PROPN
esrj-95748	350	12	&	&	CCONJ
esrj-95748	350	13	szymura	szymura	PROPN
esrj-95748	350	14	,	,	PUNCT
esrj-95748	350	15	m.	m.	NOUN
esrj-95748	350	16	(	(	PUNCT
esrj-95748	350	17	2018	2018	NUM
esrj-95748	350	18	)	)	PUNCT
esrj-95748	350	19	.	.	PUNCT
esrj-95748	351	1	topographic	topographic	PROPN
esrj-95748	351	2	wetness	wetness	PROPN
esrj-95748	351	3	index	index	NOUN
esrj-95748	351	4	explains	explain	VERB
esrj-95748	351	5	soil	soil	NOUN
esrj-95748	351	6	moisture	moisture	NOUN
esrj-95748	351	7	better	well	ADV
esrj-95748	351	8	than	than	ADP
esrj-95748	351	9	bioindication	bioindication	NOUN
esrj-95748	351	10	with	with	ADP
esrj-95748	351	11	ellenberg	ellenberg	PROPN
esrj-95748	351	12	’s	’s	PART
esrj-95748	351	13	indicator	indicator	NOUN
esrj-95748	351	14	values	value	NOUN
esrj-95748	351	15	.	.	PUNCT
esrj-95748	352	1	ecological	ecological	ADJ
esrj-95748	352	2	indicators	indicator	NOUN
esrj-95748	352	3	,	,	PUNCT
esrj-95748	352	4	85	85	NUM
esrj-95748	352	5	,	,	PUNCT
esrj-95748	352	6	172	172	NUM
esrj-95748	352	7	-	-	SYM
esrj-95748	352	8	179	179	NUM
esrj-95748	352	9	.	.	PUNCT
esrj-95748	353	1	https://doi.org/10.1016/j.ecolind.2017.10.011	https://doi.org/10.1016/j.ecolind.2017.10.011	PROPN
esrj-95748	353	2	su	su	PROPN
esrj-95748	353	3	,	,	PUNCT
esrj-95748	353	4	z.	z.	PROPN
esrj-95748	353	5	a.	a.	PROPN
esrj-95748	353	6	,	,	PUNCT
esrj-95748	353	7	zhang	zhang	PROPN
esrj-95748	353	8	,	,	PUNCT
esrj-95748	353	9	j.	j.	PROPN
esrj-95748	353	10	h.	h.	PROPN
esrj-95748	353	11	&	&	CCONJ
esrj-95748	353	12	nie	nie	PROPN
esrj-95748	353	13	,	,	PUNCT
esrj-95748	353	14	x.	x.	PROPN
esrj-95748	353	15	j.	j.	PROPN
esrj-95748	353	16	(	(	PUNCT
esrj-95748	353	17	2010	2010	NUM
esrj-95748	353	18	)	)	PUNCT
esrj-95748	353	19	.	.	PUNCT
esrj-95748	354	1	effect	effect	NOUN
esrj-95748	354	2	of	of	ADP
esrj-95748	354	3	soil	soil	NOUN
esrj-95748	354	4	erosion	erosion	NOUN
esrj-95748	354	5	on	on	ADP
esrj-95748	354	6	soil	soil	NOUN
esrj-95748	354	7	properties	property	NOUN
esrj-95748	354	8	and	and	CCONJ
esrj-95748	354	9	crop	crop	NOUN
esrj-95748	354	10	yields	yield	NOUN
esrj-95748	354	11	on	on	ADP
esrj-95748	354	12	slopes	slope	NOUN
esrj-95748	354	13	in	in	ADP
esrj-95748	354	14	the	the	DET
esrj-95748	354	15	sichuan	sichuan	PROPN
esrj-95748	354	16	basin	basin	PROPN
esrj-95748	354	17	,	,	PUNCT
esrj-95748	354	18	china	china	PROPN
esrj-95748	354	19	.	.	PUNCT
esrj-95748	354	20	pedosphere	pedosphere	PROPN
esrj-95748	354	21	,	,	PUNCT
esrj-95748	354	22	20	20	NUM
esrj-95748	354	23	(	(	PUNCT
esrj-95748	354	24	6	6	NUM
esrj-95748	354	25	)	)	PUNCT
esrj-95748	354	26	,	,	PUNCT
esrj-95748	354	27	736–746	736–746	NUM
esrj-95748	354	28	.	.	PUNCT
esrj-95748	355	1	https://doi.org/10.1016/s1002-0160(10)60064-1	https://doi.org/10.1016/s1002-0160(10)60064-1	NOUN
esrj-95748	355	2	shafer	shafer	PROPN
esrj-95748	355	3	,	,	PUNCT
esrj-95748	355	4	g.	g.	PROPN
esrj-95748	355	5	(	(	PUNCT
esrj-95748	355	6	1976	1976	NUM
esrj-95748	355	7	)	)	PUNCT
esrj-95748	355	8	.	.	PUNCT
esrj-95748	356	1	a	a	DET
esrj-95748	356	2	mathematical	mathematical	ADJ
esrj-95748	356	3	theory	theory	NOUN
esrj-95748	356	4	of	of	ADP
esrj-95748	356	5	evidence	evidence	NOUN
esrj-95748	356	6	.	.	PUNCT
esrj-95748	357	1	princeton	princeton	PROPN
esrj-95748	357	2	university	university	PROPN
esrj-95748	357	3	press	press	PROPN
esrj-95748	357	4	,	,	PUNCT
esrj-95748	357	5	princeton	princeton	PROPN
esrj-95748	357	6	.	.	PUNCT
esrj-95748	358	1	saha	saha	PROPN
esrj-95748	358	2	,	,	PUNCT
esrj-95748	358	3	s.	s.	PROPN
esrj-95748	358	4	,	,	PUNCT
esrj-95748	358	5	roy	roy	PROPN
esrj-95748	358	6	,	,	PUNCT
esrj-95748	358	7	j.	j.	PROPN
esrj-95748	358	8	,	,	PUNCT
esrj-95748	358	9	arabameri	arabameri	PROPN
esrj-95748	358	10	,	,	PUNCT
esrj-95748	358	11	a.	a.	NOUN
esrj-95748	358	12	,	,	PUNCT
esrj-95748	358	13	blaschke	blaschke	PROPN
esrj-95748	358	14	,	,	PUNCT
esrj-95748	358	15	t.	t.	PROPN
esrj-95748	358	16	,	,	PUNCT
esrj-95748	358	17	&	&	CCONJ
esrj-95748	358	18	tien	tien	PROPN
esrj-95748	358	19	bui	bui	PROPN
esrj-95748	358	20	,	,	PUNCT
esrj-95748	358	21	d.	d.	PROPN
esrj-95748	358	22	(	(	PUNCT
esrj-95748	358	23	2020	2020	NUM
esrj-95748	358	24	)	)	PUNCT
esrj-95748	358	25	.	.	PUNCT
esrj-95748	359	1	machine	machine	NOUN
esrj-95748	359	2	learning	learning	NOUN
esrj-95748	359	3	-	-	PUNCT
esrj-95748	359	4	based	base	VERB
esrj-95748	359	5	gully	gully	NOUN
esrj-95748	359	6	erosion	erosion	NOUN
esrj-95748	359	7	susceptibility	susceptibility	NOUN
esrj-95748	359	8	mapping	mapping	NOUN
esrj-95748	359	9	:	:	PUNCT
esrj-95748	359	10	a	a	DET
esrj-95748	359	11	case	case	NOUN
esrj-95748	359	12	study	study	NOUN
esrj-95748	359	13	of	of	ADP
esrj-95748	359	14	eastern	eastern	PROPN
esrj-95748	359	15	india	india	PROPN
esrj-95748	359	16	.	.	PUNCT
esrj-95748	360	1	sensors	sensor	NOUN
esrj-95748	360	2	,	,	PUNCT
esrj-95748	360	3	20(5	20(5	NUM
esrj-95748	360	4	)	)	PUNCT
esrj-95748	360	5	,	,	PUNCT
esrj-95748	360	6	1	1	NUM
esrj-95748	360	7	-	-	SYM
esrj-95748	360	8	25	25	NUM
esrj-95748	360	9	.	.	PUNCT
esrj-95748	361	1	https://doi.org/10.3390/s20051313	https://doi.org/10.3390/s20051313	PROPN
esrj-95748	361	2	xiao	xiao	PROPN
esrj-95748	361	3	,	,	PUNCT
esrj-95748	361	4	h.	h.	PROPN
esrj-95748	361	5	,	,	PUNCT
esrj-95748	361	6	li	li	PROPN
esrj-95748	361	7	,	,	PUNCT
esrj-95748	361	8	z.	z.	PROPN
esrj-95748	361	9	,	,	PUNCT
esrj-95748	361	10	dong	dong	PROPN
esrj-95748	361	11	,	,	PUNCT
esrj-95748	361	12	y.	y.	PROPN
esrj-95748	361	13	,	,	PUNCT
esrj-95748	361	14	chang	chang	PROPN
esrj-95748	361	15	,	,	PUNCT
esrj-95748	361	16	x.	x.	PROPN
esrj-95748	361	17	,	,	PUNCT
esrj-95748	361	18	deng	deng	PROPN
esrj-95748	361	19	,	,	PUNCT
esrj-95748	361	20	l.	l.	PROPN
esrj-95748	361	21	,	,	PUNCT
esrj-95748	361	22	huang	huang	PROPN
esrj-95748	361	23	,	,	PUNCT
esrj-95748	361	24	j.	j.	PROPN
esrj-95748	361	25	,	,	PUNCT
esrj-95748	361	26	&	&	CCONJ
esrj-95748	361	27	liu	liu	PROPN
esrj-95748	361	28	,	,	PUNCT
esrj-95748	361	29	q.	q.	PROPN
esrj-95748	361	30	(	(	PUNCT
esrj-95748	361	31	2017	2017	NUM
esrj-95748	361	32	)	)	PUNCT
esrj-95748	361	33	.	.	PUNCT
esrj-95748	362	1	changes	change	NOUN
esrj-95748	362	2	in	in	ADP
esrj-95748	362	3	microbial	microbial	ADJ
esrj-95748	362	4	communities	community	NOUN
esrj-95748	362	5	and	and	CCONJ
esrj-95748	362	6	respiration	respiration	NOUN
esrj-95748	362	7	following	follow	VERB
esrj-95748	362	8	the	the	DET
esrj-95748	362	9	revegetation	revegetation	NOUN
esrj-95748	362	10	of	of	ADP
esrj-95748	362	11	eroded	eroded	ADJ
esrj-95748	362	12	soil	soil	NOUN
esrj-95748	362	13	.	.	PUNCT
esrj-95748	363	1	agriculture	agriculture	NOUN
esrj-95748	363	2	,	,	PUNCT
esrj-95748	363	3	ecosystems	ecosystem	NOUN
esrj-95748	363	4	&	&	CCONJ
esrj-95748	363	5	environment	environment	PROPN
esrj-95748	363	6	,	,	PUNCT
esrj-95748	363	7	246	246	NUM
esrj-95748	363	8	,	,	PUNCT
esrj-95748	363	9	30–37	30–37	NUM
esrj-95748	363	10	.	.	PUNCT
esrj-95748	364	1	https://doi.org/10.1016/j.agee.2017.05.026	https://doi.org/10.1016/j.agee.2017.05.026	PROPN
esrj-95748	364	2	yesilnacar	yesilnacar	NOUN
esrj-95748	364	3	,	,	PUNCT
esrj-95748	364	4	e.	e.	PROPN
esrj-95748	364	5	k.	k.	PROPN
esrj-95748	364	6	(	(	PUNCT
esrj-95748	364	7	2005	2005	NUM
esrj-95748	364	8	)	)	PUNCT
esrj-95748	364	9	.	.	PUNCT
esrj-95748	365	1	the	the	DET
esrj-95748	365	2	application	application	NOUN
esrj-95748	365	3	of	of	ADP
esrj-95748	365	4	computational	computational	ADJ
esrj-95748	365	5	intelligence	intelligence	NOUN
esrj-95748	365	6	to	to	PART
esrj-95748	365	7	landslide	landslide	VERB
esrj-95748	365	8	susceptibility	susceptibility	NOUN
esrj-95748	365	9	mapping	mapping	NOUN
esrj-95748	365	10	in	in	ADP
esrj-95748	365	11	turkey	turkey	PROPN
esrj-95748	365	12	(	(	PUNCT
esrj-95748	365	13	ph.d	ph.d	PROPN
esrj-95748	365	14	thesis	thesis	NOUN
esrj-95748	365	15	)	)	PUNCT
esrj-95748	365	16	.	.	PUNCT
esrj-95748	366	1	department	department	PROPN
esrj-95748	366	2	of	of	ADP
esrj-95748	366	3	geomatics	geomatics	PROPN
esrj-95748	366	4	,	,	PUNCT
esrj-95748	366	5	university	university	PROPN
esrj-95748	366	6	of	of	ADP
esrj-95748	366	7	melbourne	melbourne	PROPN
esrj-95748	366	8	,	,	PUNCT
esrj-95748	366	9	pp	pp	ADJ
esrj-95748	366	10	.	.	PUNCT
esrj-95748	367	1	423	423	NUM
esrj-95748	367	2	.	.	PUNCT
esrj-95748	367	3	yigini	yigini	PROPN
esrj-95748	367	4	,	,	PUNCT
esrj-95748	367	5	y.	y.	PROPN
esrj-95748	367	6	,	,	PUNCT
esrj-95748	367	7	&	&	CCONJ
esrj-95748	367	8	panagos	panagos	PROPN
esrj-95748	367	9	,	,	PUNCT
esrj-95748	367	10	p.	p.	NOUN
esrj-95748	367	11	(	(	PUNCT
esrj-95748	367	12	2016	2016	NUM
esrj-95748	367	13	)	)	PUNCT
esrj-95748	367	14	.	.	PUNCT
esrj-95748	368	1	assessment	assessment	NOUN
esrj-95748	368	2	of	of	ADP
esrj-95748	368	3	soil	soil	NOUN
esrj-95748	368	4	organic	organic	ADJ
esrj-95748	368	5	carbon	carbon	NOUN
esrj-95748	368	6	stocks	stock	NOUN
esrj-95748	368	7	under	under	ADP
esrj-95748	368	8	future	future	ADJ
esrj-95748	368	9	climate	climate	NOUN
esrj-95748	368	10	and	and	CCONJ
esrj-95748	368	11	land	land	NOUN
esrj-95748	368	12	cover	cover	NOUN
esrj-95748	368	13	changes	change	NOUN
esrj-95748	368	14	in	in	ADP
esrj-95748	368	15	europe	europe	PROPN
esrj-95748	368	16	.	.	PUNCT
esrj-95748	369	1	science	science	NOUN
esrj-95748	369	2	of	of	ADP
esrj-95748	369	3	the	the	DET
esrj-95748	369	4	total	total	ADJ
esrj-95748	369	5	environment	environment	NOUN
esrj-95748	369	6	,	,	PUNCT
esrj-95748	369	7	557	557	NUM
esrj-95748	369	8	,	,	PUNCT
esrj-95748	369	9	838–850	838–850	NUM
esrj-95748	369	10	.	.	PUNCT
esrj-95748	370	1	https://doi.org/10.1016/j.scitotenv	https://doi.org/10.1016/j.scitotenv	NOUN
esrj-95748	370	2	zabihi	zabihi	PROPN
esrj-95748	370	3	,	,	PUNCT
esrj-95748	370	4	m.	m.	NOUN
esrj-95748	370	5	,	,	PUNCT
esrj-95748	370	6	mirchooli	mirchooli	PROPN
esrj-95748	370	7	,	,	PUNCT
esrj-95748	370	8	f.	f.	PROPN
esrj-95748	370	9	,	,	PUNCT
esrj-95748	370	10	motevalli	motevalli	PROPN
esrj-95748	370	11	,	,	PUNCT
esrj-95748	370	12	a.	a.	PROPN
esrj-95748	370	13	,	,	PUNCT
esrj-95748	370	14	darvishan	darvishan	PROPN
esrj-95748	370	15	,	,	PUNCT
esrj-95748	370	16	a.	a.	PROPN
esrj-95748	370	17	k.	k.	PROPN
esrj-95748	370	18	,	,	PUNCT
esrj-95748	370	19	pourghasemi	pourghasemi	PROPN
esrj-95748	370	20	,	,	PUNCT
esrj-95748	370	21	h.	h.	PROPN
esrj-95748	370	22	r.	r.	PROPN
esrj-95748	370	23	,	,	PUNCT
esrj-95748	370	24	zakeri	zakeri	PROPN
esrj-95748	370	25	,	,	PUNCT
esrj-95748	370	26	m.	m.	NOUN
esrj-95748	370	27	a.	a.	PROPN
esrj-95748	370	28	&	&	CCONJ
esrj-95748	370	29	sadighi	sadighi	PROPN
esrj-95748	370	30	,	,	PUNCT
esrj-95748	370	31	f.	f.	PROPN
esrj-95748	370	32	(	(	PUNCT
esrj-95748	370	33	2018	2018	NUM
esrj-95748	370	34	)	)	PUNCT
esrj-95748	370	35	.	.	PUNCT
esrj-95748	371	1	spatial	spatial	ADJ
esrj-95748	371	2	modelling	modelling	NOUN
esrj-95748	371	3	of	of	ADP
esrj-95748	371	4	gully	gully	ADJ
esrj-95748	371	5	erosion	erosion	NOUN
esrj-95748	371	6	in	in	ADP
esrj-95748	371	7	mazandaran	mazandaran	PROPN
esrj-95748	371	8	province	province	PROPN
esrj-95748	371	9	,	,	PUNCT
esrj-95748	371	10	northern	northern	ADJ
esrj-95748	371	11	iran	iran	PROPN
esrj-95748	371	12	.	.	PUNCT
esrj-95748	372	1	catena	catena	PROPN
esrj-95748	372	2	,	,	PUNCT
esrj-95748	372	3	161	161	NUM
esrj-95748	372	4	,	,	PUNCT
esrj-95748	372	5	1–13	1–13	NOUN
esrj-95748	372	6	.	.	PUNCT
esrj-95748	373	1	https://doi	https://doi	PROPN
esrj-95748	373	2	.	.	PUNCT
esrj-95748	373	3	org/10.1016	org/10.1016	PROPN
esrj-95748	373	4	/	/	SYM
esrj-95748	373	5	j.catena.2017.10.010	j.catena.2017.10.010	NOUN
esrj-95748	373	6	https://doi.org/10.3233/fi-2010-288	https://doi.org/10.3233/fi-2010-288	NUM
esrj-95748	373	7	https://doi.org/10.3233/fi-2010-288	https://doi.org/10.3233/fi-2010-288	NOUN
esrj-95748	373	8	https://doi.org/10.3390/rs12152478	https://doi.org/10.3390/rs12152478	INTJ
esrj-95748	373	9	https://doi.org/10.1007/s12665-011-1477-y	https://doi.org/10.1007/s12665-011-1477-y	PROPN
esrj-95748	373	10	http://dx.doi.org/10.1007/s11004-013-9511-0	http://dx.doi.org/10.1007/s11004-013-9511-0	NOUN
esrj-95748	374	1	https://doi.org/10.2136/sssaj1993.03615995005700020026x	https://doi.org/10.2136/sssaj1993.03615995005700020026x	PROPN
esrj-95748	374	2	https://doi.org/10.2136/sssaj1993.03615995005700020026x	https://doi.org/10.2136/sssaj1993.03615995005700020026x	NOUN
esrj-95748	374	3	https://doi.org/10.1016/j.enggeo.2011.09.006	https://doi.org/10.1016/j.enggeo.2011.09.006	NUM
esrj-95748	374	4	https://doi.org/10.1016/j.enggeo.2011.09.006	https://doi.org/10.1016/j.enggeo.2011.09.006	NUM
esrj-95748	374	5	https://dx.doi.org/10.1007/s10661-015-5049-6	https://dx.doi.org/10.1007/s10661-015-5049-6	NOUN
esrj-95748	374	6	https://dx.doi.org/10.1007/s10661-015-5049-6	https://dx.doi.org/10.1007/s10661-015-5049-6	NOUN
esrj-95748	374	7	https://www.researchgate.net/deref/http%3a%2f%2fdx.doi.org%2f10.1016%2fj.catena.2016.06.031?_sg%5b0%5d=voa2cpmhpt__l9bhgvockjflz7w_b28vu_iiotbnebuxubaxfralktwrafjbsmuucp7a-iw283tvzsbguykq3vrama.pk5axbisi1ybxpxj4rlwitui8d6pmxq6iadbbedhexxe_sx1vsdwvikyyra24d3zakvrbbu4vbjsfwuehpbmiw	https://www.researchgate.net/deref/http%3a%2f%2fdx.doi.org%2f10.1016%2fj.catena.2016.06.031?_sg%5b0%5d=voa2cpmhpt__l9bhgvockjflz7w_b28vu_iiotbnebuxubaxfralktwrafjbsmuucp7a-iw283tvzsbguykq3vrama.pk5axbisi1ybxpxj4rlwitui8d6pmxq6iadbbedhexxe_sx1vsdwvikyyra24d3zakvrbbu4vbjsfwuehpbmiw	NOUN
esrj-95748	374	8	https://www.researchgate.net/deref/http%3a%2f%2fdx.doi.org%2f10.1016%2fj.catena.2016.06.031?_sg%5b0%5d=voa2cpmhpt__l9bhgvockjflz7w_b28vu_iiotbnebuxubaxfralktwrafjbsmuucp7a-iw283tvzsbguykq3vrama.pk5axbisi1ybxpxj4rlwitui8d6pmxq6iadbbedhexxe_sx1vsdwvikyyra24d3zakvrbbu4vbjsfwuehpbmiw	https://www.researchgate.net/deref/http%3a%2f%2fdx.doi.org%2f10.1016%2fj.catena.2016.06.031?_sg%5b0%5d=voa2cpmhpt__l9bhgvockjflz7w_b28vu_iiotbnebuxubaxfralktwrafjbsmuucp7a-iw283tvzsbguykq3vrama.pk5axbisi1ybxpxj4rlwitui8d6pmxq6iadbbedhexxe_sx1vsdwvikyyra24d3zakvrbbu4vbjsfwuehpbmiw	NOUN
esrj-95748	374	9	https://doi.org/10.1007/s12665-010-0531-5	https://doi.org/10.1007/s12665-010-0531-5	NOUN
esrj-95748	374	10	http://dx.doi.org/10.1016/j.cageo.2012.08.023	http://dx.doi.org/10.1016/j.cageo.2012.08.023	PROPN
esrj-95748	374	11	https://doi.org/10.1016/j	https://doi.org/10.1016/j	NOUN
esrj-95748	374	12	.	.	PUNCT
esrj-95748	375	1	scitotenv.2017.07.198	scitotenv.2017.07.198	ADJ
esrj-95748	375	2	https://doi.org/10.1016/j.gsf.2020.03.005	https://doi.org/10.1016/j.gsf.2020.03.005	NOUN
esrj-95748	375	3	https://doi.org/10.1016/j.gsf.2020.03.005	https://doi.org/10.1016/j.gsf.2020.03.005	VERB
esrj-95748	375	4	https://doi.org/10.1016/j.geomorph.2017.09.006	https://doi.org/10.1016/j.geomorph.2017.09.006	NOUN
esrj-95748	375	5	https://doi.org/10.1080/19475705.2020.1753824	https://doi.org/10.1080/19475705.2020.1753824	PUNCT
esrj-95748	375	6	https://doi.org/10.1080/19475705.2020.1753824	https://doi.org/10.1080/19475705.2020.1753824	PROPN
esrj-95748	375	7	https://doi.org/10.1016/j.ecolind.2017.10.011	https://doi.org/10.1016/j.ecolind.2017.10.011	PROPN
esrj-95748	375	8	https://doi.org/10.1016/j.ecolind.2017.10.011	https://doi.org/10.1016/j.ecolind.2017.10.011	PROPN
esrj-95748	375	9	https://doi.org/10.1016/s1002-0160(10)60064-1	https://doi.org/10.1016/s1002-0160(10)60064-1	NOUN
esrj-95748	375	10	https://doi.org/10.3390/s20051313	https://doi.org/10.3390/s20051313	PROPN
esrj-95748	375	11	https://doi.org/10.1016/j.agee.2017.05.026	https://doi.org/10.1016/j.agee.2017.05.026	PROPN
esrj-95748	375	12	https://doi.org/10.1016/j.scitotenv	https://doi.org/10.1016/j.scitotenv	NOUN
esrj-95748	375	13	https://doi.org/10.1016/j.catena.2017.10.010	https://doi.org/10.1016/j.catena.2017.10.010	NOUN
esrj-95748	375	14	https://doi.org/10.1016/j.catena.2017.10.010	https://doi.org/10.1016/j.catena.2017.10.010	PROPN