id	sid	tid	token	lemma	pos
ajst-20195	1	1	academic	academic	ADJ
ajst-20195	1	2	journal	journal	NOUN
ajst-20195	1	3	of	of	ADP
ajst-20195	1	4	science	science	NOUN
ajst-20195	1	5	and	and	CCONJ
ajst-20195	1	6	technology	technology	NOUN
ajst-20195	1	7	issn	issn	NOUN
ajst-20195	1	8	:	:	PUNCT
ajst-20195	1	9	2771	2771	NUM
ajst-20195	1	10	-	-	SYM
ajst-20195	1	11	3032	3032	NUM
ajst-20195	1	12	|	|	NOUN
ajst-20195	1	13	vol	vol	NOUN
ajst-20195	1	14	.	.	PROPN
ajst-20195	2	1	10	10	NUM
ajst-20195	2	2	,	,	PUNCT
ajst-20195	2	3	no	no	INTJ
ajst-20195	2	4	.	.	NOUN
ajst-20195	2	5	2	2	NUM
ajst-20195	2	6	,	,	PUNCT
ajst-20195	2	7	2024	2024	NUM
ajst-20195	2	8	100	100	NUM
ajst-20195	2	9	quantitative	quantitative	ADJ
ajst-20195	2	10	inversion	inversion	NOUN
ajst-20195	2	11	of	of	ADP
ajst-20195	2	12	soil	soil	NOUN
ajst-20195	2	13	salinity	salinity	NOUN
ajst-20195	2	14	in	in	ADP
ajst-20195	2	15	different	different	ADJ
ajst-20195	2	16	seasons	season	NOUN
ajst-20195	2	17	in	in	ADP
ajst-20195	2	18	huinong	huinong	PROPN
ajst-20195	2	19	district	district	NOUN
ajst-20195	2	20	,	,	PUNCT
ajst-20195	2	21	ningxia	ningxia	PROPN
ajst-20195	2	22	based	base	VERB
ajst-20195	2	23	on	on	ADP
ajst-20195	2	24	sentinel‐	sentinel‐	NUM
ajst-20195	2	25	2	2	NUM
ajst-20195	2	26	satellite	satellite	NOUN
ajst-20195	2	27	tuo	tuo	PROPN
ajst-20195	2	28	wang	wang	PROPN
ajst-20195	2	29	,	,	PUNCT
ajst-20195	2	30	xiaojing	xiaojing	PROPN
ajst-20195	2	31	shen	shen	PROPN
ajst-20195	2	32	*	*	PROPN
ajst-20195	2	33	,	,	PUNCT
ajst-20195	2	34	wenjie	wenjie	PROPN
ajst-20195	2	35	luan	luan	PROPN
ajst-20195	2	36	school	school	PROPN
ajst-20195	2	37	of	of	ADP
ajst-20195	2	38	civil	civil	ADJ
ajst-20195	2	39	and	and	CCONJ
ajst-20195	2	40	water	water	NOUN
ajst-20195	2	41	resources	resource	NOUN
ajst-20195	2	42	engineering	engineering	PROPN
ajst-20195	2	43	,	,	PUNCT
ajst-20195	2	44	ningxia	ningxia	PROPN
ajst-20195	2	45	university	university	PROPN
ajst-20195	2	46	,	,	PUNCT
ajst-20195	2	47	yinchuan	yinchuan	PROPN
ajst-20195	2	48	750021	750021	NUM
ajst-20195	2	49	,	,	PUNCT
ajst-20195	2	50	ningxia	ningxia	PROPN
ajst-20195	2	51	,	,	PUNCT
ajst-20195	2	52	china	china	PROPN
ajst-20195	2	53	*	*	PUNCT
ajst-20195	2	54	corresponding	correspond	VERB
ajst-20195	2	55	author	author	NOUN
ajst-20195	2	56	abstract	abstract	NOUN
ajst-20195	2	57	:	:	PUNCT
ajst-20195	2	58	salinisation	salinisation	NOUN
ajst-20195	2	59	of	of	ADP
ajst-20195	2	60	agricultural	agricultural	ADJ
ajst-20195	2	61	soils	soil	NOUN
ajst-20195	2	62	poses	pose	VERB
ajst-20195	2	63	an	an	DET
ajst-20195	2	64	important	important	ADJ
ajst-20195	2	65	constraint	constraint	NOUN
ajst-20195	2	66	to	to	ADP
ajst-20195	2	67	sustainable	sustainable	ADJ
ajst-20195	2	68	agricultural	agricultural	ADJ
ajst-20195	2	69	development	development	NOUN
ajst-20195	2	70	,	,	PUNCT
ajst-20195	2	71	especially	especially	ADV
ajst-20195	2	72	in	in	ADP
ajst-20195	2	73	the	the	DET
ajst-20195	2	74	huinong	huinong	NOUN
ajst-20195	2	75	region	region	NOUN
ajst-20195	2	76	of	of	ADP
ajst-20195	2	77	ningxia	ningxia	PROPN
ajst-20195	2	78	,	,	PUNCT
ajst-20195	2	79	northwestern	northwestern	ADJ
ajst-20195	2	80	china	china	PROPN
ajst-20195	2	81	,	,	PUNCT
ajst-20195	2	82	where	where	SCONJ
ajst-20195	2	83	salinised	salinise	VERB
ajst-20195	2	84	soils	soil	NOUN
ajst-20195	2	85	are	be	AUX
ajst-20195	2	86	widely	widely	ADV
ajst-20195	2	87	distributed	distribute	VERB
ajst-20195	2	88	.	.	PUNCT
ajst-20195	3	1	however	however	ADV
ajst-20195	3	2	,	,	PUNCT
ajst-20195	3	3	due	due	ADP
ajst-20195	3	4	to	to	ADP
ajst-20195	3	5	the	the	DET
ajst-20195	3	6	limitations	limitation	NOUN
ajst-20195	3	7	of	of	ADP
ajst-20195	3	8	monitoring	monitor	VERB
ajst-20195	3	9	technology	technology	NOUN
ajst-20195	3	10	,	,	PUNCT
ajst-20195	3	11	the	the	DET
ajst-20195	3	12	detailed	detailed	ADJ
ajst-20195	3	13	situation	situation	NOUN
ajst-20195	3	14	of	of	ADP
ajst-20195	3	15	soil	soil	NOUN
ajst-20195	3	16	salinisation	salinisation	NOUN
ajst-20195	3	17	in	in	ADP
ajst-20195	3	18	this	this	DET
ajst-20195	3	19	region	region	NOUN
ajst-20195	3	20	is	be	AUX
ajst-20195	3	21	not	not	PART
ajst-20195	3	22	known	know	VERB
ajst-20195	3	23	.	.	PUNCT
ajst-20195	4	1	currently	currently	ADV
ajst-20195	4	2	,	,	PUNCT
ajst-20195	4	3	the	the	DET
ajst-20195	4	4	multispectral	multispectral	ADJ
ajst-20195	4	5	instrument	instrument	NOUN
ajst-20195	4	6	(	(	PUNCT
ajst-20195	4	7	msi	msi	PROPN
ajst-20195	4	8	)	)	PUNCT
ajst-20195	4	9	on	on	ADP
ajst-20195	4	10	board	board	NOUN
ajst-20195	4	11	the	the	DET
ajst-20195	4	12	sentinel-2	sentinel-2	ADJ
ajst-20195	4	13	satellite	satellite	NOUN
ajst-20195	4	14	provides	provide	VERB
ajst-20195	4	15	a	a	DET
ajst-20195	4	16	good	good	ADJ
ajst-20195	4	17	opportunity	opportunity	NOUN
ajst-20195	4	18	for	for	ADP
ajst-20195	4	19	monitoring	monitor	VERB
ajst-20195	4	20	soil	soil	NOUN
ajst-20195	4	21	salinity	salinity	NOUN
ajst-20195	4	22	dynamics	dynamic	NOUN
ajst-20195	4	23	.	.	PUNCT
ajst-20195	5	1	therefore	therefore	ADV
ajst-20195	5	2	,	,	PUNCT
ajst-20195	5	3	in	in	ADP
ajst-20195	5	4	this	this	DET
ajst-20195	5	5	study	study	NOUN
ajst-20195	5	6	,	,	PUNCT
ajst-20195	5	7	the	the	DET
ajst-20195	5	8	feasibility	feasibility	NOUN
ajst-20195	5	9	of	of	ADP
ajst-20195	5	10	using	use	VERB
ajst-20195	5	11	the	the	DET
ajst-20195	5	12	multispectral	multispectral	ADJ
ajst-20195	5	13	instrument	instrument	NOUN
ajst-20195	5	14	(	(	PUNCT
ajst-20195	5	15	msi	msi	PROPN
ajst-20195	5	16	)	)	PUNCT
ajst-20195	5	17	on	on	ADP
ajst-20195	5	18	board	board	NOUN
ajst-20195	5	19	the	the	DET
ajst-20195	5	20	sentinel-2	sentinel-2	ADJ
ajst-20195	5	21	satellite	satellite	NOUN
ajst-20195	5	22	,	,	PUNCT
ajst-20195	5	23	combined	combine	VERB
ajst-20195	5	24	with	with	ADP
ajst-20195	5	25	a	a	DET
ajst-20195	5	26	machine	machine	NOUN
ajst-20195	5	27	learning	learn	VERB
ajst-20195	5	28	model	model	NOUN
ajst-20195	5	29	,	,	PUNCT
ajst-20195	5	30	to	to	PART
ajst-20195	5	31	accurately	accurately	ADV
ajst-20195	5	32	monitor	monitor	VERB
ajst-20195	5	33	the	the	DET
ajst-20195	5	34	soil	soil	NOUN
ajst-20195	5	35	salinity	salinity	NOUN
ajst-20195	5	36	content	content	NOUN
ajst-20195	5	37	during	during	ADP
ajst-20195	5	38	the	the	DET
ajst-20195	5	39	spring	spring	NOUN
ajst-20195	5	40	and	and	CCONJ
ajst-20195	5	41	summer	summer	NOUN
ajst-20195	5	42	seasons	season	NOUN
ajst-20195	5	43	was	be	AUX
ajst-20195	5	44	explored	explore	VERB
ajst-20195	5	45	.	.	PUNCT
ajst-20195	6	1	and	and	CCONJ
ajst-20195	6	2	three	three	NUM
ajst-20195	6	3	additional	additional	ADJ
ajst-20195	6	4	red	red	ADJ
ajst-20195	6	5	-	-	PUNCT
ajst-20195	6	6	edge	edge	NOUN
ajst-20195	6	7	bands	band	NOUN
ajst-20195	6	8	(	(	PUNCT
ajst-20195	6	9	b5	b5	PROPN
ajst-20195	6	10	-	-	PUNCT
ajst-20195	6	11	b7	b7	PROPN
ajst-20195	6	12	)	)	PUNCT
ajst-20195	6	13	were	be	AUX
ajst-20195	6	14	used	use	VERB
ajst-20195	6	15	instead	instead	ADV
ajst-20195	6	16	of	of	ADP
ajst-20195	6	17	the	the	DET
ajst-20195	6	18	traditional	traditional	ADJ
ajst-20195	6	19	red	red	ADJ
ajst-20195	6	20	band	band	NOUN
ajst-20195	6	21	(	(	PUNCT
ajst-20195	6	22	b4	b4	NOUN
ajst-20195	6	23	)	)	PUNCT
ajst-20195	6	24	to	to	PART
ajst-20195	6	25	generate	generate	VERB
ajst-20195	6	26	potential	potential	ADJ
ajst-20195	6	27	soil	soil	NOUN
ajst-20195	6	28	salinity	salinity	NOUN
ajst-20195	6	29	indices	index	NOUN
ajst-20195	6	30	.	.	PUNCT
ajst-20195	7	1	a	a	DET
ajst-20195	7	2	screening	screening	NOUN
ajst-20195	7	3	method	method	NOUN
ajst-20195	7	4	based	base	VERB
ajst-20195	7	5	on	on	ADP
ajst-20195	7	6	the	the	DET
ajst-20195	7	7	pls	pls	ADJ
ajst-20195	7	8	-	-	PUNCT
ajst-20195	7	9	vip	vip	NOUN
ajst-20195	7	10	criterion	criterion	NOUN
ajst-20195	7	11	was	be	AUX
ajst-20195	7	12	used	use	VERB
ajst-20195	7	13	to	to	PART
ajst-20195	7	14	screen	screen	VERB
ajst-20195	7	15	the	the	DET
ajst-20195	7	16	spectral	spectral	ADJ
ajst-20195	7	17	covariates	covariate	NOUN
ajst-20195	7	18	,	,	PUNCT
ajst-20195	7	19	and	and	CCONJ
ajst-20195	7	20	three	three	NUM
ajst-20195	7	21	machine	machine	NOUN
ajst-20195	7	22	learning	learning	NOUN
ajst-20195	7	23	methods	method	NOUN
ajst-20195	7	24	,	,	PUNCT
ajst-20195	7	25	namely	namely	ADV
ajst-20195	7	26	,	,	PUNCT
ajst-20195	7	27	random	random	ADJ
ajst-20195	7	28	forest	forest	NOUN
ajst-20195	7	29	(	(	PUNCT
ajst-20195	7	30	rf	rf	NOUN
ajst-20195	7	31	)	)	PUNCT
ajst-20195	7	32	,	,	PUNCT
ajst-20195	7	33	support	support	NOUN
ajst-20195	7	34	vector	vector	NOUN
ajst-20195	7	35	machine	machine	NOUN
ajst-20195	7	36	(	(	PUNCT
ajst-20195	7	37	svm	svm	PROPN
ajst-20195	7	38	)	)	PUNCT
ajst-20195	7	39	and	and	CCONJ
ajst-20195	7	40	extreme	extreme	ADJ
ajst-20195	7	41	learning	learning	NOUN
ajst-20195	7	42	machine	machine	NOUN
ajst-20195	7	43	(	(	PUNCT
ajst-20195	7	44	elm	elm	PROPN
ajst-20195	7	45	)	)	PUNCT
ajst-20195	7	46	,	,	PUNCT
ajst-20195	7	47	were	be	AUX
ajst-20195	7	48	employed	employ	VERB
ajst-20195	7	49	to	to	PART
ajst-20195	7	50	build	build	VERB
ajst-20195	7	51	the	the	DET
ajst-20195	7	52	inverse	inverse	NOUN
ajst-20195	7	53	model	model	NOUN
ajst-20195	7	54	of	of	ADP
ajst-20195	7	55	soil	soil	NOUN
ajst-20195	7	56	salt	salt	NOUN
ajst-20195	7	57	content	content	NOUN
ajst-20195	7	58	.	.	PUNCT
ajst-20195	8	1	the	the	DET
ajst-20195	8	2	results	result	NOUN
ajst-20195	8	3	showed	show	VERB
ajst-20195	8	4	that	that	SCONJ
ajst-20195	8	5	the	the	DET
ajst-20195	8	6	random	random	ADJ
ajst-20195	8	7	forest	forest	NOUN
ajst-20195	8	8	model	model	NOUN
ajst-20195	8	9	based	base	VERB
ajst-20195	8	10	on	on	ADP
ajst-20195	8	11	sentinel-2	sentinel-2	ADJ
ajst-20195	8	12	imagery	imagery	NOUN
ajst-20195	8	13	performed	perform	VERB
ajst-20195	8	14	the	the	DET
ajst-20195	8	15	best	good	ADJ
ajst-20195	8	16	in	in	ADP
ajst-20195	8	17	the	the	DET
ajst-20195	8	18	inversion	inversion	NOUN
ajst-20195	8	19	with	with	ADP
ajst-20195	8	20	good	good	ADJ
ajst-20195	8	21	prediction	prediction	NOUN
ajst-20195	8	22	results	result	NOUN
ajst-20195	8	23	,	,	PUNCT
ajst-20195	8	24	with	with	ADP
ajst-20195	8	25	r2	r2	PROPN
ajst-20195	8	26	and	and	CCONJ
ajst-20195	8	27	re	re	NOUN
ajst-20195	8	28	of	of	ADP
ajst-20195	8	29	0.825	0.825	NUM
ajst-20195	8	30	and	and	CCONJ
ajst-20195	8	31	0.207	0.207	NUM
ajst-20195	8	32	and	and	CCONJ
ajst-20195	8	33	0.711	0.711	NUM
ajst-20195	8	34	and	and	CCONJ
ajst-20195	8	35	0.271	0.271	NUM
ajst-20195	8	36	in	in	ADP
ajst-20195	8	37	spring	spring	NOUN
ajst-20195	8	38	and	and	CCONJ
ajst-20195	8	39	summer	summer	NOUN
ajst-20195	8	40	,	,	PUNCT
ajst-20195	8	41	respectively.the	respectively.the	DET
ajst-20195	8	42	study	study	NOUN
ajst-20195	8	43	also	also	ADV
ajst-20195	8	44	revealed	reveal	VERB
ajst-20195	8	45	that	that	SCONJ
ajst-20195	8	46	soil	soil	NOUN
ajst-20195	8	47	salinity	salinity	NOUN
ajst-20195	8	48	varied	vary	VERB
ajst-20195	8	49	significantly	significantly	ADV
ajst-20195	8	50	between	between	ADP
ajst-20195	8	51	seasons	season	NOUN
ajst-20195	8	52	,	,	PUNCT
ajst-20195	8	53	and	and	CCONJ
ajst-20195	8	54	was	be	AUX
ajst-20195	8	55	higher	high	ADJ
ajst-20195	8	56	in	in	ADP
ajst-20195	8	57	spring	spring	NOUN
ajst-20195	8	58	than	than	ADP
ajst-20195	8	59	in	in	ADP
ajst-20195	8	60	summer	summer	NOUN
ajst-20195	8	61	.	.	PUNCT
ajst-20195	9	1	this	this	DET
ajst-20195	9	2	result	result	NOUN
ajst-20195	9	3	is	be	AUX
ajst-20195	9	4	of	of	ADP
ajst-20195	9	5	great	great	ADJ
ajst-20195	9	6	significance	significance	NOUN
ajst-20195	9	7	as	as	ADP
ajst-20195	9	8	a	a	DET
ajst-20195	9	9	guide	guide	NOUN
ajst-20195	9	10	for	for	ADP
ajst-20195	9	11	soil	soil	NOUN
ajst-20195	9	12	salinity	salinity	NOUN
ajst-20195	9	13	monitoring	monitoring	NOUN
ajst-20195	9	14	and	and	CCONJ
ajst-20195	9	15	land	land	NOUN
ajst-20195	9	16	reclamation	reclamation	NOUN
ajst-20195	9	17	in	in	ADP
ajst-20195	9	18	arid	arid	NOUN
ajst-20195	9	19	or	or	CCONJ
ajst-20195	9	20	semi	semi	ADJ
ajst-20195	9	21	-	-	ADJ
ajst-20195	9	22	arid	arid	ADJ
ajst-20195	9	23	regions	region	NOUN
ajst-20195	9	24	.	.	PUNCT
ajst-20195	10	1	keywords	keyword	NOUN
ajst-20195	10	2	:	:	PUNCT
ajst-20195	10	3	satellite	satellite	NOUN
ajst-20195	10	4	remote	remote	ADJ
ajst-20195	10	5	sensing	sensing	NOUN
ajst-20195	10	6	,	,	PUNCT
ajst-20195	10	7	variable	variable	ADJ
ajst-20195	10	8	screening	screening	NOUN
ajst-20195	10	9	,	,	PUNCT
ajst-20195	10	10	inversion	inversion	NOUN
ajst-20195	10	11	modelling	modelling	NOUN
ajst-20195	10	12	,	,	PUNCT
ajst-20195	10	13	spectral	spectral	ADJ
ajst-20195	10	14	indices	index	NOUN
ajst-20195	10	15	;	;	PUNCT
ajst-20195	10	16	machine	machine	NOUN
ajst-20195	10	17	learning	learning	NOUN
ajst-20195	10	18	.	.	PUNCT
ajst-20195	11	1	1	1	X
ajst-20195	11	2	.	.	X
ajst-20195	11	3	introduction	introduction	NOUN
ajst-20195	11	4	soil	soil	NOUN
ajst-20195	11	5	salinisation	salinisation	NOUN
ajst-20195	11	6	is	be	AUX
ajst-20195	11	7	a	a	DET
ajst-20195	11	8	global	global	ADJ
ajst-20195	11	9	problem	problem	NOUN
ajst-20195	11	10	that	that	PRON
ajst-20195	11	11	seriously	seriously	ADV
ajst-20195	11	12	affects	affect	VERB
ajst-20195	11	13	soil	soil	NOUN
ajst-20195	11	14	resources	resource	NOUN
ajst-20195	11	15	and	and	CCONJ
ajst-20195	11	16	ecosystems	ecosystem	NOUN
ajst-20195	11	17	.	.	PUNCT
ajst-20195	12	1	more	more	ADJ
ajst-20195	12	2	than	than	ADP
ajst-20195	12	3	1	1	NUM
ajst-20195	12	4	billion	billion	NUM
ajst-20195	12	5	hectares	hectare	NOUN
ajst-20195	12	6	of	of	ADP
ajst-20195	12	7	land	land	NOUN
ajst-20195	12	8	in	in	ADP
ajst-20195	12	9	hundreds	hundred	NOUN
ajst-20195	12	10	of	of	ADP
ajst-20195	12	11	countries	country	NOUN
ajst-20195	12	12	and	and	CCONJ
ajst-20195	12	13	regions	region	NOUN
ajst-20195	12	14	around	around	ADP
ajst-20195	12	15	the	the	DET
ajst-20195	12	16	world	world	NOUN
ajst-20195	12	17	are	be	AUX
ajst-20195	12	18	threatened	threaten	VERB
ajst-20195	12	19	by	by	ADP
ajst-20195	12	20	salinity	salinity	NOUN
ajst-20195	12	21	problems	problem	NOUN
ajst-20195	12	22	.	.	PUNCT
ajst-20195	13	1	high	high	ADJ
ajst-20195	13	2	levels	level	NOUN
ajst-20195	13	3	of	of	ADP
ajst-20195	13	4	soil	soil	NOUN
ajst-20195	13	5	salts	salt	NOUN
ajst-20195	13	6	are	be	AUX
ajst-20195	13	7	detrimental	detrimental	ADJ
ajst-20195	13	8	to	to	ADP
ajst-20195	13	9	crop	crop	NOUN
ajst-20195	13	10	growth	growth	NOUN
ajst-20195	13	11	,	,	PUNCT
ajst-20195	13	12	directly	directly	ADV
ajst-20195	13	13	affecting	affect	VERB
ajst-20195	13	14	crop	crop	NOUN
ajst-20195	13	15	yields	yield	NOUN
ajst-20195	13	16	and	and	CCONJ
ajst-20195	13	17	threatening	threaten	VERB
ajst-20195	13	18	land	land	NOUN
ajst-20195	13	19	quality	quality	NOUN
ajst-20195	13	20	and	and	CCONJ
ajst-20195	13	21	sustainable	sustainable	ADJ
ajst-20195	13	22	development	development	NOUN
ajst-20195	13	23	and	and	CCONJ
ajst-20195	13	24	use	use	NOUN
ajst-20195	13	25	,	,	PUNCT
ajst-20195	13	26	as	as	ADV
ajst-20195	13	27	well	well	ADV
ajst-20195	13	28	as	as	ADP
ajst-20195	13	29	sustainable	sustainable	ADJ
ajst-20195	13	30	agriculture[1	agriculture[1	NOUN
ajst-20195	13	31	]	]	PUNCT
ajst-20195	13	32	.	.	PUNCT
ajst-20195	14	1	accumulation	accumulation	NOUN
ajst-20195	14	2	of	of	ADP
ajst-20195	14	3	salt	salt	NOUN
ajst-20195	14	4	leads	lead	VERB
ajst-20195	14	5	to	to	ADP
ajst-20195	14	6	soil	soil	NOUN
ajst-20195	14	7	degradation	degradation	NOUN
ajst-20195	14	8	,	,	PUNCT
ajst-20195	14	9	especially	especially	ADV
ajst-20195	14	10	in	in	ADP
ajst-20195	14	11	arid	arid	NOUN
ajst-20195	14	12	and	and	CCONJ
ajst-20195	14	13	semi	semi	ADJ
ajst-20195	14	14	-	-	ADJ
ajst-20195	14	15	arid	arid	ADJ
ajst-20195	14	16	areas	area	NOUN
ajst-20195	14	17	.	.	PUNCT
ajst-20195	15	1	due	due	ADP
ajst-20195	15	2	to	to	ADP
ajst-20195	15	3	environmental	environmental	ADJ
ajst-20195	15	4	,	,	PUNCT
ajst-20195	15	5	social	social	ADJ
ajst-20195	15	6	and	and	CCONJ
ajst-20195	15	7	economic	economic	ADJ
ajst-20195	15	8	backwardness	backwardness	NOUN
ajst-20195	15	9	,	,	PUNCT
ajst-20195	15	10	in	in	ADP
ajst-20195	15	11	arid	arid	NOUN
ajst-20195	15	12	and	and	CCONJ
ajst-20195	15	13	semi	semi	ADJ
ajst-20195	15	14	-	-	ADJ
ajst-20195	15	15	arid	arid	ADJ
ajst-20195	15	16	areas	area	NOUN
ajst-20195	15	17	,	,	PUNCT
ajst-20195	15	18	salts	salt	NOUN
ajst-20195	15	19	migrate	migrate	VERB
ajst-20195	15	20	from	from	ADP
ajst-20195	15	21	deeper	deep	ADJ
ajst-20195	15	22	soil	soil	NOUN
ajst-20195	15	23	layers	layer	NOUN
ajst-20195	15	24	and	and	CCONJ
ajst-20195	15	25	accumulate	accumulate	VERB
ajst-20195	15	26	in	in	ADP
ajst-20195	15	27	topsoil	topsoil	NOUN
ajst-20195	15	28	with	with	ADP
ajst-20195	15	29	evaporative	evaporative	ADJ
ajst-20195	15	30	water	water	NOUN
ajst-20195	15	31	intensive	intensive	ADJ
ajst-20195	15	32	irrigated	irrigate	VERB
ajst-20195	15	33	agricultural	agricultural	ADJ
ajst-20195	15	34	production	production	NOUN
ajst-20195	15	35	.	.	PUNCT
ajst-20195	16	1	rational	rational	ADJ
ajst-20195	16	2	use	use	NOUN
ajst-20195	16	3	of	of	ADP
ajst-20195	16	4	salinity	salinity	NOUN
ajst-20195	16	5	-	-	PUNCT
ajst-20195	16	6	affected	affect	VERB
ajst-20195	16	7	lands	land	NOUN
ajst-20195	16	8	can	can	AUX
ajst-20195	16	9	increase	increase	VERB
ajst-20195	16	10	the	the	DET
ajst-20195	16	11	area	area	NOUN
ajst-20195	16	12	of	of	ADP
ajst-20195	16	13	arable	arable	ADJ
ajst-20195	16	14	land	land	NOUN
ajst-20195	16	15	and	and	CCONJ
ajst-20195	16	16	reduce	reduce	VERB
ajst-20195	16	17	the	the	DET
ajst-20195	16	18	pressure	pressure	NOUN
ajst-20195	16	19	between	between	ADP
ajst-20195	16	20	agricultural	agricultural	ADJ
ajst-20195	16	21	production	production	NOUN
ajst-20195	16	22	and	and	CCONJ
ajst-20195	16	23	urban	urban	ADJ
ajst-20195	16	24	development	development	NOUN
ajst-20195	16	25	.	.	PUNCT
ajst-20195	17	1	effective	effective	ADJ
ajst-20195	17	2	management	management	NOUN
ajst-20195	17	3	of	of	ADP
ajst-20195	17	4	salinityaffected	salinityaffecte	VERB
ajst-20195	17	5	soils	soil	NOUN
ajst-20195	17	6	requires	require	VERB
ajst-20195	17	7	accurate	accurate	ADJ
ajst-20195	17	8	and	and	CCONJ
ajst-20195	17	9	efficient	efficient	ADJ
ajst-20195	17	10	monitoring	monitoring	NOUN
ajst-20195	17	11	and	and	CCONJ
ajst-20195	17	12	mapping	mapping	NOUN
ajst-20195	17	13	of	of	ADP
ajst-20195	17	14	soil	soil	NOUN
ajst-20195	17	15	salinisation	salinisation	NOUN
ajst-20195	17	16	.	.	PUNCT
ajst-20195	18	1	various	various	ADJ
ajst-20195	18	2	methods	method	NOUN
ajst-20195	18	3	and	and	CCONJ
ajst-20195	18	4	platforms	platform	NOUN
ajst-20195	18	5	are	be	AUX
ajst-20195	18	6	being	be	AUX
ajst-20195	18	7	used	use	VERB
ajst-20195	18	8	to	to	PART
ajst-20195	18	9	quantify	quantify	VERB
ajst-20195	18	10	the	the	DET
ajst-20195	18	11	salt	salt	NOUN
ajst-20195	18	12	content	content	NOUN
ajst-20195	18	13	of	of	ADP
ajst-20195	18	14	different	different	ADJ
ajst-20195	18	15	soil	soil	NOUN
ajst-20195	18	16	depth	depth	NOUN
ajst-20195	18	17	intervals	interval	NOUN
ajst-20195	18	18	.	.	PUNCT
ajst-20195	19	1	soil	soil	NOUN
ajst-20195	19	2	electrical	electrical	ADJ
ajst-20195	19	3	conductivity	conductivity	NOUN
ajst-20195	19	4	(	(	PUNCT
ajst-20195	19	5	ec	ec	PROPN
ajst-20195	19	6	)	)	PUNCT
ajst-20195	19	7	is	be	AUX
ajst-20195	19	8	often	often	ADV
ajst-20195	19	9	used	use	VERB
ajst-20195	19	10	for	for	ADP
ajst-20195	19	11	dynamic	dynamic	ADJ
ajst-20195	19	12	monitoring	monitoring	NOUN
ajst-20195	19	13	of	of	ADP
ajst-20195	19	14	soil	soil	NOUN
ajst-20195	19	15	salinity	salinity	NOUN
ajst-20195	19	16	due	due	ADP
ajst-20195	19	17	to	to	ADP
ajst-20195	19	18	its	its	PRON
ajst-20195	19	19	strong	strong	ADJ
ajst-20195	19	20	correlation	correlation	NOUN
ajst-20195	19	21	with	with	ADP
ajst-20195	19	22	soil	soil	NOUN
ajst-20195	19	23	salinity[2	salinity[2	PROPN
ajst-20195	19	24	]	]	X
ajst-20195	19	25	.	.	PUNCT
ajst-20195	20	1	traditional	traditional	ADJ
ajst-20195	20	2	methods	method	NOUN
ajst-20195	20	3	of	of	ADP
ajst-20195	20	4	soil	soil	NOUN
ajst-20195	20	5	conductivity	conductivity	NOUN
ajst-20195	20	6	analysis	analysis	NOUN
ajst-20195	20	7	,	,	PUNCT
ajst-20195	20	8	which	which	PRON
ajst-20195	20	9	mainly	mainly	ADV
ajst-20195	20	10	involve	involve	VERB
ajst-20195	20	11	on	on	ADP
ajst-20195	20	12	-	-	PUNCT
ajst-20195	20	13	site	site	NOUN
ajst-20195	20	14	sampling	sampling	NOUN
ajst-20195	20	15	and	and	CCONJ
ajst-20195	20	16	bringing	bring	VERB
ajst-20195	20	17	soil	soil	NOUN
ajst-20195	20	18	samples	sample	NOUN
ajst-20195	20	19	back	back	ADV
ajst-20195	20	20	to	to	ADP
ajst-20195	20	21	the	the	DET
ajst-20195	20	22	laboratory	laboratory	NOUN
ajst-20195	20	23	for	for	ADP
ajst-20195	20	24	processing	processing	NOUN
ajst-20195	20	25	,	,	PUNCT
ajst-20195	20	26	have	have	VERB
ajst-20195	20	27	high	high	ADJ
ajst-20195	20	28	accuracy	accuracy	NOUN
ajst-20195	20	29	,	,	PUNCT
ajst-20195	20	30	but	but	CCONJ
ajst-20195	20	31	are	be	AUX
ajst-20195	20	32	unable	unable	ADJ
ajst-20195	20	33	to	to	PART
ajst-20195	20	34	monitor	monitor	VERB
ajst-20195	20	35	soil	soil	NOUN
ajst-20195	20	36	salinity	salinity	NOUN
ajst-20195	20	37	on	on	ADP
ajst-20195	20	38	a	a	DET
ajst-20195	20	39	large	large	ADJ
ajst-20195	20	40	scale	scale	NOUN
ajst-20195	20	41	and	and	CCONJ
ajst-20195	20	42	make	make	VERB
ajst-20195	20	43	multiple	multiple	ADJ
ajst-20195	20	44	measurements	measurement	NOUN
ajst-20195	20	45	.	.	PUNCT
ajst-20195	21	1	as	as	ADP
ajst-20195	21	2	an	an	DET
ajst-20195	21	3	alternative	alternative	NOUN
ajst-20195	21	4	,	,	PUNCT
ajst-20195	21	5	satellite	satellite	NOUN
ajst-20195	21	6	remote	remote	ADJ
ajst-20195	21	7	sensing	sensing	NOUN
ajst-20195	21	8	(	(	PUNCT
ajst-20195	21	9	rs	rs	NOUN
ajst-20195	21	10	)	)	PUNCT
ajst-20195	21	11	technology	technology	NOUN
ajst-20195	21	12	can	can	AUX
ajst-20195	21	13	provide	provide	VERB
ajst-20195	21	14	a	a	DET
ajst-20195	21	15	large	large	ADJ
ajst-20195	21	16	amount	amount	NOUN
ajst-20195	21	17	of	of	ADP
ajst-20195	21	18	information	information	NOUN
ajst-20195	21	19	about	about	ADP
ajst-20195	21	20	the	the	DET
ajst-20195	21	21	soil	soil	NOUN
ajst-20195	21	22	,	,	PUNCT
ajst-20195	21	23	and	and	CCONJ
ajst-20195	21	24	the	the	DET
ajst-20195	21	25	satellite	satellite	NOUN
ajst-20195	21	26	remote	remote	ADJ
ajst-20195	21	27	sensing	sensing	NOUN
ajst-20195	21	28	method	method	NOUN
ajst-20195	21	29	has	have	VERB
ajst-20195	21	30	the	the	DET
ajst-20195	21	31	advantages	advantage	NOUN
ajst-20195	21	32	of	of	ADP
ajst-20195	21	33	wide	wide	ADJ
ajst-20195	21	34	spatial	spatial	ADJ
ajst-20195	21	35	coverage	coverage	NOUN
ajst-20195	21	36	and	and	CCONJ
ajst-20195	21	37	high	high	ADJ
ajst-20195	21	38	resolution	resolution	NOUN
ajst-20195	21	39	compared	compare	VERB
ajst-20195	21	40	with	with	ADP
ajst-20195	21	41	traditional	traditional	ADJ
ajst-20195	21	42	field	field	NOUN
ajst-20195	21	43	measurements	measurement	NOUN
ajst-20195	21	44	.	.	PUNCT
ajst-20195	22	1	saline	saline	ADJ
ajst-20195	22	2	soils	soil	NOUN
ajst-20195	22	3	typically	typically	ADV
ajst-20195	22	4	exhibit	exhibit	VERB
ajst-20195	22	5	higher	high	ADJ
ajst-20195	22	6	albedo	albedo	NOUN
ajst-20195	22	7	compared	compare	VERB
ajst-20195	22	8	to	to	ADP
ajst-20195	22	9	non	non	ADJ
ajst-20195	22	10	-	-	ADJ
ajst-20195	22	11	saline	saline	ADJ
ajst-20195	22	12	soils	soil	NOUN
ajst-20195	22	13	and	and	CCONJ
ajst-20195	22	14	salt	salt	NOUN
ajst-20195	22	15	accumulation	accumulation	NOUN
ajst-20195	22	16	on	on	ADP
ajst-20195	22	17	the	the	DET
ajst-20195	22	18	soil	soil	NOUN
ajst-20195	22	19	surface	surface	NOUN
ajst-20195	22	20	can	can	AUX
ajst-20195	22	21	be	be	AUX
ajst-20195	22	22	theoretically	theoretically	ADV
ajst-20195	22	23	observed	observe	VERB
ajst-20195	22	24	using	use	VERB
ajst-20195	22	25	remote	remote	ADJ
ajst-20195	22	26	sensing	sense	VERB
ajst-20195	22	27	imagery	imagery	NOUN
ajst-20195	22	28	.	.	PUNCT
ajst-20195	23	1	optical	optical	ADJ
ajst-20195	23	2	remote	remote	ADJ
ajst-20195	23	3	sensing	sense	VERB
ajst-20195	23	4	satellites	satellite	NOUN
ajst-20195	23	5	can	can	AUX
ajst-20195	23	6	directly	directly	ADV
ajst-20195	23	7	record	record	VERB
ajst-20195	23	8	the	the	DET
ajst-20195	23	9	spectral	spectral	ADJ
ajst-20195	23	10	reflectance	reflectance	NOUN
ajst-20195	23	11	of	of	ADP
ajst-20195	23	12	soil	soil	NOUN
ajst-20195	23	13	salinisation.the	salinisation.the	DET
ajst-20195	23	14	sentinel-2	sentinel-2	NUM
ajst-20195	23	15	satellite	satellite	NOUN
ajst-20195	23	16	equipped	equip	VERB
ajst-20195	23	17	with	with	ADP
ajst-20195	23	18	a	a	DET
ajst-20195	23	19	multispectral	multispectral	ADJ
ajst-20195	23	20	instrument	instrument	NOUN
ajst-20195	23	21	(	(	PUNCT
ajst-20195	23	22	msi	msi	PROPN
ajst-20195	23	23	)	)	PUNCT
ajst-20195	23	24	launched	launch	VERB
ajst-20195	23	25	in	in	ADP
ajst-20195	23	26	2015	2015	NUM
ajst-20195	23	27	provides	provide	VERB
ajst-20195	23	28	13	13	NUM
ajst-20195	23	29	spectral	spectral	ADJ
ajst-20195	23	30	bands	band	NOUN
ajst-20195	23	31	ranging	range	VERB
ajst-20195	23	32	from	from	ADP
ajst-20195	23	33	443	443	NUM
ajst-20195	23	34	nm	nm	NOUN
ajst-20195	23	35	to	to	ADP
ajst-20195	23	36	2,190	2,190	NUM
ajst-20195	23	37	nm	nm	NOUN
ajst-20195	23	38	.	.	PUNCT
ajst-20195	24	1	the	the	DET
ajst-20195	24	2	provided	provide	VERB
ajst-20195	24	3	spectral	spectral	ADJ
ajst-20195	24	4	images	image	NOUN
ajst-20195	24	5	have	have	VERB
ajst-20195	24	6	high	high	ADJ
ajst-20195	24	7	spatial	spatial	ADJ
ajst-20195	24	8	resolution	resolution	NOUN
ajst-20195	24	9	,	,	PUNCT
ajst-20195	24	10	multispectral	multispectral	ADJ
ajst-20195	24	11	bands	band	NOUN
ajst-20195	24	12	and	and	CCONJ
ajst-20195	24	13	short	short	ADJ
ajst-20195	24	14	revisit	revisit	NOUN
ajst-20195	24	15	time	time	NOUN
ajst-20195	24	16	,	,	PUNCT
ajst-20195	24	17	which	which	PRON
ajst-20195	24	18	makes	make	VERB
ajst-20195	24	19	them	they	PRON
ajst-20195	24	20	advantageous	advantageous	ADJ
ajst-20195	24	21	for	for	ADP
ajst-20195	24	22	soil	soil	NOUN
ajst-20195	24	23	monitoring.gorji	monitoring.gorji	NOUN
ajst-20195	24	24	et	et	NOUN
ajst-20195	24	25	al[3	al[3	NOUN
ajst-20195	24	26	]	]	PUNCT
ajst-20195	24	27	detected	detect	VERB
ajst-20195	24	28	soil	soil	NOUN
ajst-20195	24	29	salinity	salinity	NOUN
ajst-20195	24	30	changes	change	NOUN
ajst-20195	24	31	(	(	PUNCT
ajst-20195	24	32	0.0	0.0	NUM
ajst-20195	24	33	-	-	SYM
ajst-20195	24	34	0.2	0.2	NUM
ajst-20195	24	35	m	m	NOUN
ajst-20195	24	36	)	)	PUNCT
ajst-20195	24	37	at	at	ADP
ajst-20195	24	38	the	the	DET
ajst-20195	24	39	field	field	NOUN
ajst-20195	24	40	scale	scale	NOUN
ajst-20195	24	41	using	use	VERB
ajst-20195	24	42	sentinel-2	sentinel-2	ADJ
ajst-20195	24	43	satellite	satellite	NOUN
ajst-20195	24	44	.	.	PUNCT
ajst-20195	25	1	at	at	ADP
ajst-20195	25	2	the	the	DET
ajst-20195	25	3	regional	regional	ADJ
ajst-20195	25	4	scale	scale	NOUN
ajst-20195	25	5	,	,	PUNCT
ajst-20195	25	6	wang	wang	PROPN
ajst-20195	25	7	et	et	PROPN
ajst-20195	25	8	al[4	al[4	PROPN
ajst-20195	25	9	]	]	PUNCT
ajst-20195	25	10	used	use	VERB
ajst-20195	25	11	sentinel-2	sentinel-2	NUM
ajst-20195	25	12	multispectral	multispectral	ADJ
ajst-20195	25	13	scanning	scanning	NOUN
ajst-20195	25	14	imaging	imaging	NOUN
ajst-20195	25	15	(	(	PUNCT
ajst-20195	25	16	msi	msi	PROPN
ajst-20195	25	17	)	)	PUNCT
ajst-20195	25	18	satellite	satellite	NOUN
ajst-20195	25	19	to	to	PART
ajst-20195	25	20	estimate	estimate	VERB
ajst-20195	25	21	surface	surface	NOUN
ajst-20195	25	22	soil	soil	NOUN
ajst-20195	25	23	salinity	salinity	NOUN
ajst-20195	25	24	(	(	PUNCT
ajst-20195	25	25	0.0	0.0	NUM
ajst-20195	25	26	-	-	SYM
ajst-20195	25	27	0.2	0.2	NUM
ajst-20195	25	28	m	m	NOUN
ajst-20195	25	29	)	)	PUNCT
ajst-20195	25	30	in	in	ADP
ajst-20195	25	31	the	the	DET
ajst-20195	25	32	lake	lake	NOUN
ajst-20195	25	33	ebinur	ebinur	NOUN
ajst-20195	25	34	region.bannari	region.bannari	PROPN
ajst-20195	25	35	et	et	NOUN
ajst-20195	25	36	al	al	PROPN
ajst-20195	26	1	[	[	X
ajst-20195	26	2	5	5	NUM
ajst-20195	26	3	]	]	PUNCT
ajst-20195	26	4	applied	apply	VERB
ajst-20195	26	5	vis	vis	X
ajst-20195	26	6	-	-	ADJ
ajst-20195	26	7	nir	nir	ADJ
ajst-20195	26	8	and	and	CCONJ
ajst-20195	26	9	swir	swir	ADJ
ajst-20195	26	10	spectral	spectral	ADJ
ajst-20195	26	11	bands	band	NOUN
ajst-20195	26	12	of	of	ADP
ajst-20195	26	13	sentinel	sentinel	ADJ
ajst-20195	26	14	2	2	NUM
ajst-20195	26	15	-	-	PUNCT
ajst-20195	26	16	msi	msi	NOUN
ajst-20195	26	17	for	for	ADP
ajst-20195	26	18	soil	soil	NOUN
ajst-20195	26	19	salinity	salinity	NOUN
ajst-20195	26	20	detection	detection	NOUN
ajst-20195	26	21	in	in	ADP
ajst-20195	26	22	the	the	DET
ajst-20195	26	23	kingdom	kingdom	NOUN
ajst-20195	26	24	of	of	ADP
ajst-20195	26	25	bahrain	bahrain	NOUN
ajst-20195	26	26	and	and	CCONJ
ajst-20195	26	27	showed	show	VERB
ajst-20195	26	28	that	that	SCONJ
ajst-20195	26	29	the	the	DET
ajst-20195	26	30	data	datum	NOUN
ajst-20195	26	31	's	's	PART
ajst-20195	26	32	potential	potential	NOUN
ajst-20195	26	33	in	in	ADP
ajst-20195	26	34	soil	soil	NOUN
ajst-20195	26	35	salinity	salinity	NOUN
ajst-20195	26	36	discrimination	discrimination	NOUN
ajst-20195	26	37	.	.	PUNCT
ajst-20195	27	1	based	base	VERB
ajst-20195	27	2	on	on	ADP
ajst-20195	27	3	remote	remote	ADJ
ajst-20195	27	4	sensing	sense	VERB
ajst-20195	27	5	imagery	imagery	NOUN
ajst-20195	27	6	,	,	PUNCT
ajst-20195	27	7	researchers	researcher	NOUN
ajst-20195	27	8	have	have	AUX
ajst-20195	27	9	developed	develop	VERB
ajst-20195	27	10	various	various	ADJ
ajst-20195	27	11	vegetation	vegetation	NOUN
ajst-20195	27	12	,	,	PUNCT
ajst-20195	27	13	salinity	salinity	NOUN
ajst-20195	27	14	and	and	CCONJ
ajst-20195	27	15	soil	soil	NOUN
ajst-20195	27	16	indices	index	NOUN
ajst-20195	27	17	to	to	PART
ajst-20195	27	18	estimate	estimate	VERB
ajst-20195	27	19	soil	soil	NOUN
ajst-20195	27	20	salinity	salinity	NOUN
ajst-20195	27	21	[	[	X
ajst-20195	27	22	6	6	NUM
ajst-20195	27	23	]	]	PUNCT
ajst-20195	27	24	.	.	PUNCT
ajst-20195	28	1	in	in	ADP
ajst-20195	28	2	addition	addition	NOUN
ajst-20195	28	3	,	,	PUNCT
ajst-20195	28	4	many	many	ADJ
ajst-20195	28	5	modelling	modelling	NOUN
ajst-20195	28	6	approaches	approach	NOUN
ajst-20195	28	7	such	such	ADJ
ajst-20195	28	8	as	as	ADP
ajst-20195	28	9	partial	partial	ADJ
ajst-20195	28	10	least	least	ADJ
ajst-20195	28	11	squares	square	NOUN
ajst-20195	28	12	regression	regression	NOUN
ajst-20195	28	13	,	,	PUNCT
ajst-20195	28	14	random	random	ADJ
ajst-20195	28	15	forest	forest	NOUN
ajst-20195	28	16	,	,	PUNCT
ajst-20195	28	17	support	support	NOUN
ajst-20195	28	18	vector	vector	NOUN
ajst-20195	28	19	machine	machine	NOUN
ajst-20195	28	20	regression	regression	NOUN
ajst-20195	28	21	,	,	PUNCT
ajst-20195	28	22	artificial	artificial	ADJ
ajst-20195	28	23	neural	neural	ADJ
ajst-20195	28	24	networks	network	NOUN
ajst-20195	28	25	and	and	CCONJ
ajst-20195	28	26	convolutional	convolutional	ADJ
ajst-20195	28	27	neural	neural	ADJ
ajst-20195	28	28	networks	network	NOUN
ajst-20195	28	29	have	have	AUX
ajst-20195	28	30	been	be	AUX
ajst-20195	28	31	widely	widely	ADV
ajst-20195	28	32	used	use	VERB
ajst-20195	28	33	to	to	PART
ajst-20195	28	34	predict	predict	VERB
ajst-20195	28	35	soil	soil	NOUN
ajst-20195	28	36	salinity	salinity	NOUN
ajst-20195	28	37	changes	change	NOUN
ajst-20195	28	38	.	.	PUNCT
ajst-20195	29	1	in	in	ADP
ajst-20195	29	2	order	order	NOUN
ajst-20195	29	3	to	to	PART
ajst-20195	29	4	improve	improve	VERB
ajst-20195	29	5	the	the	DET
ajst-20195	29	6	model	model	NOUN
ajst-20195	29	7	performance	performance	NOUN
ajst-20195	29	8	,	,	PUNCT
ajst-20195	29	9	methods	method	NOUN
ajst-20195	29	10	such	such	ADJ
ajst-20195	29	11	as	as	ADP
ajst-20195	29	12	pearson	pearson	PROPN
ajst-20195	29	13	correlation	correlation	NOUN
ajst-20195	29	14	analysis	analysis	NOUN
ajst-20195	29	15	,	,	PUNCT
ajst-20195	29	16	grey	grey	ADJ
ajst-20195	29	17	correlation	correlation	NOUN
ajst-20195	29	18	analysis	analysis	NOUN
ajst-20195	29	19	,	,	PUNCT
ajst-20195	29	20	genetic	genetic	ADJ
ajst-20195	29	21	algorithms	algorithm	NOUN
ajst-20195	29	22	,	,	PUNCT
ajst-20195	29	23	and	and	CCONJ
ajst-20195	29	24	random	random	ADJ
ajst-20195	29	25	forests	forest	NOUN
ajst-20195	29	26	have	have	AUX
ajst-20195	29	27	been	be	AUX
ajst-20195	29	28	used	use	VERB
ajst-20195	29	29	to	to	PART
ajst-20195	29	30	select	select	VERB
ajst-20195	29	31	the	the	DET
ajst-20195	29	32	best	good	ADJ
ajst-20195	29	33	covariates	covariate	NOUN
ajst-20195	29	34	to	to	PART
ajst-20195	29	35	be	be	AUX
ajst-20195	29	36	used	use	VERB
ajst-20195	29	37	in	in	ADP
ajst-20195	29	38	the	the	DET
ajst-20195	29	39	final	final	ADJ
ajst-20195	29	40	model	model	NOUN
ajst-20195	29	41	.	.	PUNCT
ajst-20195	30	1	however	however	ADV
ajst-20195	30	2	,	,	PUNCT
ajst-20195	30	3	the	the	DET
ajst-20195	30	4	contribution	contribution	NOUN
ajst-20195	30	5	of	of	ADP
ajst-20195	30	6	different	different	ADJ
ajst-20195	30	7	remote	remote	ADJ
ajst-20195	30	8	sensing	sense	VERB
ajst-20195	30	9	indices	index	NOUN
ajst-20195	30	10	(	(	PUNCT
ajst-20195	30	11	or	or	CCONJ
ajst-20195	30	12	covariates	covariate	VERB
ajst-20195	30	13	)	)	PUNCT
ajst-20195	30	14	to	to	ADP
ajst-20195	30	15	the	the	DET
ajst-20195	30	16	salt	salt	NOUN
ajst-20195	30	17	estimation	estimation	NOUN
ajst-20195	30	18	model	model	NOUN
ajst-20195	30	19	is	be	AUX
ajst-20195	30	20	site	site	NOUN
ajst-20195	30	21	-	-	PUNCT
ajst-20195	30	22	specific	specific	ADJ
ajst-20195	30	23	as	as	SCONJ
ajst-20195	30	24	they	they	PRON
ajst-20195	30	25	are	be	AUX
ajst-20195	30	26	affected	affect	VERB
ajst-20195	30	27	by	by	ADP
ajst-20195	30	28	land	land	NOUN
ajst-20195	30	29	cover	cover	NOUN
ajst-20195	30	30	type	type	NOUN
ajst-20195	30	31	and	and	CCONJ
ajst-20195	30	32	other	other	ADJ
ajst-20195	30	33	surface	surface	NOUN
ajst-20195	30	34	parameters	parameter	NOUN
ajst-20195	30	35	.	.	PUNCT
ajst-20195	31	1	101	101	NUM
ajst-20195	31	2	therefore	therefore	ADV
ajst-20195	31	3	,	,	PUNCT
ajst-20195	31	4	in	in	ADP
ajst-20195	31	5	this	this	DET
ajst-20195	31	6	study	study	NOUN
ajst-20195	31	7	,	,	PUNCT
ajst-20195	31	8	the	the	DET
ajst-20195	31	9	feasibility	feasibility	NOUN
ajst-20195	31	10	of	of	ADP
ajst-20195	31	11	using	use	VERB
ajst-20195	31	12	the	the	DET
ajst-20195	31	13	multispectral	multispectral	ADJ
ajst-20195	31	14	instrument	instrument	NOUN
ajst-20195	31	15	(	(	PUNCT
ajst-20195	31	16	msi	msi	PROPN
ajst-20195	31	17	)	)	PUNCT
ajst-20195	31	18	on	on	ADP
ajst-20195	31	19	board	board	NOUN
ajst-20195	31	20	the	the	DET
ajst-20195	31	21	sentinel-2	sentinel-2	ADJ
ajst-20195	31	22	satellite	satellite	NOUN
ajst-20195	31	23	in	in	ADP
ajst-20195	31	24	conjunction	conjunction	NOUN
ajst-20195	31	25	with	with	ADP
ajst-20195	31	26	a	a	DET
ajst-20195	31	27	machine	machine	NOUN
ajst-20195	31	28	learning	learn	VERB
ajst-20195	31	29	model	model	NOUN
ajst-20195	31	30	to	to	PART
ajst-20195	31	31	accurately	accurately	ADV
ajst-20195	31	32	monitor	monitor	VERB
ajst-20195	31	33	soil	soil	NOUN
ajst-20195	31	34	salinity	salinity	NOUN
ajst-20195	31	35	content	content	NOUN
ajst-20195	31	36	during	during	ADP
ajst-20195	31	37	the	the	DET
ajst-20195	31	38	spring	spring	NOUN
ajst-20195	31	39	and	and	CCONJ
ajst-20195	31	40	summer	summer	NOUN
ajst-20195	31	41	seasons	season	NOUN
ajst-20195	31	42	was	be	AUX
ajst-20195	31	43	explored	explore	VERB
ajst-20195	31	44	.	.	PUNCT
ajst-20195	32	1	and	and	CCONJ
ajst-20195	32	2	three	three	NUM
ajst-20195	32	3	additional	additional	ADJ
ajst-20195	32	4	red	red	ADJ
ajst-20195	32	5	-	-	PUNCT
ajst-20195	32	6	edge	edge	NOUN
ajst-20195	32	7	bands	band	NOUN
ajst-20195	32	8	(	(	PUNCT
ajst-20195	32	9	b5	b5	PROPN
ajst-20195	32	10	-	-	PUNCT
ajst-20195	32	11	b7	b7	PROPN
ajst-20195	32	12	)	)	PUNCT
ajst-20195	32	13	were	be	AUX
ajst-20195	32	14	used	use	VERB
ajst-20195	32	15	instead	instead	ADV
ajst-20195	32	16	of	of	ADP
ajst-20195	32	17	the	the	DET
ajst-20195	32	18	traditional	traditional	ADJ
ajst-20195	32	19	red	red	ADJ
ajst-20195	32	20	band	band	NOUN
ajst-20195	32	21	(	(	PUNCT
ajst-20195	32	22	b4	b4	NOUN
ajst-20195	32	23	)	)	PUNCT
ajst-20195	32	24	to	to	PART
ajst-20195	32	25	generate	generate	VERB
ajst-20195	32	26	potential	potential	ADJ
ajst-20195	32	27	soil	soil	NOUN
ajst-20195	32	28	salinity	salinity	NOUN
ajst-20195	32	29	indices	index	NOUN
ajst-20195	32	30	.	.	PUNCT
ajst-20195	33	1	a	a	DET
ajst-20195	33	2	screening	screening	NOUN
ajst-20195	33	3	method	method	NOUN
ajst-20195	33	4	based	base	VERB
ajst-20195	33	5	on	on	ADP
ajst-20195	33	6	the	the	DET
ajst-20195	33	7	pls	pls	ADJ
ajst-20195	33	8	-	-	PUNCT
ajst-20195	33	9	vip	vip	NOUN
ajst-20195	33	10	criterion	criterion	NOUN
ajst-20195	33	11	was	be	AUX
ajst-20195	33	12	used	use	VERB
ajst-20195	33	13	to	to	PART
ajst-20195	33	14	screen	screen	VERB
ajst-20195	33	15	the	the	DET
ajst-20195	33	16	spectral	spectral	ADJ
ajst-20195	33	17	covariates	covariate	NOUN
ajst-20195	33	18	,	,	PUNCT
ajst-20195	33	19	and	and	CCONJ
ajst-20195	33	20	three	three	NUM
ajst-20195	33	21	machine	machine	NOUN
ajst-20195	33	22	learning	learning	NOUN
ajst-20195	33	23	methods	method	NOUN
ajst-20195	33	24	,	,	PUNCT
ajst-20195	33	25	namely	namely	ADV
ajst-20195	33	26	,	,	PUNCT
ajst-20195	33	27	random	random	ADJ
ajst-20195	33	28	forest	forest	NOUN
ajst-20195	33	29	(	(	PUNCT
ajst-20195	33	30	rf	rf	NOUN
ajst-20195	33	31	)	)	PUNCT
ajst-20195	33	32	,	,	PUNCT
ajst-20195	33	33	support	support	NOUN
ajst-20195	33	34	vector	vector	NOUN
ajst-20195	33	35	machine	machine	NOUN
ajst-20195	33	36	(	(	PUNCT
ajst-20195	33	37	svm	svm	PROPN
ajst-20195	33	38	)	)	PUNCT
ajst-20195	33	39	and	and	CCONJ
ajst-20195	33	40	extreme	extreme	ADJ
ajst-20195	33	41	learning	learning	NOUN
ajst-20195	33	42	machine	machine	NOUN
ajst-20195	33	43	(	(	PUNCT
ajst-20195	33	44	elm	elm	PROPN
ajst-20195	33	45	)	)	PUNCT
ajst-20195	33	46	,	,	PUNCT
ajst-20195	33	47	were	be	AUX
ajst-20195	33	48	employed	employ	VERB
ajst-20195	33	49	to	to	PART
ajst-20195	33	50	build	build	VERB
ajst-20195	33	51	the	the	DET
ajst-20195	33	52	inverse	inverse	NOUN
ajst-20195	33	53	model	model	NOUN
ajst-20195	33	54	of	of	ADP
ajst-20195	33	55	soil	soil	NOUN
ajst-20195	33	56	salt	salt	NOUN
ajst-20195	33	57	content	content	NOUN
ajst-20195	33	58	.	.	PUNCT
ajst-20195	34	1	2	2	X
ajst-20195	34	2	.	.	X
ajst-20195	34	3	materials	material	NOUN
ajst-20195	34	4	and	and	CCONJ
ajst-20195	34	5	methods	method	NOUN
ajst-20195	34	6	2.1	2.1	NUM
ajst-20195	34	7	.	.	PUNCT
ajst-20195	35	1	overview	overview	NOUN
ajst-20195	35	2	of	of	ADP
ajst-20195	35	3	the	the	DET
ajst-20195	35	4	study	study	NOUN
ajst-20195	35	5	area	area	NOUN
ajst-20195	35	6	the	the	DET
ajst-20195	35	7	study	study	NOUN
ajst-20195	35	8	area	area	NOUN
ajst-20195	35	9	is	be	AUX
ajst-20195	35	10	located	locate	VERB
ajst-20195	35	11	in	in	ADP
ajst-20195	35	12	huinong	huinong	PROPN
ajst-20195	35	13	district	district	NOUN
ajst-20195	35	14	,	,	PUNCT
ajst-20195	35	15	shizuishan	shizuishan	PROPN
ajst-20195	35	16	city	city	PROPN
ajst-20195	35	17	,	,	PUNCT
ajst-20195	35	18	ningxia	ningxia	PROPN
ajst-20195	35	19	hui	hui	PROPN
ajst-20195	35	20	autonomous	autonomous	PROPN
ajst-20195	35	21	region	region	NOUN
ajst-20195	35	22	.	.	PUNCT
ajst-20195	36	1	its	its	PRON
ajst-20195	36	2	geographical	geographical	ADJ
ajst-20195	36	3	coordinates	coordinate	NOUN
ajst-20195	36	4	are	be	AUX
ajst-20195	36	5	between	between	ADP
ajst-20195	36	6	38	38	NUM
ajst-20195	36	7	°	°	NUM
ajst-20195	36	8	05	05	NUM
ajst-20195	36	9	'	'	PUNCT
ajst-20195	36	10	and	and	CCONJ
ajst-20195	36	11	38	38	NUM
ajst-20195	36	12	°	°	NUM
ajst-20195	36	13	38	38	NUM
ajst-20195	36	14	'	'	PART
ajst-20195	36	15	north	north	NOUN
ajst-20195	36	16	latitude	latitude	NOUN
ajst-20195	36	17	and	and	CCONJ
ajst-20195	36	18	105	105	NUM
ajst-20195	36	19	°	°	NUM
ajst-20195	36	20	07	07	NUM
ajst-20195	36	21	'	'	PUNCT
ajst-20195	36	22	and	and	CCONJ
ajst-20195	36	23	106	106	NUM
ajst-20195	36	24	°	°	NUM
ajst-20195	36	25	09	09	NUM
ajst-20195	36	26	'	'	PART
ajst-20195	36	27	east	east	NOUN
ajst-20195	36	28	longitude	longitude	NOUN
ajst-20195	36	29	.	.	PUNCT
ajst-20195	37	1	the	the	DET
ajst-20195	37	2	area	area	NOUN
ajst-20195	37	3	is	be	AUX
ajst-20195	37	4	relatively	relatively	ADV
ajst-20195	37	5	flat	flat	ADJ
ajst-20195	37	6	and	and	CCONJ
ajst-20195	37	7	is	be	AUX
ajst-20195	37	8	one	one	NUM
ajst-20195	37	9	of	of	ADP
ajst-20195	37	10	the	the	DET
ajst-20195	37	11	important	important	ADJ
ajst-20195	37	12	agricultural	agricultural	ADJ
ajst-20195	37	13	production	production	NOUN
ajst-20195	37	14	areas	area	NOUN
ajst-20195	37	15	in	in	ADP
ajst-20195	37	16	ningxia	ningxia	PROPN
ajst-20195	37	17	.	.	PUNCT
ajst-20195	38	1	it	it	PRON
ajst-20195	38	2	is	be	AUX
ajst-20195	38	3	a	a	DET
ajst-20195	38	4	typical	typical	ADJ
ajst-20195	38	5	inland	inland	ADJ
ajst-20195	38	6	arid	arid	NOUN
ajst-20195	38	7	climate	climate	NOUN
ajst-20195	38	8	zone	zone	NOUN
ajst-20195	38	9	with	with	ADP
ajst-20195	38	10	large	large	ADJ
ajst-20195	38	11	temperature	temperature	NOUN
ajst-20195	38	12	differences	difference	NOUN
ajst-20195	38	13	between	between	ADP
ajst-20195	38	14	seasons	season	NOUN
ajst-20195	38	15	.	.	PUNCT
ajst-20195	39	1	the	the	DET
ajst-20195	39	2	average	average	ADJ
ajst-20195	39	3	annual	annual	ADJ
ajst-20195	39	4	precipitation	precipitation	NOUN
ajst-20195	39	5	is	be	AUX
ajst-20195	39	6	292	292	NUM
ajst-20195	39	7	mm	mm	NOUN
ajst-20195	39	8	;	;	PUNCT
ajst-20195	39	9	the	the	DET
ajst-20195	39	10	average	average	ADJ
ajst-20195	39	11	annual	annual	ADJ
ajst-20195	39	12	evaporation	evaporation	NOUN
ajst-20195	39	13	is	be	AUX
ajst-20195	39	14	2,444	2,444	NUM
ajst-20195	39	15	mm	mm	NOUN
ajst-20195	39	16	,	,	PUNCT
ajst-20195	39	17	mainly	mainly	ADV
ajst-20195	39	18	in	in	ADP
ajst-20195	39	19	summer	summer	NOUN
ajst-20195	39	20	and	and	CCONJ
ajst-20195	39	21	autumn	autumn	NOUN
ajst-20195	39	22	.	.	PUNCT
ajst-20195	40	1	crop	crop	NOUN
ajst-20195	40	2	cultivation	cultivation	NOUN
ajst-20195	40	3	is	be	AUX
ajst-20195	40	4	dominated	dominate	VERB
ajst-20195	40	5	by	by	ADP
ajst-20195	40	6	maize	maize	NOUN
ajst-20195	40	7	,	,	PUNCT
ajst-20195	40	8	and	and	CCONJ
ajst-20195	40	9	it	it	PRON
ajst-20195	40	10	is	be	AUX
ajst-20195	40	11	one	one	NUM
ajst-20195	40	12	of	of	ADP
ajst-20195	40	13	the	the	DET
ajst-20195	40	14	regions	region	NOUN
ajst-20195	40	15	in	in	ADP
ajst-20195	40	16	china	china	PROPN
ajst-20195	40	17	with	with	ADP
ajst-20195	40	18	a	a	DET
ajst-20195	40	19	high	high	ADJ
ajst-20195	40	20	concentration	concentration	NOUN
ajst-20195	40	21	of	of	ADP
ajst-20195	40	22	saline	saline	NOUN
ajst-20195	40	23	and	and	CCONJ
ajst-20195	40	24	alkaline	alkaline	NOUN
ajst-20195	40	25	land	land	NOUN
ajst-20195	40	26	,	,	PUNCT
ajst-20195	40	27	with	with	ADP
ajst-20195	40	28	relatively	relatively	ADV
ajst-20195	40	29	serious	serious	ADJ
ajst-20195	40	30	problems	problem	NOUN
ajst-20195	40	31	of	of	ADP
ajst-20195	40	32	soil	soil	NOUN
ajst-20195	40	33	salinisation	salinisation	NOUN
ajst-20195	40	34	.	.	PUNCT
ajst-20195	41	1	2.2	2.2	NUM
ajst-20195	41	2	.	.	PUNCT
ajst-20195	41	3	experimental	experimental	ADJ
ajst-20195	41	4	data	datum	NOUN
ajst-20195	41	5	collection	collection	NOUN
ajst-20195	41	6	and	and	CCONJ
ajst-20195	41	7	preprocessing	preprocesse	VERB
ajst-20195	41	8	2.2.1	2.2.1	NUM
ajst-20195	41	9	.	.	PUNCT
ajst-20195	42	1	collection	collection	NOUN
ajst-20195	42	2	and	and	CCONJ
ajst-20195	42	3	determination	determination	NOUN
ajst-20195	42	4	of	of	ADP
ajst-20195	42	5	soil	soil	NOUN
ajst-20195	42	6	samples	sample	VERB
ajst-20195	42	7	a	a	DET
ajst-20195	42	8	combination	combination	NOUN
ajst-20195	42	9	of	of	ADP
ajst-20195	42	10	soil	soil	NOUN
ajst-20195	42	11	type	type	NOUN
ajst-20195	42	12	,	,	PUNCT
ajst-20195	42	13	soil	soil	NOUN
ajst-20195	42	14	surface	surface	NOUN
ajst-20195	42	15	characteristics	characteristic	NOUN
ajst-20195	42	16	,	,	PUNCT
ajst-20195	42	17	and	and	CCONJ
ajst-20195	42	18	prior	prior	ADJ
ajst-20195	42	19	field	field	NOUN
ajst-20195	42	20	sampling	sample	VERB
ajst-20195	42	21	experience	experience	NOUN
ajst-20195	42	22	were	be	AUX
ajst-20195	42	23	considered	consider	VERB
ajst-20195	42	24	.	.	PUNCT
ajst-20195	43	1	a	a	DET
ajst-20195	43	2	total	total	NOUN
ajst-20195	43	3	of	of	ADP
ajst-20195	43	4	86	86	NUM
ajst-20195	43	5	soil	soil	NOUN
ajst-20195	43	6	samples	sample	NOUN
ajst-20195	43	7	were	be	AUX
ajst-20195	43	8	collected	collect	VERB
ajst-20195	43	9	on	on	ADP
ajst-20195	43	10	28	28	NUM
ajst-20195	43	11	may	may	PROPN
ajst-20195	43	12	2023	2023	NUM
ajst-20195	43	13	and	and	CCONJ
ajst-20195	43	14	24	24	NUM
ajst-20195	43	15	july	july	PROPN
ajst-20195	43	16	2023	2023	NUM
ajst-20195	43	17	,	,	PUNCT
ajst-20195	43	18	including	include	VERB
ajst-20195	43	19	43	43	NUM
ajst-20195	43	20	soil	soil	NOUN
ajst-20195	43	21	samples	sample	NOUN
ajst-20195	43	22	in	in	ADP
ajst-20195	43	23	spring	spring	NOUN
ajst-20195	43	24	and	and	CCONJ
ajst-20195	43	25	43	43	NUM
ajst-20195	43	26	samples	sample	NOUN
ajst-20195	43	27	in	in	ADP
ajst-20195	43	28	summer	summer	NOUN
ajst-20195	43	29	.	.	PUNCT
ajst-20195	44	1	sampling	sample	VERB
ajst-20195	44	2	depths	depth	NOUN
ajst-20195	44	3	ranged	range	VERB
ajst-20195	44	4	from	from	ADP
ajst-20195	44	5	0	0	NUM
ajst-20195	44	6	-	-	SYM
ajst-20195	44	7	20	20	NUM
ajst-20195	44	8	cm	cm	NOUN
ajst-20195	44	9	,	,	PUNCT
ajst-20195	44	10	and	and	CCONJ
ajst-20195	44	11	latitude	latitude	NOUN
ajst-20195	44	12	and	and	CCONJ
ajst-20195	44	13	longitude	longitude	ADJ
ajst-20195	44	14	coordinates	coordinate	NOUN
ajst-20195	44	15	of	of	ADP
ajst-20195	44	16	sampling	sample	VERB
ajst-20195	44	17	sites	site	NOUN
ajst-20195	44	18	were	be	AUX
ajst-20195	44	19	recorded	record	VERB
ajst-20195	44	20	.	.	PUNCT
ajst-20195	45	1	the	the	DET
ajst-20195	45	2	collected	collect	VERB
ajst-20195	45	3	soil	soil	NOUN
ajst-20195	45	4	samples	sample	NOUN
ajst-20195	45	5	were	be	AUX
ajst-20195	45	6	placed	place	VERB
ajst-20195	45	7	sequentially	sequentially	ADV
ajst-20195	45	8	in	in	ADP
ajst-20195	45	9	aluminium	aluminium	NOUN
ajst-20195	45	10	boxes	box	NOUN
ajst-20195	45	11	according	accord	VERB
ajst-20195	45	12	to	to	ADP
ajst-20195	45	13	the	the	DET
ajst-20195	45	14	assigned	assign	VERB
ajst-20195	45	15	numbers	number	NOUN
ajst-20195	45	16	and	and	CCONJ
ajst-20195	45	17	subsequently	subsequently	ADV
ajst-20195	45	18	brought	bring	VERB
ajst-20195	45	19	back	back	ADV
ajst-20195	45	20	to	to	ADP
ajst-20195	45	21	the	the	DET
ajst-20195	45	22	laboratory	laboratory	NOUN
ajst-20195	45	23	for	for	ADP
ajst-20195	45	24	experimental	experimental	ADJ
ajst-20195	45	25	analysis	analysis	NOUN
ajst-20195	45	26	.	.	PUNCT
ajst-20195	46	1	the	the	DET
ajst-20195	46	2	moisture	moisture	NOUN
ajst-20195	46	3	content	content	NOUN
ajst-20195	46	4	of	of	ADP
ajst-20195	46	5	the	the	DET
ajst-20195	46	6	soil	soil	NOUN
ajst-20195	46	7	was	be	AUX
ajst-20195	46	8	determined	determine	VERB
ajst-20195	46	9	by	by	ADP
ajst-20195	46	10	oven	oven	NOUN
ajst-20195	46	11	drying	dry	VERB
ajst-20195	46	12	method	method	NOUN
ajst-20195	46	13	.	.	PUNCT
ajst-20195	47	1	the	the	DET
ajst-20195	47	2	procedure	procedure	NOUN
ajst-20195	47	3	for	for	ADP
ajst-20195	47	4	the	the	DET
ajst-20195	47	5	determination	determination	NOUN
ajst-20195	47	6	of	of	ADP
ajst-20195	47	7	soil	soil	NOUN
ajst-20195	47	8	electrical	electrical	ADJ
ajst-20195	47	9	conductivity	conductivity	NOUN
ajst-20195	47	10	(	(	PUNCT
ajst-20195	47	11	ec	ec	PROPN
ajst-20195	47	12	,	,	PUNCT
ajst-20195	47	13	us	us	PROPN
ajst-20195	47	14	/	/	SYM
ajst-20195	47	15	cm	cm	NOUN
ajst-20195	47	16	)	)	PUNCT
ajst-20195	47	17	consisted	consist	VERB
ajst-20195	47	18	of	of	ADP
ajst-20195	47	19	grinding	grind	VERB
ajst-20195	47	20	the	the	DET
ajst-20195	47	21	dried	dry	VERB
ajst-20195	47	22	soil	soil	NOUN
ajst-20195	47	23	samples	sample	NOUN
ajst-20195	47	24	and	and	CCONJ
ajst-20195	47	25	preparing	prepare	VERB
ajst-20195	47	26	them	they	PRON
ajst-20195	47	27	into	into	ADP
ajst-20195	47	28	a	a	DET
ajst-20195	47	29	1:5	1:5	NUM
ajst-20195	47	30	(	(	PUNCT
ajst-20195	47	31	soil	soil	NOUN
ajst-20195	47	32	to	to	PART
ajst-20195	47	33	water	water	NOUN
ajst-20195	47	34	ratio	ratio	NOUN
ajst-20195	47	35	)	)	PUNCT
ajst-20195	47	36	solution	solution	NOUN
ajst-20195	47	37	.	.	PUNCT
ajst-20195	48	1	subsequently	subsequently	ADV
ajst-20195	48	2	,	,	PUNCT
ajst-20195	48	3	conductivity	conductivity	NOUN
ajst-20195	48	4	values	value	NOUN
ajst-20195	48	5	were	be	AUX
ajst-20195	48	6	determined	determine	VERB
ajst-20195	48	7	using	use	VERB
ajst-20195	48	8	a	a	DET
ajst-20195	48	9	conductivity	conductivity	NOUN
ajst-20195	48	10	meter	meter	NOUN
ajst-20195	48	11	(	(	PUNCT
ajst-20195	48	12	model	model	NOUN
ajst-20195	48	13	mtd	mtd	PROPN
ajst-20195	48	14	15	15	NUM
ajst-20195	48	15	)	)	PUNCT
ajst-20195	48	16	after	after	ADP
ajst-20195	48	17	routine	routine	ADJ
ajst-20195	48	18	operations	operation	NOUN
ajst-20195	48	19	such	such	ADJ
ajst-20195	48	20	as	as	ADP
ajst-20195	48	21	stirring	stirring	NOUN
ajst-20195	48	22	,	,	PUNCT
ajst-20195	48	23	standing	standing	NOUN
ajst-20195	48	24	,	,	PUNCT
ajst-20195	48	25	settling	settling	NOUN
ajst-20195	48	26	and	and	CCONJ
ajst-20195	48	27	filtration	filtration	NOUN
ajst-20195	48	28	.	.	PUNCT
ajst-20195	49	1	the	the	DET
ajst-20195	49	2	formula	formula	NOUN
ajst-20195	49	3	for	for	ADP
ajst-20195	49	4	calculating	calculate	VERB
ajst-20195	49	5	soil	soil	NOUN
ajst-20195	49	6	salinity	salinity	NOUN
ajst-20195	49	7	(	(	PUNCT
ajst-20195	49	8	ssc	ssc	NOUN
ajst-20195	49	9	,	,	PUNCT
ajst-20195	49	10	%	%	INTJ
ajst-20195	49	11	)	)	PUNCT
ajst-20195	49	12	entailed	entail	VERB
ajst-20195	49	13	calibrating	calibrate	VERB
ajst-20195	49	14	the	the	DET
ajst-20195	49	15	relationship	relationship	NOUN
ajst-20195	49	16	between	between	ADP
ajst-20195	49	17	soil	soil	NOUN
ajst-20195	49	18	conductivity	conductivity	NOUN
ajst-20195	49	19	and	and	CCONJ
ajst-20195	49	20	soil	soil	NOUN
ajst-20195	49	21	salinity	salinity	NOUN
ajst-20195	49	22	by	by	ADP
ajst-20195	49	23	conducting	conduct	VERB
ajst-20195	49	24	a	a	DET
ajst-20195	49	25	large	large	ADJ
ajst-20195	49	26	number	number	NOUN
ajst-20195	49	27	of	of	ADP
ajst-20195	49	28	soil	soil	NOUN
ajst-20195	49	29	conductivity	conductivity	NOUN
ajst-20195	49	30	and	and	CCONJ
ajst-20195	49	31	drying	dry	VERB
ajst-20195	49	32	salinity	salinity	NOUN
ajst-20195	49	33	correspondence	correspondence	NOUN
ajst-20195	49	34	tests	test	NOUN
ajst-20195	49	35	as	as	ADP
ajst-20195	49	36	.	.	PUNCT
ajst-20195	50	1	𝑌	𝑌	PROPN
ajst-20195	50	2	0.0054951	0.0054951	NUM
ajst-20195	50	3	𝑋	𝑋	PROPN
ajst-20195	50	4	0.00131	0.00131	NUM
ajst-20195	50	5	𝑅	𝑅	PROPN
ajst-20195	50	6	0.998	0.998	NUM
ajst-20195	50	7	1	1	NUM
ajst-20195	50	8	where	where	SCONJ
ajst-20195	50	9	:	:	PUNCT
ajst-20195	50	10	y	y	PROPN
ajst-20195	50	11	is	be	AUX
ajst-20195	50	12	the	the	DET
ajst-20195	50	13	salt	salt	NOUN
ajst-20195	50	14	content	content	NOUN
ajst-20195	50	15	of	of	ADP
ajst-20195	50	16	the	the	DET
ajst-20195	50	17	soil	soil	NOUN
ajst-20195	50	18	,	,	PUNCT
ajst-20195	50	19	g	g	NOUN
ajst-20195	50	20	/	/	SYM
ajst-20195	50	21	kg	kg	PROPN
ajst-20195	50	22	;	;	PUNCT
ajst-20195	50	23	x	x	SYM
ajst-20195	50	24	：	：	PUNCT
ajst-20195	50	25	the	the	DET
ajst-20195	50	26	electrical	electrical	ADJ
ajst-20195	50	27	conductivity	conductivity	NOUN
ajst-20195	50	28	of	of	ADP
ajst-20195	50	29	the	the	DET
ajst-20195	50	30	soil	soil	NOUN
ajst-20195	50	31	,	,	PUNCT
ajst-20195	50	32	μs	μs	NOUN
ajst-20195	50	33	/	/	SYM
ajst-20195	50	34	cm	cm	NOUN
ajst-20195	50	35	.	.	PUNCT
ajst-20195	51	1	2.2.2	2.2.2	NUM
ajst-20195	51	2	.	.	PUNCT
ajst-20195	51	3	acquisition	acquisition	NOUN
ajst-20195	51	4	and	and	CCONJ
ajst-20195	51	5	processing	processing	NOUN
ajst-20195	51	6	of	of	ADP
ajst-20195	51	7	sentinel-2	sentinel-2	ADJ
ajst-20195	51	8	satellite	satellite	NOUN
ajst-20195	51	9	images	image	NOUN
ajst-20195	51	10	soil	soil	NOUN
ajst-20195	51	11	salinity	salinity	NOUN
ajst-20195	51	12	in	in	ADP
ajst-20195	51	13	the	the	DET
ajst-20195	51	14	study	study	NOUN
ajst-20195	51	15	area	area	NOUN
ajst-20195	51	16	was	be	AUX
ajst-20195	51	17	estimated	estimate	VERB
ajst-20195	51	18	using	use	VERB
ajst-20195	51	19	sentinel2	sentinel2	PROPN
ajst-20195	51	20	time	time	NOUN
ajst-20195	51	21	-	-	PUNCT
ajst-20195	51	22	series	series	NOUN
ajst-20195	51	23	satellite	satellite	NOUN
ajst-20195	51	24	data	data	PROPN
ajst-20195	51	25	,	,	PUNCT
ajst-20195	51	26	sentinel-2	sentinel-2	NUM
ajst-20195	51	27	satellite	satellite	NOUN
ajst-20195	51	28	images	image	NOUN
ajst-20195	51	29	were	be	AUX
ajst-20195	51	30	downloaded	download	VERB
ajst-20195	51	31	from	from	ADP
ajst-20195	51	32	the	the	DET
ajst-20195	51	33	esa	esa	PROPN
ajst-20195	51	34	copernicus	copernicus	PROPN
ajst-20195	51	35	data	data	PROPN
ajst-20195	51	36	centre	centre	NOUN
ajst-20195	51	37	(	(	PUNCT
ajst-20195	51	38	open	open	ADJ
ajst-20195	51	39	access	access	NOUN
ajst-20195	51	40	hub	hub	NOUN
ajst-20195	51	41	(	(	PUNCT
ajst-20195	51	42	copernicus.eu	copernicus.eu	NOUN
ajst-20195	51	43	)	)	PUNCT
ajst-20195	51	44	)	)	PUNCT
ajst-20195	51	45	,	,	PUNCT
ajst-20195	51	46	and	and	CCONJ
ajst-20195	51	47	the	the	DET
ajst-20195	51	48	sampling	sample	VERB
ajst-20195	51	49	time	time	NOUN
ajst-20195	51	50	of	of	ADP
ajst-20195	51	51	the	the	DET
ajst-20195	51	52	field	field	NOUN
ajst-20195	51	53	experiments	experiment	NOUN
ajst-20195	51	54	coincided	coincide	VERB
ajst-20195	51	55	with	with	ADP
ajst-20195	51	56	the	the	DET
ajst-20195	51	57	time	time	NOUN
ajst-20195	51	58	of	of	ADP
ajst-20195	51	59	sentinel-2	sentinel-2	ADJ
ajst-20195	51	60	satellite	satellite	NOUN
ajst-20195	51	61	image	image	NOUN
ajst-20195	51	62	collection	collection	NOUN
ajst-20195	51	63	.	.	PUNCT
ajst-20195	52	1	the	the	DET
ajst-20195	52	2	time	time	NOUN
ajst-20195	52	3	span	span	NOUN
ajst-20195	52	4	of	of	ADP
ajst-20195	52	5	the	the	DET
ajst-20195	52	6	study	study	NOUN
ajst-20195	52	7	was	be	AUX
ajst-20195	52	8	from	from	ADP
ajst-20195	52	9	may	may	PROPN
ajst-20195	52	10	2023	2023	NUM
ajst-20195	52	11	to	to	ADP
ajst-20195	52	12	july	july	PROPN
ajst-20195	52	13	2023	2023	NUM
ajst-20195	52	14	.	.	PUNCT
ajst-20195	53	1	using	use	VERB
ajst-20195	53	2	envi	envi	NOUN
ajst-20195	53	3	5.6.3	5.6.3	NUM
ajst-20195	53	4	software	software	NOUN
ajst-20195	53	5	,	,	PUNCT
ajst-20195	53	6	image	image	NOUN
ajst-20195	53	7	preprocessing	preprocessing	NOUN
ajst-20195	53	8	was	be	AUX
ajst-20195	53	9	performed	perform	VERB
ajst-20195	53	10	through	through	ADP
ajst-20195	53	11	radiometric	radiometric	ADJ
ajst-20195	53	12	calibration	calibration	NOUN
ajst-20195	53	13	,	,	PUNCT
ajst-20195	53	14	geometric	geometric	ADJ
ajst-20195	53	15	correction	correction	NOUN
ajst-20195	53	16	,	,	PUNCT
ajst-20195	53	17	and	and	CCONJ
ajst-20195	53	18	atmospheric	atmospheric	ADJ
ajst-20195	53	19	correction	correction	NOUN
ajst-20195	53	20	steps	step	NOUN
ajst-20195	53	21	,	,	PUNCT
ajst-20195	53	22	and	and	CCONJ
ajst-20195	53	23	reflectance	reflectance	NOUN
ajst-20195	53	24	data	datum	NOUN
ajst-20195	53	25	were	be	AUX
ajst-20195	53	26	acquired	acquire	VERB
ajst-20195	53	27	at	at	ADP
ajst-20195	53	28	the	the	DET
ajst-20195	53	29	sampling	sample	VERB
ajst-20195	53	30	sites	site	NOUN
ajst-20195	53	31	.	.	PUNCT
ajst-20195	54	1	2.3	2.3	NUM
ajst-20195	54	2	.	.	PUNCT
ajst-20195	55	1	construction	construction	NOUN
ajst-20195	55	2	of	of	ADP
ajst-20195	55	3	spectral	spectral	ADJ
ajst-20195	55	4	indices	index	NOUN
ajst-20195	55	5	based	base	VERB
ajst-20195	55	6	on	on	ADP
ajst-20195	55	7	the	the	DET
ajst-20195	55	8	soil	soil	NOUN
ajst-20195	55	9	salinity	salinity	NOUN
ajst-20195	55	10	index	index	NOUN
ajst-20195	55	11	listed	list	VERB
ajst-20195	55	12	in	in	ADP
ajst-20195	55	13	table	table	NOUN
ajst-20195	55	14	1	1	NUM
ajst-20195	55	15	as	as	ADP
ajst-20195	55	16	the	the	DET
ajst-20195	55	17	reference	reference	NOUN
ajst-20195	55	18	spectral	spectral	ADJ
ajst-20195	55	19	salinity	salinity	NOUN
ajst-20195	55	20	index	index	NOUN
ajst-20195	55	21	and	and	CCONJ
ajst-20195	55	22	incorporating	incorporate	VERB
ajst-20195	55	23	the	the	DET
ajst-20195	55	24	new	new	ADJ
ajst-20195	55	25	spectral	spectral	ADJ
ajst-20195	55	26	functions	function	NOUN
ajst-20195	55	27	of	of	ADP
ajst-20195	55	28	the	the	DET
ajst-20195	55	29	three	three	NUM
ajst-20195	55	30	additional	additional	ADJ
ajst-20195	55	31	red	red	ADJ
ajst-20195	55	32	-	-	PUNCT
ajst-20195	55	33	edge	edge	NOUN
ajst-20195	55	34	bands	band	NOUN
ajst-20195	55	35	(	(	PUNCT
ajst-20195	55	36	b5b7)[7	b5b7)[7	PROPN
ajst-20195	55	37	]	]	PUNCT
ajst-20195	55	38	,	,	PUNCT
ajst-20195	55	39	this	this	DET
ajst-20195	55	40	study	study	NOUN
ajst-20195	55	41	substitutes	substitute	VERB
ajst-20195	55	42	these	these	DET
ajst-20195	55	43	three	three	NUM
ajst-20195	55	44	bands	band	NOUN
ajst-20195	55	45	(	(	PUNCT
ajst-20195	55	46	b5	b5	PROPN
ajst-20195	55	47	-	-	PUNCT
ajst-20195	55	48	b7	b7	PROPN
ajst-20195	55	49	)	)	PUNCT
ajst-20195	55	50	for	for	ADP
ajst-20195	55	51	b4	b4	NOUN
ajst-20195	55	52	and	and	CCONJ
ajst-20195	55	53	calculates	calculate	VERB
ajst-20195	55	54	the	the	DET
ajst-20195	55	55	various	various	ADJ
ajst-20195	55	56	possible	possible	ADJ
ajst-20195	55	57	combinations	combination	NOUN
ajst-20195	55	58	of	of	ADP
ajst-20195	55	59	these	these	DET
ajst-20195	55	60	new	new	ADJ
ajst-20195	55	61	red	red	ADJ
ajst-20195	55	62	-	-	PUNCT
ajst-20195	55	63	edge	edge	NOUN
ajst-20195	55	64	bands	band	NOUN
ajst-20195	55	65	to	to	PART
ajst-20195	55	66	generate	generate	VERB
ajst-20195	55	67	the	the	DET
ajst-20195	55	68	potential	potential	ADJ
ajst-20195	55	69	soil	soil	NOUN
ajst-20195	55	70	salinity	salinity	NOUN
ajst-20195	55	71	indices	indice	VERB
ajst-20195	55	72	for	for	ADP
ajst-20195	55	73	the	the	DET
ajst-20195	55	74	estimation	estimation	NOUN
ajst-20195	55	75	of	of	ADP
ajst-20195	55	76	conductivity	conductivity	NOUN
ajst-20195	55	77	(	(	PUNCT
ajst-20195	55	78	table	table	NOUN
ajst-20195	55	79	2	2	NUM
ajst-20195	55	80	)	)	PUNCT
ajst-20195	55	81	.	.	PUNCT
ajst-20195	56	1	table	table	NOUN
ajst-20195	56	2	1	1	NUM
ajst-20195	56	3	.	.	X
ajst-20195	57	1	reference	reference	NOUN
ajst-20195	57	2	spectral	spectral	ADJ
ajst-20195	57	3	salinity	salinity	NOUN
ajst-20195	57	4	index	index	NOUN
ajst-20195	57	5	salinity	salinity	NOUN
ajst-20195	57	6	index	index	NOUN
ajst-20195	57	7	equation	equation	NOUN
ajst-20195	57	8	salinity	salinity	NOUN
ajst-20195	57	9	index	index	NOUN
ajst-20195	57	10	equation	equation	NOUN
ajst-20195	57	11	int1	int1	NOUN
ajst-20195	57	12	𝐵3	𝐵3	PROPN
ajst-20195	57	13	𝐵4	𝐵4	PROPN
ajst-20195	57	14	/	/	SYM
ajst-20195	57	15	2	2	NUM
ajst-20195	57	16	s1	s1	NOUN
ajst-20195	57	17	𝐵2	𝐵2	NOUN
ajst-20195	57	18	/	/	SYM
ajst-20195	57	19	𝐵4	𝐵4	PROPN
ajst-20195	57	20	int2	int2	PROPN
ajst-20195	57	21	𝐵3	𝐵3	PROPN
ajst-20195	57	22	𝐵4	𝐵4	PROPN
ajst-20195	57	23	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	57	24	s2	s2	PROPN
ajst-20195	57	25	𝐵3	𝐵3	PROPN
ajst-20195	57	26	𝐵4	𝐵4	PROPN
ajst-20195	57	27	/	/	SYM
ajst-20195	57	28	𝐵3	𝐵3	PROPN
ajst-20195	57	29	𝐵4	𝐵4	PROPN
ajst-20195	57	30	si	si	PROPN
ajst-20195	57	31	√𝐵3	√𝐵3	ADJ
ajst-20195	57	32	𝐵4	𝐵4	PROPN
ajst-20195	57	33	s3	s3	PROPN
ajst-20195	57	34	𝐵3	𝐵3	PROPN
ajst-20195	57	35	𝐵4	𝐵4	PROPN
ajst-20195	57	36	/	/	SYM
ajst-20195	57	37	𝐵2	𝐵2	NOUN
ajst-20195	57	38	si1	si1	VERB
ajst-20195	57	39	√𝐵3	√𝐵3	ADJ
ajst-20195	57	40	𝐵4	𝐵4	NOUN
ajst-20195	57	41	si	si	PROPN
ajst-20195	57	42	-	-	PROPN
ajst-20195	57	43	t	t	NOUN
ajst-20195	57	44	𝐵4/𝐵8𝑎	𝐵4/𝐵8𝑎	PROPN
ajst-20195	57	45	100	100	NUM
ajst-20195	57	46	si2	si2	NOUN
ajst-20195	57	47	𝐵3	𝐵3	PROPN
ajst-20195	57	48	𝐵4	𝐵4	PROPN
ajst-20195	57	49	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	57	50	ndsi	ndsi	PROPN
ajst-20195	57	51	𝐵3	𝐵3	PROPN
ajst-20195	57	52	𝐵4	𝐵4	PROPN
ajst-20195	57	53	si3	si3	PROPN
ajst-20195	57	54	𝐵3	𝐵3	PROPN
ajst-20195	57	55	𝐵4	𝐵4	PROPN
ajst-20195	57	56	table	table	NOUN
ajst-20195	57	57	2	2	NUM
ajst-20195	57	58	.	.	PUNCT
ajst-20195	57	59	newly	newly	ADV
ajst-20195	57	60	proposed	propose	VERB
ajst-20195	57	61	red	red	ADJ
ajst-20195	57	62	-	-	PUNCT
ajst-20195	57	63	edge	edge	NOUN
ajst-20195	57	64	spectral	spectral	ADJ
ajst-20195	57	65	indices	index	NOUN
ajst-20195	57	66	salinity	salinity	NOUN
ajst-20195	57	67	index	index	NOUN
ajst-20195	57	68	equation	equation	NOUN
ajst-20195	57	69	salinity	salinity	NOUN
ajst-20195	57	70	index	index	NOUN
ajst-20195	57	71	equation	equation	NOUN
ajst-20195	57	72	int1	int1	NOUN
ajst-20195	57	73	re1	re1	PROPN
ajst-20195	57	74	𝐵3	𝐵3	PROPN
ajst-20195	57	75	𝐵5	𝐵5	PROPN
ajst-20195	57	76	/	/	SYM
ajst-20195	57	77	2	2	NUM
ajst-20195	57	78	s3	s3	PROPN
ajst-20195	57	79	re3	re3	PROPN
ajst-20195	57	80	𝐵3	𝐵3	PROPN
ajst-20195	57	81	𝐵7	𝐵7	PROPN
ajst-20195	57	82	/	/	SYM
ajst-20195	57	83	𝐵2	𝐵2	NOUN
ajst-20195	57	84	int1	int1	PROPN
ajst-20195	57	85	re2	re2	PROPN
ajst-20195	57	86	𝐵3	𝐵3	PROPN
ajst-20195	57	87	𝐵6	𝐵6	PROPN
ajst-20195	57	88	/	/	SYM
ajst-20195	57	89	2	2	NUM
ajst-20195	57	90	si	si	NOUN
ajst-20195	57	91	-	-	PUNCT
ajst-20195	57	92	t	t	NOUN
ajst-20195	57	93	re1	re1	PROPN
ajst-20195	57	94	𝐵5	𝐵5	PROPN
ajst-20195	57	95	/	/	SYM
ajst-20195	57	96	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	57	97	100	100	NUM
ajst-20195	57	98	int1	int1	NOUN
ajst-20195	57	99	re3	re3	PROPN
ajst-20195	57	100	𝐵3	𝐵3	PROPN
ajst-20195	57	101	𝐵7	𝐵7	PROPN
ajst-20195	57	102	/	/	SYM
ajst-20195	57	103	2	2	NUM
ajst-20195	57	104	si	si	NOUN
ajst-20195	57	105	-	-	PUNCT
ajst-20195	57	106	t	t	PROPN
ajst-20195	57	107	re2	re2	PROPN
ajst-20195	57	108	𝐵6	𝐵6	PROPN
ajst-20195	57	109	/	/	SYM
ajst-20195	57	110	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	57	111	100	100	NUM
ajst-20195	58	1	int2	int2	PROPN
ajst-20195	58	2	re1	re1	PROPN
ajst-20195	58	3	𝐵3	𝐵3	PROPN
ajst-20195	58	4	𝐵5	𝐵5	PROPN
ajst-20195	58	5	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	58	6	si	si	PROPN
ajst-20195	58	7	-	-	PUNCT
ajst-20195	58	8	t	t	PROPN
ajst-20195	58	9	re3	re3	PROPN
ajst-20195	58	10	𝐵7	𝐵7	PROPN
ajst-20195	58	11	/	/	SYM
ajst-20195	58	12	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	58	13	100	100	NUM
ajst-20195	58	14	int2	int2	PROPN
ajst-20195	58	15	re2	re2	PROPN
ajst-20195	58	16	𝐵3	𝐵3	PROPN
ajst-20195	58	17	𝐵6	𝐵6	PROPN
ajst-20195	59	1	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	59	2	si	si	PROPN
ajst-20195	59	3	re1	re1	PROPN
ajst-20195	59	4	√𝐵2	√𝐵2	PROPN
ajst-20195	59	5	𝐵5	𝐵5	PROPN
ajst-20195	59	6	int2	int2	PROPN
ajst-20195	59	7	re3	re3	PROPN
ajst-20195	59	8	𝐵3	𝐵3	PROPN
ajst-20195	59	9	𝐵7	𝐵7	PROPN
ajst-20195	59	10	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	59	11	si	si	PROPN
ajst-20195	60	1	re2	re2	PROPN
ajst-20195	60	2	√𝐵2	√𝐵2	PROPN
ajst-20195	60	3	𝐵6	𝐵6	PROPN
ajst-20195	60	4	ndsi	ndsi	PROPN
ajst-20195	60	5	re1	re1	PROPN
ajst-20195	60	6	𝐵5	𝐵5	INTJ
ajst-20195	60	7	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	60	8	/	/	SYM
ajst-20195	60	9	𝐵5	𝐵5	NOUN
ajst-20195	60	10	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	60	11	si	si	PROPN
ajst-20195	60	12	re3	re3	PROPN
ajst-20195	60	13	√𝐵2	√𝐵2	PROPN
ajst-20195	60	14	𝐵7	𝐵7	PROPN
ajst-20195	60	15	ndsi	ndsi	PROPN
ajst-20195	60	16	re2	re2	PROPN
ajst-20195	60	17	𝐵6	𝐵6	PROPN
ajst-20195	60	18	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	60	19	/	/	SYM
ajst-20195	60	20	𝐵6	𝐵6	PROPN
ajst-20195	61	1	𝐵9𝑎	𝐵9𝑎	PROPN
ajst-20195	61	2	si1	si1	PRON
ajst-20195	61	3	re1	re1	PROPN
ajst-20195	61	4	√𝐵3	√𝐵3	ADJ
ajst-20195	61	5	𝐵5	𝐵5	PROPN
ajst-20195	61	6	ndsi	ndsi	PROPN
ajst-20195	61	7	re3	re3	PROPN
ajst-20195	61	8	𝐵7	𝐵7	PROPN
ajst-20195	61	9	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	61	10	/	/	PUNCT
ajst-20195	61	11	𝐵7	𝐵7	PROPN
ajst-20195	61	12	𝐵10𝑎	𝐵10𝑎	ADV
ajst-20195	61	13	si1	si1	PROPN
ajst-20195	61	14	re2	re2	PROPN
ajst-20195	61	15	√𝐵3	√𝐵3	PROPN
ajst-20195	61	16	𝐵6	𝐵6	PROPN
ajst-20195	61	17	s1	s1	PROPN
ajst-20195	61	18	re1	re1	PROPN
ajst-20195	61	19	𝐵2	𝐵2	PROPN
ajst-20195	61	20	/	/	SYM
ajst-20195	61	21	𝐵5	𝐵5	NOUN
ajst-20195	61	22	si1	si1	PROPN
ajst-20195	61	23	re3	re3	PROPN
ajst-20195	61	24	√𝐵3	√𝐵3	ADJ
ajst-20195	61	25	𝐵7	𝐵7	PROPN
ajst-20195	61	26	s1	s1	PROPN
ajst-20195	61	27	re2	re2	PROPN
ajst-20195	61	28	𝐵2	𝐵2	PROPN
ajst-20195	61	29	/	/	SYM
ajst-20195	61	30	𝐵6	𝐵6	PROPN
ajst-20195	61	31	si2	si2	NOUN
ajst-20195	61	32	re1	re1	PROPN
ajst-20195	61	33	𝐵3	𝐵3	PROPN
ajst-20195	61	34	𝐵5	𝐵5	PROPN
ajst-20195	61	35	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	61	36	s1	s1	PROPN
ajst-20195	61	37	re3	re3	PROPN
ajst-20195	61	38	𝐵2	𝐵2	PROPN
ajst-20195	61	39	/	/	PUNCT
ajst-20195	61	40	𝐵7	𝐵7	PROPN
ajst-20195	61	41	si2	si2	NOUN
ajst-20195	61	42	re2	re2	PROPN
ajst-20195	61	43	𝐵3	𝐵3	PROPN
ajst-20195	61	44	𝐵6	𝐵6	PROPN
ajst-20195	62	1	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	62	2	s2	s2	PROPN
ajst-20195	62	3	re1	re1	PROPN
ajst-20195	62	4	𝐵3	𝐵3	PROPN
ajst-20195	62	5	𝐵5	𝐵5	PROPN
ajst-20195	62	6	/	/	SYM
ajst-20195	63	1	𝐵3	𝐵3	PROPN
ajst-20195	63	2	𝐵5	𝐵5	PROPN
ajst-20195	63	3	si2	si2	PROPN
ajst-20195	63	4	re3	re3	PROPN
ajst-20195	63	5	𝐵3	𝐵3	PROPN
ajst-20195	63	6	𝐵7	𝐵7	PROPN
ajst-20195	63	7	𝐵8𝑎	𝐵8𝑎	PROPN
ajst-20195	63	8	s2	s2	PROPN
ajst-20195	63	9	re2	re2	PROPN
ajst-20195	63	10	𝐵3	𝐵3	PROPN
ajst-20195	63	11	𝐵6	𝐵6	PROPN
ajst-20195	63	12	/	/	PUNCT
ajst-20195	64	1	𝐵3	𝐵3	PROPN
ajst-20195	64	2	𝐵6	𝐵6	PROPN
ajst-20195	64	3	si3	si3	PROPN
ajst-20195	64	4	re1	re1	PROPN
ajst-20195	64	5	𝐵5	𝐵5	PROPN
ajst-20195	64	6	𝐵3	𝐵3	PROPN
ajst-20195	64	7	s2	s2	PROPN
ajst-20195	64	8	re3	re3	PROPN
ajst-20195	64	9	𝐵3	𝐵3	PROPN
ajst-20195	64	10	𝐵7	𝐵7	PROPN
ajst-20195	64	11	/	/	SYM
ajst-20195	64	12	𝐵3	𝐵3	PROPN
ajst-20195	64	13	𝐵7	𝐵7	PROPN
ajst-20195	64	14	si3	si3	PROPN
ajst-20195	64	15	re2	re2	PROPN
ajst-20195	64	16	𝐵6	𝐵6	PROPN
ajst-20195	64	17	𝐵3	𝐵3	PROPN
ajst-20195	64	18	s3	s3	PROPN
ajst-20195	64	19	re1	re1	PROPN
ajst-20195	64	20	𝐵3	𝐵3	PROPN
ajst-20195	64	21	𝐵5	𝐵5	PROPN
ajst-20195	64	22	/	/	SYM
ajst-20195	65	1	𝐵2	𝐵2	PROPN
ajst-20195	65	2	si3	si3	PROPN
ajst-20195	65	3	re3	re3	PROPN
ajst-20195	65	4	𝐵7	𝐵7	PROPN
ajst-20195	65	5	𝐵3	𝐵3	PROPN
ajst-20195	65	6	s3	s3	PROPN
ajst-20195	65	7	re2	re2	PROPN
ajst-20195	65	8	𝐵3	𝐵3	PROPN
ajst-20195	65	9	𝐵6	𝐵6	PROPN
ajst-20195	65	10	/	/	PUNCT
ajst-20195	65	11	𝐵2	𝐵2	PROPN
ajst-20195	65	12	102	102	NUM
ajst-20195	65	13	2.4	2.4	NUM
ajst-20195	65	14	.	.	PUNCT
ajst-20195	66	1	screening	screen	VERB
ajst-20195	66	2	of	of	ADP
ajst-20195	66	3	spectral	spectral	ADJ
ajst-20195	66	4	indices	index	NOUN
ajst-20195	66	5	considering	consider	VERB
ajst-20195	66	6	that	that	SCONJ
ajst-20195	66	7	too	too	ADV
ajst-20195	66	8	many	many	ADJ
ajst-20195	66	9	spectral	spectral	ADJ
ajst-20195	66	10	indices	index	NOUN
ajst-20195	66	11	may	may	AUX
ajst-20195	66	12	lead	lead	VERB
ajst-20195	66	13	to	to	PART
ajst-20195	66	14	redundant	redundant	VERB
ajst-20195	66	15	information	information	NOUN
ajst-20195	66	16	,	,	PUNCT
ajst-20195	66	17	the	the	DET
ajst-20195	66	18	study	study	NOUN
ajst-20195	66	19	chose	choose	VERB
ajst-20195	66	20	the	the	DET
ajst-20195	66	21	partial	partial	ADJ
ajst-20195	66	22	least	least	ADJ
ajst-20195	66	23	squares	square	NOUN
ajst-20195	66	24	-	-	PUNCT
ajst-20195	66	25	based	base	VERB
ajst-20195	66	26	variable	variable	ADJ
ajst-20195	66	27	projection	projection	NOUN
ajst-20195	66	28	importance	importance	NOUN
ajst-20195	66	29	(	(	PUNCT
ajst-20195	66	30	pls	pls	INTJ
ajst-20195	66	31	-	-	PUNCT
ajst-20195	66	32	vip	vip	NOUN
ajst-20195	66	33	)	)	PUNCT
ajst-20195	66	34	criterion	criterion	NOUN
ajst-20195	66	35	for	for	ADP
ajst-20195	66	36	independent	independent	ADJ
ajst-20195	66	37	variable	variable	NOUN
ajst-20195	66	38	screening[8	screening[8	PROPN
ajst-20195	66	39	]	]	PUNCT
ajst-20195	66	40	.	.	PUNCT
ajst-20195	67	1	with	with	ADP
ajst-20195	67	2	this	this	DET
ajst-20195	67	3	criterion	criterion	NOUN
ajst-20195	67	4	,	,	PUNCT
ajst-20195	67	5	they	they	PRON
ajst-20195	67	6	constructed	construct	VERB
ajst-20195	67	7	the	the	DET
ajst-20195	67	8	spectral	spectral	ADJ
ajst-20195	67	9	indices	index	NOUN
ajst-20195	67	10	as	as	ADP
ajst-20195	67	11	a	a	DET
ajst-20195	67	12	combination	combination	NOUN
ajst-20195	67	13	of	of	ADP
ajst-20195	67	14	variables	variable	NOUN
ajst-20195	67	15	in	in	ADP
ajst-20195	67	16	spring	spring	NOUN
ajst-20195	67	17	and	and	CCONJ
ajst-20195	67	18	summer	summer	NOUN
ajst-20195	67	19	seasons	season	NOUN
ajst-20195	67	20	as	as	ADP
ajst-20195	67	21	input	input	NOUN
ajst-20195	67	22	independent	independent	ADJ
ajst-20195	67	23	variables	variable	NOUN
ajst-20195	67	24	for	for	ADP
ajst-20195	67	25	the	the	DET
ajst-20195	67	26	soil	soil	NOUN
ajst-20195	67	27	salinity	salinity	NOUN
ajst-20195	67	28	inversion	inversion	NOUN
ajst-20195	67	29	model	model	NOUN
ajst-20195	67	30	.	.	PUNCT
ajst-20195	68	1	in	in	ADP
ajst-20195	68	2	the	the	DET
ajst-20195	68	3	spring	spring	NOUN
ajst-20195	68	4	and	and	CCONJ
ajst-20195	68	5	summer	summer	NOUN
ajst-20195	68	6	seasons	season	NOUN
ajst-20195	68	7	,	,	PUNCT
ajst-20195	68	8	the	the	DET
ajst-20195	68	9	study	study	NOUN
ajst-20195	68	10	considered	consider	VERB
ajst-20195	68	11	the	the	DET
ajst-20195	68	12	variables	variable	NOUN
ajst-20195	68	13	greater	great	ADJ
ajst-20195	68	14	than	than	ADP
ajst-20195	68	15	1	1	NUM
ajst-20195	68	16	as	as	ADV
ajst-20195	68	17	significant	significant	ADJ
ajst-20195	68	18	to	to	ADP
ajst-20195	68	19	the	the	DET
ajst-20195	68	20	measured	measure	VERB
ajst-20195	68	21	soil	soil	NOUN
ajst-20195	68	22	salinity	salinity	NOUN
ajst-20195	68	23	based	base	VERB
ajst-20195	68	24	on	on	ADP
ajst-20195	68	25	the	the	DET
ajst-20195	68	26	pls	pls	ADJ
ajst-20195	68	27	-	-	PUNCT
ajst-20195	68	28	vip	vip	NOUN
ajst-20195	68	29	calculation	calculation	NOUN
ajst-20195	68	30	results	result	NOUN
ajst-20195	68	31	and	and	CCONJ
ajst-20195	68	32	used	use	VERB
ajst-20195	68	33	them	they	PRON
ajst-20195	68	34	as	as	ADP
ajst-20195	68	35	the	the	DET
ajst-20195	68	36	independent	independent	ADJ
ajst-20195	68	37	variables	variable	NOUN
ajst-20195	68	38	of	of	ADP
ajst-20195	68	39	the	the	DET
ajst-20195	68	40	satellite	satellite	NOUN
ajst-20195	68	41	remote	remote	ADJ
ajst-20195	68	42	sensing	sense	VERB
ajst-20195	68	43	inversion	inversion	NOUN
ajst-20195	68	44	model	model	NOUN
ajst-20195	68	45	.	.	PUNCT
ajst-20195	69	1	the	the	DET
ajst-20195	69	2	principle	principle	NOUN
ajst-20195	69	3	of	of	ADP
ajst-20195	69	4	pls	pls	NOUN
ajst-20195	69	5	-	-	PUNCT
ajst-20195	69	6	vip	vip	NOUN
ajst-20195	69	7	criterion	criterion	NOUN
ajst-20195	69	8	is	be	AUX
ajst-20195	69	9	given	give	VERB
ajst-20195	69	10	in	in	ADP
ajst-20195	69	11	the	the	DET
ajst-20195	69	12	following	follow	VERB
ajst-20195	69	13	equation	equation	NOUN
ajst-20195	69	14	.	.	PUNCT
ajst-20195	70	1	𝑉𝐼𝑃	𝑉𝐼𝑃	PROPN
ajst-20195	70	2	𝑝	𝑝	ADP
ajst-20195	70	3	∑	∑	DET
ajst-20195	70	4	  	  	SPACE
ajst-20195	70	5	𝑅	𝑅	PROPN
ajst-20195	70	6	𝑌	𝑌	PROPN
ajst-20195	70	7	,	,	PUNCT
ajst-20195	70	8	𝑡	𝑡	VERB
ajst-20195	70	9	𝑤	𝑤	ADP
ajst-20195	70	10	∑	∑	DET
ajst-20195	70	11	  	  	SPACE
ajst-20195	70	12	𝑅	𝑅	PROPN
ajst-20195	70	13	𝑌	𝑌	PROPN
ajst-20195	70	14	,	,	PUNCT
ajst-20195	70	15	𝑡	𝑡	NOUN
ajst-20195	70	16	2	2	NUM
ajst-20195	70	17	where	where	SCONJ
ajst-20195	70	18	p	p	NOUN
ajst-20195	70	19	is	be	AUX
ajst-20195	70	20	the	the	DET
ajst-20195	70	21	number	number	NOUN
ajst-20195	70	22	of	of	ADP
ajst-20195	70	23	independent	independent	ADJ
ajst-20195	70	24	variables	variable	NOUN
ajst-20195	70	25	;	;	PUNCT
ajst-20195	70	26	m	m	VERB
ajst-20195	70	27	is	be	AUX
ajst-20195	70	28	the	the	DET
ajst-20195	70	29	number	number	NOUN
ajst-20195	70	30	of	of	ADP
ajst-20195	70	31	components	component	NOUN
ajst-20195	70	32	extracted	extract	VERB
ajst-20195	70	33	from	from	ADP
ajst-20195	70	34	the	the	DET
ajst-20195	70	35	original	original	ADJ
ajst-20195	70	36	variable	variable	ADJ
ajst-20195	70	37	species	specie	NOUN
ajst-20195	70	38	by	by	ADP
ajst-20195	70	39	partial	partial	ADJ
ajst-20195	70	40	least	least	ADJ
ajst-20195	70	41	squares	square	NOUN
ajst-20195	70	42	(	(	PUNCT
ajst-20195	70	43	pls	pls	INTJ
ajst-20195	70	44	)	)	PUNCT
ajst-20195	70	45	;	;	PUNCT
ajst-20195	70	46	𝑡	𝑡	PROPN
ajst-20195	70	47	is	be	AUX
ajst-20195	70	48	the	the	DET
ajst-20195	70	49	hth	hth	PROPN
ajst-20195	70	50	component	component	NOUN
ajst-20195	70	51	;	;	PUNCT
ajst-20195	70	52	𝑅	𝑅	PROPN
ajst-20195	70	53	𝑌	𝑌	PROPN
ajst-20195	70	54	,	,	PUNCT
ajst-20195	70	55	𝑡	𝑡	PROPN
ajst-20195	70	56	is	be	AUX
ajst-20195	70	57	the	the	DET
ajst-20195	70	58	explanatory	explanatory	ADJ
ajst-20195	70	59	power	power	NOUN
ajst-20195	70	60	of	of	ADP
ajst-20195	70	61	component	component	NOUN
ajst-20195	70	62	𝑡	𝑡	PROPN
ajst-20195	70	63	on	on	ADP
ajst-20195	70	64	the	the	DET
ajst-20195	70	65	dependent	dependent	ADJ
ajst-20195	70	66	variable	variable	ADJ
ajst-20195	70	67	y	y	PROPN
ajst-20195	70	68	,	,	PUNCT
ajst-20195	70	69	which	which	PRON
ajst-20195	70	70	is	be	AUX
ajst-20195	70	71	usually	usually	ADV
ajst-20195	70	72	the	the	DET
ajst-20195	70	73	square	square	NOUN
ajst-20195	70	74	of	of	ADP
ajst-20195	70	75	the	the	DET
ajst-20195	70	76	correlation	correlation	NOUN
ajst-20195	70	77	coefficient	coefficient	NOUN
ajst-20195	70	78	of	of	ADP
ajst-20195	70	79	the	the	DET
ajst-20195	70	80	two	two	NUM
ajst-20195	70	81	;	;	PUNCT
ajst-20195	70	82	𝑊	𝑊	PROPN
ajst-20195	70	83	is	be	AUX
ajst-20195	70	84	the	the	DET
ajst-20195	70	85	jth	jth	PROPN
ajst-20195	70	86	component	component	NOUN
ajst-20195	70	87	of	of	ADP
ajst-20195	70	88	the	the	DET
ajst-20195	70	89	axis	axis	NOUN
ajst-20195	70	90	𝑤	𝑤	PROPN
ajst-20195	70	91	and	and	CCONJ
ajst-20195	70	92	𝑊	𝑊	PROPN
ajst-20195	70	93	is	be	AUX
ajst-20195	70	94	the	the	DET
ajst-20195	70	95	eigenvector	eigenvector	NOUN
ajst-20195	70	96	of	of	ADP
ajst-20195	70	97	the	the	DET
ajst-20195	70	98	matrix	matrix	NOUN
ajst-20195	70	99	𝑋	𝑋	NOUN
ajst-20195	70	100	,	,	PUNCT
ajst-20195	70	101	𝑌	𝑌	PROPN
ajst-20195	70	102	𝑌	𝑌	PROPN
ajst-20195	70	103	,	,	PUNCT
ajst-20195	70	104	𝑋	𝑋	NOUN
ajst-20195	70	105	eigenvectors	eigenvector	NOUN
ajst-20195	70	106	.	.	PUNCT
ajst-20195	71	1	when	when	SCONJ
ajst-20195	71	2	the	the	DET
ajst-20195	71	3	pls	pls	ADJ
ajst-20195	71	4	-	-	PUNCT
ajst-20195	71	5	vip	vip	NOUN
ajst-20195	71	6	value	value	NOUN
ajst-20195	71	7	of	of	ADP
ajst-20195	71	8	an	an	DET
ajst-20195	71	9	independent	independent	ADJ
ajst-20195	71	10	variable	variable	NOUN
ajst-20195	71	11	is	be	AUX
ajst-20195	71	12	greater	great	ADJ
ajst-20195	71	13	than	than	ADP
ajst-20195	71	14	1	1	NUM
ajst-20195	71	15	,	,	PUNCT
ajst-20195	71	16	it	it	PRON
ajst-20195	71	17	means	mean	VERB
ajst-20195	71	18	that	that	SCONJ
ajst-20195	71	19	the	the	DET
ajst-20195	71	20	independent	independent	ADJ
ajst-20195	71	21	variable	variable	NOUN
ajst-20195	71	22	has	have	VERB
ajst-20195	71	23	an	an	DET
ajst-20195	71	24	important	important	ADJ
ajst-20195	71	25	role	role	NOUN
ajst-20195	71	26	in	in	ADP
ajst-20195	71	27	explaining	explain	VERB
ajst-20195	71	28	the	the	DET
ajst-20195	71	29	dependent	dependent	ADJ
ajst-20195	71	30	variable	variable	ADJ
ajst-20195	71	31	y	y	NOUN
ajst-20195	71	32	,	,	PUNCT
ajst-20195	71	33	while	while	SCONJ
ajst-20195	71	34	when	when	SCONJ
ajst-20195	71	35	the	the	DET
ajst-20195	71	36	pls	pls	ADJ
ajst-20195	71	37	-	-	PUNCT
ajst-20195	71	38	vip	vip	NOUN
ajst-20195	71	39	value	value	NOUN
ajst-20195	71	40	is	be	AUX
ajst-20195	71	41	less	less	ADJ
ajst-20195	71	42	than	than	ADP
ajst-20195	71	43	1	1	NUM
ajst-20195	71	44	,	,	PUNCT
ajst-20195	71	45	it	it	PRON
ajst-20195	71	46	means	mean	VERB
ajst-20195	71	47	that	that	SCONJ
ajst-20195	71	48	the	the	DET
ajst-20195	71	49	independent	independent	ADJ
ajst-20195	71	50	variable	variable	NOUN
ajst-20195	71	51	has	have	VERB
ajst-20195	71	52	a	a	DET
ajst-20195	71	53	less	less	ADV
ajst-20195	71	54	important	important	ADJ
ajst-20195	71	55	role[9	role[9	NOUN
ajst-20195	71	56	]	]	PUNCT
ajst-20195	71	57	.	.	PUNCT
ajst-20195	72	1	2.5	2.5	NUM
ajst-20195	72	2	.	.	PUNCT
ajst-20195	73	1	construction	construction	NOUN
ajst-20195	73	2	of	of	ADP
ajst-20195	73	3	soil	soil	NOUN
ajst-20195	73	4	salinity	salinity	NOUN
ajst-20195	73	5	inversion	inversion	NOUN
ajst-20195	73	6	model	model	NOUN
ajst-20195	73	7	2.5.1	2.5.1	NUM
ajst-20195	73	8	.	.	PUNCT
ajst-20195	74	1	random	random	ADJ
ajst-20195	74	2	forest	forest	NOUN
ajst-20195	74	3	method	method	NOUN
ajst-20195	74	4	(	(	PUNCT
ajst-20195	74	5	rf	rf	NOUN
ajst-20195	74	6	)	)	PUNCT
ajst-20195	74	7	random	random	ADJ
ajst-20195	74	8	forest	forest	NOUN
ajst-20195	74	9	model	model	NOUN
ajst-20195	74	10	(	(	PUNCT
ajst-20195	74	11	rf	rf	NOUN
ajst-20195	74	12	)	)	PUNCT
ajst-20195	74	13	is	be	AUX
ajst-20195	74	14	an	an	DET
ajst-20195	74	15	integrated	integrate	VERB
ajst-20195	74	16	method	method	NOUN
ajst-20195	74	17	based	base	VERB
ajst-20195	74	18	on	on	ADP
ajst-20195	74	19	decision	decision	NOUN
ajst-20195	74	20	trees	tree	NOUN
ajst-20195	74	21	with	with	ADP
ajst-20195	74	22	excellent	excellent	ADJ
ajst-20195	74	23	generalisation	generalisation	NOUN
ajst-20195	74	24	performance	performance	NOUN
ajst-20195	74	25	,	,	PUNCT
ajst-20195	74	26	which	which	PRON
ajst-20195	74	27	can	can	AUX
ajst-20195	74	28	be	be	AUX
ajst-20195	74	29	widely	widely	ADV
ajst-20195	74	30	applied	apply	VERB
ajst-20195	74	31	to	to	ADP
ajst-20195	74	32	regression	regression	NOUN
ajst-20195	74	33	and	and	CCONJ
ajst-20195	74	34	classification	classification	NOUN
ajst-20195	74	35	problems[10	problems[10	NOUN
ajst-20195	74	36	]	]	PUNCT
ajst-20195	74	37	.	.	PUNCT
ajst-20195	75	1	the	the	DET
ajst-20195	75	2	prediction	prediction	NOUN
ajst-20195	75	3	error	error	NOUN
ajst-20195	75	4	is	be	AUX
ajst-20195	75	5	estimated	estimate	VERB
ajst-20195	75	6	by	by	ADP
ajst-20195	75	7	generating	generate	VERB
ajst-20195	75	8	classification	classification	NOUN
ajst-20195	75	9	and	and	CCONJ
ajst-20195	75	10	regression	regression	NOUN
ajst-20195	75	11	trees	tree	NOUN
ajst-20195	75	12	using	use	VERB
ajst-20195	75	13	the	the	DET
ajst-20195	75	14	bagging	bagging	NOUN
ajst-20195	75	15	algorithm	algorithm	NOUN
ajst-20195	75	16	,	,	PUNCT
ajst-20195	75	17	using	use	VERB
ajst-20195	75	18	the	the	DET
ajst-20195	75	19	randomly	randomly	ADV
ajst-20195	75	20	selected	select	VERB
ajst-20195	75	21	training	training	NOUN
ajst-20195	75	22	set	set	VERB
ajst-20195	75	23	as	as	ADP
ajst-20195	75	24	an	an	DET
ajst-20195	75	25	independent	independent	ADJ
ajst-20195	75	26	dataset	dataset	NOUN
ajst-20195	75	27	and	and	CCONJ
ajst-20195	75	28	the	the	DET
ajst-20195	75	29	unselected	unselected	ADJ
ajst-20195	75	30	data	datum	NOUN
ajst-20195	75	31	as	as	ADP
ajst-20195	75	32	out	out	ADP
ajst-20195	75	33	-	-	PUNCT
ajst-20195	75	34	of	of	ADP
ajst-20195	75	35	-	-	PUNCT
ajst-20195	75	36	bag	bag	NOUN
ajst-20195	75	37	data	datum	NOUN
ajst-20195	75	38	.	.	PUNCT
ajst-20195	76	1	at	at	ADP
ajst-20195	76	2	the	the	DET
ajst-20195	76	3	nodes	node	NOUN
ajst-20195	76	4	of	of	ADP
ajst-20195	76	5	each	each	DET
ajst-20195	76	6	decision	decision	NOUN
ajst-20195	76	7	tree	tree	NOUN
ajst-20195	76	8	,	,	PUNCT
ajst-20195	76	9	the	the	DET
ajst-20195	76	10	covariates	covariate	NOUN
ajst-20195	76	11	are	be	AUX
ajst-20195	76	12	also	also	ADV
ajst-20195	76	13	randomly	randomly	ADV
ajst-20195	76	14	divided	divide	VERB
ajst-20195	76	15	into	into	ADP
ajst-20195	76	16	multiple	multiple	ADJ
ajst-20195	76	17	groups	group	NOUN
ajst-20195	76	18	to	to	PART
ajst-20195	76	19	minimise	minimise	VERB
ajst-20195	76	20	the	the	DET
ajst-20195	76	21	variance	variance	NOUN
ajst-20195	76	22	of	of	ADP
ajst-20195	76	23	the	the	DET
ajst-20195	76	24	split	split	ADJ
ajst-20195	76	25	groups	group	NOUN
ajst-20195	76	26	,	,	PUNCT
ajst-20195	76	27	thus	thus	ADV
ajst-20195	76	28	completing	complete	VERB
ajst-20195	76	29	the	the	DET
ajst-20195	76	30	tree	tree	NOUN
ajst-20195	76	31	splitting	splitting	NOUN
ajst-20195	76	32	process	process	NOUN
ajst-20195	76	33	.	.	PUNCT
ajst-20195	77	1	the	the	DET
ajst-20195	77	2	performance	performance	NOUN
ajst-20195	77	3	of	of	ADP
ajst-20195	77	4	random	random	ADJ
ajst-20195	77	5	forests	forest	NOUN
ajst-20195	77	6	is	be	AUX
ajst-20195	77	7	usually	usually	ADV
ajst-20195	77	8	evaluated	evaluate	VERB
ajst-20195	77	9	by	by	ADP
ajst-20195	77	10	out	out	ADV
ajst-20195	77	11	-	-	PUNCT
ajst-20195	77	12	of	of	ADP
ajst-20195	77	13	-	-	PUNCT
ajst-20195	77	14	bag	bag	NOUN
ajst-20195	77	15	error	error	NOUN
ajst-20195	77	16	(	(	PUNCT
ajst-20195	77	17	erroobt	erroobt	ADJ
ajst-20195	77	18	)	)	PUNCT
ajst-20195	77	19	,	,	PUNCT
ajst-20195	77	20	while	while	SCONJ
ajst-20195	77	21	variable	variable	ADJ
ajst-20195	77	22	importance	importance	NOUN
ajst-20195	77	23	(	(	PUNCT
ajst-20195	77	24	vi	vi	NOUN
ajst-20195	77	25	)	)	PUNCT
ajst-20195	77	26	is	be	AUX
ajst-20195	77	27	based	base	VERB
ajst-20195	77	28	on	on	ADP
ajst-20195	77	29	accuracy	accuracy	NOUN
ajst-20195	77	30	,	,	PUNCT
ajst-20195	77	31	using	use	VERB
ajst-20195	77	32	the	the	DET
ajst-20195	77	33	significance	significance	NOUN
ajst-20195	77	34	of	of	ADP
ajst-20195	77	35	mean	mean	ADJ
ajst-20195	77	36	square	square	ADJ
ajst-20195	77	37	error	error	NOUN
ajst-20195	77	38	(	(	PUNCT
ajst-20195	77	39	%	%	INTJ
ajst-20195	77	40	incmse	incmse	NOUN
ajst-20195	77	41	)	)	PUNCT
ajst-20195	77	42	and	and	CCONJ
ajst-20195	77	43	node	node	ADJ
ajst-20195	77	44	purity	purity	NOUN
ajst-20195	77	45	(	(	PUNCT
ajst-20195	77	46	incnodepurity	incnodepurity	NOUN
ajst-20195	77	47	)	)	PUNCT
ajst-20195	77	48	to	to	PART
ajst-20195	77	49	rank	rank	VERB
ajst-20195	77	50	them	they	PRON
ajst-20195	77	51	.	.	PUNCT
ajst-20195	78	1	for	for	ADP
ajst-20195	78	2	each	each	DET
ajst-20195	78	3	tree	tree	NOUN
ajst-20195	78	4	(	(	PUNCT
ajst-20195	78	5	t	t	NOUN
ajst-20195	78	6	)	)	PUNCT
ajst-20195	78	7	in	in	ADP
ajst-20195	78	8	the	the	DET
ajst-20195	78	9	random	random	ADJ
ajst-20195	78	10	forest	forest	NOUN
ajst-20195	78	11	,	,	PUNCT
ajst-20195	78	12	the	the	DET
ajst-20195	78	13	rf	rf	ADJ
ajst-20195	78	14	variable	variable	ADJ
ajst-20195	78	15	importance	importance	NOUN
ajst-20195	78	16	of	of	ADP
ajst-20195	78	17	xi	xi	PRON
ajst-20195	78	18	can	can	AUX
ajst-20195	78	19	be	be	AUX
ajst-20195	78	20	calculated	calculate	VERB
ajst-20195	78	21	as	as	ADP
ajst-20195	78	22	in	in	ADP
ajst-20195	78	23	equation	equation	NOUN
ajst-20195	78	24	(	(	PUNCT
ajst-20195	78	25	3	3	X
ajst-20195	78	26	)	)	PUNCT
ajst-20195	78	27	below	below	ADV
ajst-20195	78	28	.	.	PUNCT
ajst-20195	79	1	𝑉𝐼	𝑉𝐼	PROPN
ajst-20195	79	2	𝑋	𝑋	PROPN
ajst-20195	79	3	1	1	NUM
ajst-20195	79	4	𝑛𝑡𝑟𝑒𝑒	𝑛𝑡𝑟𝑒𝑒	ADJ
ajst-20195	79	5	𝑒𝑟𝑟𝑂𝑂	𝑒𝑟𝑟𝑂𝑂	NOUN
ajst-20195	79	6	𝑒𝑟𝑟𝑂𝑂𝐵	𝑒𝑟𝑟𝑂𝑂𝐵	PROPN
ajst-20195	79	7	3	3	NUM
ajst-20195	79	8	where	where	SCONJ
ajst-20195	79	9	t	t	PROPN
ajst-20195	79	10	denotes	denote	VERB
ajst-20195	79	11	each	each	DET
ajst-20195	79	12	tree	tree	NOUN
ajst-20195	79	13	in	in	ADP
ajst-20195	79	14	the	the	DET
ajst-20195	79	15	forest	forest	NOUN
ajst-20195	79	16	;	;	PUNCT
ajst-20195	79	17	oobt	oobt	NOUN
ajst-20195	79	18	denotes	denote	VERB
ajst-20195	79	19	the	the	DET
ajst-20195	79	20	relevant	relevant	ADJ
ajst-20195	79	21	part	part	NOUN
ajst-20195	79	22	of	of	ADP
ajst-20195	79	23	the	the	DET
ajst-20195	79	24	bootstrap	bootstrap	NOUN
ajst-20195	79	25	process	process	NOUN
ajst-20195	79	26	used	use	VERB
ajst-20195	79	27	to	to	PART
ajst-20195	79	28	construct	construct	VERB
ajst-20195	79	29	t	t	PROPN
ajst-20195	79	30	that	that	PRON
ajst-20195	79	31	is	be	AUX
ajst-20195	79	32	not	not	PART
ajst-20195	79	33	included	include	VERB
ajst-20195	79	34	;	;	PUNCT
ajst-20195	79	35	erroobt	erroobt	ADJ
ajst-20195	79	36	is	be	AUX
ajst-20195	79	37	the	the	DET
ajst-20195	79	38	error	error	NOUN
ajst-20195	79	39	of	of	ADP
ajst-20195	79	40	a	a	DET
ajst-20195	79	41	specific	specific	ADJ
ajst-20195	79	42	tree	tree	NOUN
ajst-20195	79	43	t	t	NOUN
ajst-20195	79	44	on	on	ADP
ajst-20195	79	45	the	the	DET
ajst-20195	79	46	relevant	relevant	ADJ
ajst-20195	79	47	oobt	oobt	NOUN
ajst-20195	79	48	sample	sample	NOUN
ajst-20195	79	49	;	;	PUNCT
ajst-20195	79	50	𝑒𝑟𝑟𝑂𝑂	𝑒𝑟𝑟𝑂𝑂	PROPN
ajst-20195	79	51	denotes	denote	VERB
ajst-20195	79	52	the	the	DET
ajst-20195	79	53	perturbed	perturb	VERB
ajst-20195	79	54	samples	sample	NOUN
ajst-20195	79	55	affected	affect	VERB
ajst-20195	79	56	by	by	ADP
ajst-20195	79	57	the	the	DET
ajst-20195	79	58	values	value	NOUN
ajst-20195	79	59	of	of	ADP
ajst-20195	79	60	xi	xi	PROPN
ajst-20195	79	61	alignment	alignment	NOUN
ajst-20195	79	62	.	.	PUNCT
ajst-20195	80	1	in	in	ADP
ajst-20195	80	2	this	this	DET
ajst-20195	80	3	study	study	NOUN
ajst-20195	80	4	,	,	PUNCT
ajst-20195	80	5	the	the	DET
ajst-20195	80	6	size	size	NOUN
ajst-20195	80	7	of	of	ADP
ajst-20195	80	8	the	the	DET
ajst-20195	80	9	subset	subset	NOUN
ajst-20195	80	10	of	of	ADP
ajst-20195	80	11	input	input	NOUN
ajst-20195	80	12	variables	variable	NOUN
ajst-20195	80	13	was	be	AUX
ajst-20195	80	14	set	set	VERB
ajst-20195	80	15	to	to	ADP
ajst-20195	80	16	23	23	NUM
ajst-20195	80	17	by	by	ADP
ajst-20195	80	18	repeated	repeat	VERB
ajst-20195	80	19	tests	test	NOUN
ajst-20195	80	20	,	,	PUNCT
ajst-20195	80	21	and	and	CCONJ
ajst-20195	80	22	the	the	DET
ajst-20195	80	23	number	number	NOUN
ajst-20195	80	24	of	of	ADP
ajst-20195	80	25	trees	tree	NOUN
ajst-20195	80	26	was	be	AUX
ajst-20195	80	27	set	set	VERB
ajst-20195	80	28	to	to	ADP
ajst-20195	80	29	500	500	NUM
ajst-20195	80	30	based	base	VERB
ajst-20195	80	31	on	on	ADP
ajst-20195	80	32	the	the	DET
ajst-20195	80	33	stability	stability	NOUN
ajst-20195	80	34	properties	property	NOUN
ajst-20195	80	35	of	of	ADP
ajst-20195	80	36	𝑒𝑟𝑟𝑂𝑂	𝑒𝑟𝑟𝑂𝑂	NOUN
ajst-20195	80	37	.	.	PUNCT
ajst-20195	81	1	2.5.2	2.5.2	NUM
ajst-20195	81	2	.	.	PUNCT
ajst-20195	81	3	extreme	extreme	ADJ
ajst-20195	81	4	learning	learning	NOUN
ajst-20195	81	5	machines	machine	NOUN
ajst-20195	81	6	(	(	PUNCT
ajst-20195	81	7	elm	elm	PROPN
ajst-20195	81	8	)	)	PUNCT
ajst-20195	81	9	elm	elm	NOUN
ajst-20195	81	10	is	be	AUX
ajst-20195	81	11	a	a	DET
ajst-20195	81	12	relatively	relatively	ADV
ajst-20195	81	13	new	new	ADJ
ajst-20195	81	14	computational	computational	ADJ
ajst-20195	81	15	(	(	PUNCT
ajst-20195	81	16	or	or	CCONJ
ajst-20195	81	17	data	datum	NOUN
ajst-20195	81	18	intelligence	intelligence	NOUN
ajst-20195	81	19	)	)	PUNCT
ajst-20195	81	20	model	model	NOUN
ajst-20195	81	21	designed	design	VERB
ajst-20195	81	22	to	to	PART
ajst-20195	81	23	address	address	VERB
ajst-20195	81	24	the	the	DET
ajst-20195	81	25	shortcomings	shortcoming	NOUN
ajst-20195	81	26	of	of	ADP
ajst-20195	81	27	classical	classical	ADJ
ajst-20195	81	28	machine	machine	NOUN
ajst-20195	81	29	learning	learn	VERB
ajst-20195	81	30	models.the	models.the	DET
ajst-20195	81	31	computation	computation	NOUN
ajst-20195	81	32	in	in	ADP
ajst-20195	81	33	elm	elm	NOUN
ajst-20195	81	34	does	do	AUX
ajst-20195	81	35	not	not	PART
ajst-20195	81	36	require	require	VERB
ajst-20195	81	37	iterations	iteration	NOUN
ajst-20195	81	38	as	as	ADP
ajst-20195	81	39	in	in	ADP
ajst-20195	81	40	gradient	gradient	NOUN
ajst-20195	81	41	-	-	PUNCT
ajst-20195	81	42	based	base	VERB
ajst-20195	81	43	algorithms	algorithm	NOUN
ajst-20195	81	44	.	.	PUNCT
ajst-20195	82	1	in	in	ADP
ajst-20195	82	2	addition	addition	NOUN
ajst-20195	82	3	,	,	PUNCT
ajst-20195	82	4	the	the	DET
ajst-20195	82	5	hidden	hide	VERB
ajst-20195	82	6	nodes	node	NOUN
ajst-20195	82	7	of	of	ADP
ajst-20195	82	8	elm	elm	NOUN
ajst-20195	82	9	can	can	AUX
ajst-20195	82	10	be	be	AUX
ajst-20195	82	11	randomly	randomly	ADV
ajst-20195	82	12	generated	generate	VERB
ajst-20195	82	13	and	and	CCONJ
ajst-20195	82	14	the	the	DET
ajst-20195	82	15	output	output	NOUN
ajst-20195	82	16	weights	weight	NOUN
ajst-20195	82	17	can	can	AUX
ajst-20195	82	18	be	be	AUX
ajst-20195	82	19	solved	solve	VERB
ajst-20195	82	20	by	by	ADP
ajst-20195	82	21	least	least	ADJ
ajst-20195	82	22	squares.elm	squares.elm	PRON
ajst-20195	82	23	has	have	VERB
ajst-20195	82	24	the	the	DET
ajst-20195	82	25	advantages	advantage	NOUN
ajst-20195	82	26	of	of	ADP
ajst-20195	82	27	convenience	convenience	NOUN
ajst-20195	82	28	,	,	PUNCT
ajst-20195	82	29	high	high	ADJ
ajst-20195	82	30	learning	learning	NOUN
ajst-20195	82	31	efficiency	efficiency	NOUN
ajst-20195	82	32	,	,	PUNCT
ajst-20195	82	33	and	and	CCONJ
ajst-20195	82	34	greater	great	ADJ
ajst-20195	82	35	adaptability	adaptability	NOUN
ajst-20195	82	36	to	to	ADP
ajst-20195	82	37	some	some	DET
ajst-20195	82	38	nonlinear	nonlinear	ADJ
ajst-20195	82	39	activations	activation	NOUN
ajst-20195	82	40	and	and	CCONJ
ajst-20195	82	41	kernel	kernel	NOUN
ajst-20195	82	42	functions	function	NOUN
ajst-20195	82	43	.	.	PUNCT
ajst-20195	83	1	2.5.3	2.5.3	X
ajst-20195	83	2	.	.	PUNCT
ajst-20195	84	1	support	support	NOUN
ajst-20195	84	2	vector	vector	NOUN
ajst-20195	84	3	machines	machine	NOUN
ajst-20195	84	4	(	(	PUNCT
ajst-20195	84	5	svm	svm	ADJ
ajst-20195	84	6	)	)	PUNCT
ajst-20195	84	7	support	support	NOUN
ajst-20195	84	8	vector	vector	NOUN
ajst-20195	84	9	machine	machine	NOUN
ajst-20195	84	10	(	(	PUNCT
ajst-20195	84	11	svm	svm	PROPN
ajst-20195	84	12	)	)	PUNCT
ajst-20195	84	13	is	be	AUX
ajst-20195	84	14	a	a	DET
ajst-20195	84	15	supervised	supervised	ADJ
ajst-20195	84	16	machine	machine	NOUN
ajst-20195	84	17	learning	learning	NOUN
ajst-20195	84	18	technique	technique	NOUN
ajst-20195	84	19	with	with	ADP
ajst-20195	84	20	intelligent	intelligent	ADJ
ajst-20195	84	21	design	design	NOUN
ajst-20195	84	22	.	.	PUNCT
ajst-20195	85	1	it	it	PRON
ajst-20195	85	2	was	be	AUX
ajst-20195	85	3	originally	originally	ADV
ajst-20195	85	4	proposed	propose	VERB
ajst-20195	85	5	by	by	ADP
ajst-20195	85	6	boser	boser	NOUN
ajst-20195	85	7	,	,	PUNCT
ajst-20195	85	8	guyon	guyon	NOUN
ajst-20195	85	9	and	and	CCONJ
ajst-20195	85	10	vapnik	vapnik	NOUN
ajst-20195	85	11	in	in	ADP
ajst-20195	85	12	1992[11].svms	1992[11].svms	NUM
ajst-20195	85	13	use	use	VERB
ajst-20195	85	14	learning	learn	VERB
ajst-20195	85	15	algorithms	algorithm	NOUN
ajst-20195	85	16	based	base	VERB
ajst-20195	85	17	on	on	ADP
ajst-20195	85	18	statistical	statistical	ADJ
ajst-20195	85	19	learning	learning	NOUN
ajst-20195	85	20	theory	theory	NOUN
ajst-20195	85	21	and	and	CCONJ
ajst-20195	85	22	optimisation	optimisation	NOUN
ajst-20195	85	23	theory	theory	NOUN
ajst-20195	85	24	to	to	PART
ajst-20195	85	25	enable	enable	VERB
ajst-20195	85	26	computer	computer	NOUN
ajst-20195	85	27	programs	program	NOUN
ajst-20195	85	28	to	to	PART
ajst-20195	85	29	learn	learn	VERB
ajst-20195	85	30	how	how	SCONJ
ajst-20195	85	31	to	to	PART
ajst-20195	85	32	achieve	achieve	VERB
ajst-20195	85	33	classification	classification	NOUN
ajst-20195	85	34	and	and	CCONJ
ajst-20195	85	35	regression	regression	NOUN
ajst-20195	85	36	tasks	task	NOUN
ajst-20195	85	37	,	,	PUNCT
ajst-20195	85	38	improve	improve	VERB
ajst-20195	85	39	prediction	prediction	NOUN
ajst-20195	85	40	accuracy	accuracy	NOUN
ajst-20195	85	41	and	and	CCONJ
ajst-20195	85	42	avoid	avoid	VERB
ajst-20195	85	43	overfitting.the	overfitting.the	DET
ajst-20195	85	44	basic	basic	ADJ
ajst-20195	85	45	idea	idea	NOUN
ajst-20195	85	46	of	of	ADP
ajst-20195	85	47	svms	svms	NOUN
ajst-20195	85	48	is	be	AUX
ajst-20195	85	49	to	to	PART
ajst-20195	85	50	use	use	VERB
ajst-20195	85	51	the	the	DET
ajst-20195	85	52	vapnikbased	vapnikbase	VERB
ajst-20195	85	53	chervonenkis	chervonenki	NOUN
ajst-20195	85	54	(	(	PUNCT
ajst-20195	85	55	vc	vc	NOUN
ajst-20195	85	56	)	)	PUNCT
ajst-20195	85	57	dimension	dimension	NOUN
ajst-20195	85	58	-	-	PUNCT
ajst-20195	85	59	based	base	VERB
ajst-20195	85	60	structural	structural	ADJ
ajst-20195	85	61	risk	risk	NOUN
ajst-20195	85	62	minimisation	minimisation	NOUN
ajst-20195	85	63	(	(	PUNCT
ajst-20195	85	64	srm	srm	NOUN
ajst-20195	85	65	)	)	PUNCT
ajst-20195	85	66	principle	principle	NOUN
ajst-20195	85	67	to	to	PART
ajst-20195	85	68	find	find	VERB
ajst-20195	85	69	hyperplanes	hyperplane	NOUN
ajst-20195	85	70	and	and	CCONJ
ajst-20195	85	71	separate	separate	ADJ
ajst-20195	85	72	data	datum	NOUN
ajst-20195	85	73	in	in	ADP
ajst-20195	85	74	highdimensional	highdimensional	ADJ
ajst-20195	85	75	spaces	space	NOUN
ajst-20195	85	76	.	.	PUNCT
ajst-20195	86	1	compared	compare	VERB
ajst-20195	86	2	to	to	ADP
ajst-20195	86	3	complex	complex	ADJ
ajst-20195	86	4	neural	neural	ADJ
ajst-20195	86	5	network	network	NOUN
ajst-20195	86	6	functions	function	NOUN
ajst-20195	86	7	,	,	PUNCT
ajst-20195	86	8	svms	svms	NOUN
ajst-20195	86	9	are	be	AUX
ajst-20195	86	10	popular	popular	ADJ
ajst-20195	86	11	for	for	ADP
ajst-20195	86	12	their	their	PRON
ajst-20195	86	13	high	high	ADJ
ajst-20195	86	14	empirical	empirical	ADJ
ajst-20195	86	15	performance	performance	NOUN
ajst-20195	86	16	while	while	SCONJ
ajst-20195	86	17	avoiding	avoid	VERB
ajst-20195	86	18	local	local	ADJ
ajst-20195	86	19	minima	minima	NOUN
ajst-20195	86	20	.	.	PUNCT
ajst-20195	87	1	2.6	2.6	NUM
ajst-20195	87	2	.	.	PUNCT
ajst-20195	88	1	evaluation	evaluation	NOUN
ajst-20195	88	2	indicators	indicator	NOUN
ajst-20195	88	3	in	in	ADP
ajst-20195	88	4	order	order	NOUN
ajst-20195	88	5	to	to	PART
ajst-20195	88	6	evaluate	evaluate	VERB
ajst-20195	88	7	and	and	CCONJ
ajst-20195	88	8	compare	compare	VERB
ajst-20195	88	9	the	the	DET
ajst-20195	88	10	overall	overall	ADJ
ajst-20195	88	11	performance	performance	NOUN
ajst-20195	88	12	of	of	ADP
ajst-20195	88	13	the	the	DET
ajst-20195	88	14	estimation	estimation	NOUN
ajst-20195	88	15	models	model	NOUN
ajst-20195	88	16	,	,	PUNCT
ajst-20195	88	17	the	the	DET
ajst-20195	88	18	study	study	NOUN
ajst-20195	88	19	introduced	introduce	VERB
ajst-20195	88	20	the	the	DET
ajst-20195	88	21	coefficient	coefficient	NOUN
ajst-20195	88	22	of	of	ADP
ajst-20195	88	23	determination	determination	NOUN
ajst-20195	88	24	(	(	PUNCT
ajst-20195	88	25	r2	r2	PROPN
ajst-20195	88	26	)	)	PUNCT
ajst-20195	88	27	and	and	CCONJ
ajst-20195	88	28	the	the	DET
ajst-20195	88	29	relative	relative	ADJ
ajst-20195	88	30	error	error	NOUN
ajst-20195	88	31	(	(	PUNCT
ajst-20195	88	32	re	re	NOUN
ajst-20195	88	33	)	)	PUNCT
ajst-20195	88	34	to	to	PART
ajst-20195	88	35	comprehensively	comprehensively	ADV
ajst-20195	88	36	assess	assess	VERB
ajst-20195	88	37	the	the	DET
ajst-20195	88	38	fitting	fitting	ADJ
ajst-20195	88	39	effect	effect	NOUN
ajst-20195	88	40	,	,	PUNCT
ajst-20195	88	41	in	in	ADP
ajst-20195	88	42	which	which	PRON
ajst-20195	88	43	the	the	PRON
ajst-20195	88	44	closer	close	ADV
ajst-20195	88	45	the	the	DET
ajst-20195	88	46	r2	r2	NOUN
ajst-20195	88	47	is	be	AUX
ajst-20195	88	48	to	to	ADP
ajst-20195	88	49	1	1	NUM
ajst-20195	88	50	and	and	CCONJ
ajst-20195	88	51	the	the	DET
ajst-20195	88	52	smaller	small	ADJ
ajst-20195	88	53	the	the	DET
ajst-20195	88	54	re	re	NOUN
ajst-20195	88	55	is	be	AUX
ajst-20195	88	56	,	,	PUNCT
ajst-20195	88	57	the	the	PRON
ajst-20195	88	58	higher	high	ADJ
ajst-20195	88	59	the	the	DET
ajst-20195	88	60	accuracy	accuracy	NOUN
ajst-20195	88	61	of	of	ADP
ajst-20195	88	62	the	the	DET
ajst-20195	88	63	inversion	inversion	NOUN
ajst-20195	88	64	model	model	NOUN
ajst-20195	88	65	of	of	ADP
ajst-20195	88	66	soil	soil	NOUN
ajst-20195	88	67	salt	salt	NOUN
ajst-20195	88	68	content	content	NOUN
ajst-20195	88	69	is	be	AUX
ajst-20195	88	70	.	.	PUNCT
ajst-20195	89	1	𝑅	𝑅	NOUN
ajst-20195	89	2	∑	∑	PROPN
ajst-20195	89	3	𝑦	𝑦	PROPN
ajst-20195	89	4	𝑦	𝑦	PROPN
ajst-20195	89	5	∑	∑	PUNCT
ajst-20195	89	6	𝑦	𝑦	PRON
ajst-20195	89	7	𝑦	𝑦	SYM
ajst-20195	89	8	4	4	NUM
ajst-20195	89	9	𝑅𝐸	𝑅𝐸	PROPN
ajst-20195	89	10	1	1	NUM
ajst-20195	89	11	𝑛	𝑛	PRON
ajst-20195	89	12	𝑦	𝑦	NUM
ajst-20195	89	13	𝑦	𝑦	NOUN
ajst-20195	89	14	𝑦	𝑦	NOUN
ajst-20195	89	15	5	5	NUM
ajst-20195	89	16	where	where	SCONJ
ajst-20195	89	17	n	n	PRON
ajst-20195	89	18	is	be	AUX
ajst-20195	89	19	the	the	DET
ajst-20195	89	20	number	number	NOUN
ajst-20195	89	21	of	of	ADP
ajst-20195	89	22	soil	soil	NOUN
ajst-20195	89	23	samples	sample	NOUN
ajst-20195	89	24	;	;	PUNCT
ajst-20195	89	25	𝑦	𝑦	PRON
ajst-20195	89	26	is	be	AUX
ajst-20195	89	27	the	the	DET
ajst-20195	89	28	predicted	predict	VERB
ajst-20195	89	29	value	value	NOUN
ajst-20195	89	30	;	;	PUNCT
ajst-20195	89	31	𝑦	𝑦	NUM
ajst-20195	89	32	̄	̄	NOUN
ajst-20195	89	33	is	be	AUX
ajst-20195	89	34	the	the	DET
ajst-20195	89	35	mean	mean	ADJ
ajst-20195	89	36	value	value	NOUN
ajst-20195	89	37	;	;	PUNCT
ajst-20195	89	38	and	and	CCONJ
ajst-20195	89	39	𝑦	𝑦	NOUN
ajst-20195	89	40	is	be	AUX
ajst-20195	89	41	the	the	DET
ajst-20195	89	42	measured	measured	ADJ
ajst-20195	89	43	value	value	NOUN
ajst-20195	89	44	.	.	PUNCT
ajst-20195	90	1	3	3	X
ajst-20195	90	2	.	.	NOUN
ajst-20195	90	3	results	result	NOUN
ajst-20195	90	4	and	and	CCONJ
ajst-20195	90	5	analyses	analysis	NOUN
ajst-20195	90	6	3.1	3.1	NUM
ajst-20195	90	7	.	.	PUNCT
ajst-20195	91	1	statistical	statistical	ADJ
ajst-20195	91	2	results	result	NOUN
ajst-20195	91	3	of	of	ADP
ajst-20195	91	4	measured	measure	VERB
ajst-20195	91	5	soil	soil	NOUN
ajst-20195	91	6	salinity	salinity	NOUN
ajst-20195	91	7	data	datum	NOUN
ajst-20195	91	8	in	in	ADP
ajst-20195	91	9	the	the	DET
ajst-20195	91	10	study	study	NOUN
ajst-20195	91	11	area	area	NOUN
ajst-20195	91	12	to	to	PART
ajst-20195	91	13	ensure	ensure	VERB
ajst-20195	91	14	generalisation	generalisation	NOUN
ajst-20195	91	15	and	and	CCONJ
ajst-20195	91	16	robustness	robustness	NOUN
ajst-20195	91	17	of	of	ADP
ajst-20195	91	18	the	the	DET
ajst-20195	91	19	model	model	NOUN
ajst-20195	91	20	,	,	PUNCT
ajst-20195	91	21	all	all	DET
ajst-20195	91	22	soil	soil	NOUN
ajst-20195	91	23	samples	sample	NOUN
ajst-20195	91	24	(	(	PUNCT
ajst-20195	91	25	collected	collect	VERB
ajst-20195	91	26	in	in	ADP
ajst-20195	91	27	spring	spring	NOUN
ajst-20195	91	28	and	and	CCONJ
ajst-20195	91	29	summer	summer	NOUN
ajst-20195	91	30	)	)	PUNCT
ajst-20195	91	31	were	be	AUX
ajst-20195	91	32	considered	consider	VERB
ajst-20195	91	33	as	as	SCONJ
ajst-20195	91	34	one	one	NUM
ajst-20195	91	35	dataset	dataset	NOUN
ajst-20195	91	36	in	in	ADP
ajst-20195	91	37	this	this	DET
ajst-20195	91	38	study	study	NOUN
ajst-20195	91	39	.	.	PUNCT
ajst-20195	92	1	the	the	DET
ajst-20195	92	2	dataset	dataset	NOUN
ajst-20195	92	3	contains	contain	VERB
ajst-20195	92	4	a	a	DET
ajst-20195	92	5	total	total	NOUN
ajst-20195	92	6	of	of	ADP
ajst-20195	92	7	86	86	NUM
ajst-20195	92	8	samples	sample	NOUN
ajst-20195	92	9	and	and	CCONJ
ajst-20195	92	10	is	be	AUX
ajst-20195	92	11	divided	divide	VERB
ajst-20195	92	12	into	into	ADP
ajst-20195	92	13	two	two	NUM
ajst-20195	92	14	parts	part	NOUN
ajst-20195	92	15	using	use	VERB
ajst-20195	92	16	kennard	kennard	NOUN
ajst-20195	92	17	-	-	PUNCT
ajst-20195	92	18	stone	stone	NOUN
ajst-20195	92	19	(	(	PUNCT
ajst-20195	92	20	k	k	NOUN
ajst-20195	92	21	-	-	NOUN
ajst-20195	92	22	s)[12	s)[12	NOUN
ajst-20195	92	23	]	]	X
ajst-20195	92	24	:	:	PUNCT
ajst-20195	92	25	55	55	NUM
ajst-20195	92	26	soil	soil	NOUN
ajst-20195	92	27	samples	sample	NOUN
ajst-20195	92	28	constitute	constitute	VERB
ajst-20195	92	29	the	the	DET
ajst-20195	92	30	calibration	calibration	NOUN
ajst-20195	92	31	set	set	VERB
ajst-20195	92	32	and	and	CCONJ
ajst-20195	92	33	31	31	NUM
ajst-20195	92	34	soil	soil	NOUN
ajst-20195	92	35	samples	sample	NOUN
ajst-20195	92	36	constitute	constitute	VERB
ajst-20195	92	37	the	the	DET
ajst-20195	92	38	validation	validation	NOUN
ajst-20195	92	39	set	set	VERB
ajst-20195	92	40	as	as	SCONJ
ajst-20195	92	41	shown	show	VERB
ajst-20195	92	42	in	in	ADP
ajst-20195	92	43	table	table	NOUN
ajst-20195	92	44	3	3	NUM
ajst-20195	92	45	.	.	PUNCT
ajst-20195	93	1	the	the	DET
ajst-20195	93	2	two	two	NUM
ajst-20195	93	3	sets	set	NOUN
ajst-20195	93	4	were	be	AUX
ajst-20195	93	5	used	use	VERB
ajst-20195	93	6	for	for	ADP
ajst-20195	93	7	crossvalidation	crossvalidation	NOUN
ajst-20195	93	8	and	and	CCONJ
ajst-20195	93	9	independent	independent	ADJ
ajst-20195	93	10	validation	validation	NOUN
ajst-20195	93	11	,	,	PUNCT
ajst-20195	93	12	respectively	respectively	ADV
ajst-20195	93	13	.	.	PUNCT
ajst-20195	94	1	103	103	NUM
ajst-20195	94	2	table	table	NOUN
ajst-20195	94	3	3	3	NUM
ajst-20195	94	4	.	.	PUNCT
ajst-20195	94	5	division	division	NOUN
ajst-20195	94	6	of	of	ADP
ajst-20195	94	7	training	training	NOUN
ajst-20195	94	8	and	and	CCONJ
ajst-20195	94	9	validation	validation	NOUN
ajst-20195	94	10	sets	set	NOUN
ajst-20195	94	11	depth	depth	NOUN
ajst-20195	94	12	/	/	SYM
ajst-20195	94	13	cm	cm	NOUN
ajst-20195	94	14	data	data	NOUN
ajst-20195	94	15	sets	set	NOUN
ajst-20195	94	16	type	type	NOUN
ajst-20195	94	17	of	of	ADP
ajst-20195	94	18	sampling	sample	VERB
ajst-20195	94	19	point	point	NOUN
ajst-20195	94	20	salinity	salinity	NOUN
ajst-20195	94	21	(	(	PUNCT
ajst-20195	94	22	g/100	g/100	PROPN
ajst-20195	94	23	g	g	NOUN
ajst-20195	94	24	)	)	PUNCT
ajst-20195	94	25	unsalted	unsalted	ADJ
ajst-20195	94	26	(	(	PUNCT
ajst-20195	94	27	<	<	NOUN
ajst-20195	94	28	0.2	0.2	NUM
ajst-20195	94	29	%	%	NOUN
ajst-20195	94	30	)	)	PUNCT
ajst-20195	94	31	mild	mild	ADJ
ajst-20195	94	32	salinisation	salinisation	NOUN
ajst-20195	94	33	(	(	PUNCT
ajst-20195	94	34	0.2%~0.5	0.2%~0.5	NUM
ajst-20195	94	35	%	%	NOUN
ajst-20195	94	36	)	)	PUNCT
ajst-20195	94	37	heavy	heavy	ADJ
ajst-20195	94	38	salinisation	salinisation	NOUN
ajst-20195	94	39	(	(	PUNCT
ajst-20195	94	40	0.5%~1.0	0.5%~1.0	PROPN
ajst-20195	94	41	%	%	NOUN
ajst-20195	94	42	)	)	PUNCT
ajst-20195	94	43	salted	salt	VERB
ajst-20195	94	44	soil	soil	NOUN
ajst-20195	94	45	(	(	PUNCT
ajst-20195	94	46	>	>	X
ajst-20195	94	47	1.0	1.0	NUM
ajst-20195	94	48	%	%	NOUN
ajst-20195	94	49	)	)	PUNCT
ajst-20195	95	1	sd%	sd%	PROPN
ajst-20195	95	2	cv	cv	PROPN
ajst-20195	95	3	0	0	NUM
ajst-20195	95	4	-	-	SYM
ajst-20195	95	5	20	20	NUM
ajst-20195	95	6	total	total	ADJ
ajst-20195	95	7	sample	sample	NOUN
ajst-20195	95	8	24	24	NUM
ajst-20195	95	9	39	39	NUM
ajst-20195	95	10	21	21	NUM
ajst-20195	95	11	2	2	NUM
ajst-20195	95	12	2.85	2.85	NUM
ajst-20195	95	13	0.62	0.62	NUM
ajst-20195	95	14	training	training	NOUN
ajst-20195	95	15	set	set	VERB
ajst-20195	95	16	15	15	NUM
ajst-20195	95	17	24	24	NUM
ajst-20195	95	18	15	15	NUM
ajst-20195	95	19	1	1	NUM
ajst-20195	95	20	2.94	2.94	NUM
ajst-20195	95	21	0.62	0.62	NUM
ajst-20195	95	22	validation	validation	NOUN
ajst-20195	95	23	set	set	VERB
ajst-20195	95	24	9	9	NUM
ajst-20195	95	25	15	15	NUM
ajst-20195	95	26	6	6	NUM
ajst-20195	95	27	1	1	NUM
ajst-20195	95	28	3.02	3.02	NUM
ajst-20195	95	29	0.61	0.61	NUM
ajst-20195	95	30	the	the	DET
ajst-20195	95	31	mean	mean	ADJ
ajst-20195	95	32	value	value	NOUN
ajst-20195	95	33	of	of	ADP
ajst-20195	95	34	soil	soil	NOUN
ajst-20195	95	35	salinity	salinity	NOUN
ajst-20195	95	36	in	in	ADP
ajst-20195	95	37	the	the	DET
ajst-20195	95	38	study	study	NOUN
ajst-20195	95	39	area	area	NOUN
ajst-20195	95	40	was	be	AUX
ajst-20195	95	41	4.855	4.855	NUM
ajst-20195	95	42	g	g	NOUN
ajst-20195	95	43	/	/	SYM
ajst-20195	95	44	kg	kg	NOUN
ajst-20195	95	45	in	in	ADP
ajst-20195	95	46	spring	spring	NOUN
ajst-20195	95	47	(	(	PUNCT
ajst-20195	95	48	may	may	PROPN
ajst-20195	95	49	)	)	PUNCT
ajst-20195	95	50	and	and	CCONJ
ajst-20195	95	51	2.548	2.548	NUM
ajst-20195	95	52	g	g	NOUN
ajst-20195	95	53	/	/	SYM
ajst-20195	95	54	kg	kg	NOUN
ajst-20195	95	55	in	in	ADP
ajst-20195	95	56	summer	summer	NOUN
ajst-20195	95	57	(	(	PUNCT
ajst-20195	95	58	july	july	PROPN
ajst-20195	95	59	)	)	PUNCT
ajst-20195	95	60	(	(	PUNCT
ajst-20195	95	61	fig	fig	NOUN
ajst-20195	95	62	.	.	PUNCT
ajst-20195	95	63	1	1	NUM
ajst-20195	95	64	)	)	PUNCT
ajst-20195	95	65	.	.	PUNCT
ajst-20195	96	1	according	accord	VERB
ajst-20195	96	2	to	to	ADP
ajst-20195	96	3	the	the	DET
ajst-20195	96	4	soil	soil	NOUN
ajst-20195	96	5	salinity	salinity	NOUN
ajst-20195	96	6	grading	grade	VERB
ajst-20195	96	7	criteria	criterion	NOUN
ajst-20195	96	8	[	[	X
ajst-20195	96	9	10	10	NUM
ajst-20195	96	10	]	]	PUNCT
ajst-20195	96	11	,	,	PUNCT
ajst-20195	96	12	most	most	ADJ
ajst-20195	96	13	of	of	ADP
ajst-20195	96	14	the	the	DET
ajst-20195	96	15	study	study	NOUN
ajst-20195	96	16	area	area	NOUN
ajst-20195	96	17	is	be	AUX
ajst-20195	96	18	in	in	ADP
ajst-20195	96	19	the	the	DET
ajst-20195	96	20	region	region	NOUN
ajst-20195	96	21	of	of	ADP
ajst-20195	96	22	moderate	moderate	ADJ
ajst-20195	96	23	to	to	PART
ajst-20195	96	24	light	light	ADJ
ajst-20195	96	25	salinity	salinity	NOUN
ajst-20195	96	26	,	,	PUNCT
ajst-20195	96	27	but	but	CCONJ
ajst-20195	96	28	there	there	PRON
ajst-20195	96	29	are	be	VERB
ajst-20195	96	30	some	some	DET
ajst-20195	96	31	areas	area	NOUN
ajst-20195	96	32	with	with	ADP
ajst-20195	96	33	heavy	heavy	ADJ
ajst-20195	96	34	salinity	salinity	NOUN
ajst-20195	96	35	.	.	PUNCT
ajst-20195	97	1	this	this	DET
ajst-20195	97	2	situation	situation	NOUN
ajst-20195	97	3	is	be	AUX
ajst-20195	97	4	basically	basically	ADV
ajst-20195	97	5	consistent	consistent	ADJ
ajst-20195	97	6	with	with	ADP
ajst-20195	97	7	the	the	DET
ajst-20195	97	8	growth	growth	NOUN
ajst-20195	97	9	of	of	ADP
ajst-20195	97	10	crops	crop	NOUN
ajst-20195	97	11	in	in	ADP
ajst-20195	97	12	the	the	DET
ajst-20195	97	13	study	study	NOUN
ajst-20195	97	14	area	area	NOUN
ajst-20195	97	15	.	.	PUNCT
ajst-20195	98	1	figure	figure	NOUN
ajst-20195	98	2	1	1	NUM
ajst-20195	98	3	.	.	PUNCT
ajst-20195	99	1	soil	soil	NOUN
ajst-20195	99	2	descriptive	descriptive	ADJ
ajst-20195	99	3	statistics	statistic	NOUN
ajst-20195	99	4	3.2	3.2	NUM
ajst-20195	99	5	.	.	PUNCT
ajst-20195	100	1	comparison	comparison	NOUN
ajst-20195	100	2	of	of	ADP
ajst-20195	100	3	the	the	DET
ajst-20195	100	4	red	red	ADJ
ajst-20195	100	5	edge	edge	NOUN
ajst-20195	100	6	index	index	NOUN
ajst-20195	100	7	with	with	ADP
ajst-20195	100	8	existing	exist	VERB
ajst-20195	100	9	soil	soil	NOUN
ajst-20195	100	10	salinity	salinity	NOUN
ajst-20195	100	11	indices	indice	VERB
ajst-20195	100	12	a	a	DET
ajst-20195	100	13	comparison	comparison	NOUN
ajst-20195	100	14	was	be	AUX
ajst-20195	100	15	made	make	VERB
ajst-20195	100	16	between	between	ADP
ajst-20195	100	17	existing	exist	VERB
ajst-20195	100	18	soil	soil	NOUN
ajst-20195	100	19	salinity	salinity	NOUN
ajst-20195	100	20	indices	index	NOUN
ajst-20195	100	21	and	and	CCONJ
ajst-20195	100	22	soil	soil	NOUN
ajst-20195	100	23	salinity	salinity	NOUN
ajst-20195	100	24	data	datum	NOUN
ajst-20195	100	25	extracted	extract	VERB
ajst-20195	100	26	from	from	ADP
ajst-20195	100	27	the	the	DET
ajst-20195	100	28	huinong	huinong	NOUN
ajst-20195	100	29	district	district	NOUN
ajst-20195	100	30	.	.	PUNCT
ajst-20195	101	1	considering	consider	VERB
ajst-20195	101	2	the	the	DET
ajst-20195	101	3	new	new	ADJ
ajst-20195	101	4	spectral	spectral	ADJ
ajst-20195	101	5	capabilities	capability	NOUN
ajst-20195	101	6	of	of	ADP
ajst-20195	101	7	the	the	DET
ajst-20195	101	8	three	three	NUM
ajst-20195	101	9	additional	additional	ADJ
ajst-20195	101	10	red	red	ADJ
ajst-20195	101	11	-	-	PUNCT
ajst-20195	101	12	edge	edge	NOUN
ajst-20195	101	13	bands	band	NOUN
ajst-20195	101	14	,	,	PUNCT
ajst-20195	101	15	three	three	NUM
ajst-20195	101	16	bands	band	NOUN
ajst-20195	101	17	(	(	PUNCT
ajst-20195	101	18	b5	b5	PROPN
ajst-20195	101	19	-	-	PUNCT
ajst-20195	101	20	b7	b7	PROPN
ajst-20195	101	21	)	)	PUNCT
ajst-20195	101	22	were	be	AUX
ajst-20195	101	23	used	use	VERB
ajst-20195	101	24	in	in	ADP
ajst-20195	101	25	this	this	DET
ajst-20195	101	26	study	study	NOUN
ajst-20195	101	27	instead	instead	ADV
ajst-20195	101	28	of	of	ADP
ajst-20195	101	29	b4	b4	NOUN
ajst-20195	101	30	,	,	PUNCT
ajst-20195	101	31	and	and	CCONJ
ajst-20195	101	32	all	all	PRON
ajst-20195	101	33	of	of	ADP
ajst-20195	101	34	the	the	DET
ajst-20195	101	35	published	publish	VERB
ajst-20195	101	36	indices	index	NOUN
ajst-20195	101	37	showed	show	VERB
ajst-20195	101	38	significant	significant	ADJ
ajst-20195	101	39	correlations	correlation	NOUN
ajst-20195	101	40	with	with	ADP
ajst-20195	101	41	conductivity	conductivity	NOUN
ajst-20195	101	42	at	at	ADP
ajst-20195	101	43	the	the	DET
ajst-20195	101	44	0.01	0.01	NUM
ajst-20195	101	45	level	level	NOUN
ajst-20195	101	46	(	(	PUNCT
ajst-20195	101	47	p	p	X
ajst-20195	101	48	<	<	X
ajst-20195	101	49	0.01	0.01	NUM
ajst-20195	101	50	)	)	PUNCT
ajst-20195	101	51	,	,	PUNCT
ajst-20195	101	52	except	except	SCONJ
ajst-20195	101	53	for	for	ADP
ajst-20195	101	54	the	the	DET
ajst-20195	101	55	ndsi	ndsi	ADJ
ajst-20195	101	56	,	,	PUNCT
ajst-20195	101	57	s1	s1	NOUN
ajst-20195	101	58	,	,	PUNCT
ajst-20195	101	59	and	and	CCONJ
ajst-20195	101	60	s2	s2	PROPN
ajst-20195	101	61	,	,	PUNCT
ajst-20195	101	62	which	which	PRON
ajst-20195	101	63	were	be	AUX
ajst-20195	101	64	relatively	relatively	ADV
ajst-20195	101	65	unsatisfactory	unsatisfactory	ADJ
ajst-20195	101	66	.	.	PUNCT
ajst-20195	102	1	these	these	DET
ajst-20195	102	2	three	three	NUM
ajst-20195	102	3	indices	index	NOUN
ajst-20195	102	4	will	will	AUX
ajst-20195	102	5	be	be	AUX
ajst-20195	102	6	discussed	discuss	VERB
ajst-20195	102	7	separately	separately	ADV
ajst-20195	102	8	in	in	ADP
ajst-20195	102	9	this	this	DET
ajst-20195	102	10	study	study	NOUN
ajst-20195	102	11	.	.	PUNCT
ajst-20195	103	1	an	an	DET
ajst-20195	103	2	increase	increase	NOUN
ajst-20195	103	3	in	in	ADP
ajst-20195	103	4	correlation	correlation	NOUN
ajst-20195	103	5	can	can	AUX
ajst-20195	103	6	be	be	AUX
ajst-20195	103	7	observed	observe	VERB
ajst-20195	103	8	when	when	SCONJ
ajst-20195	103	9	replacing	replace	VERB
ajst-20195	103	10	the	the	DET
ajst-20195	103	11	red	red	ADJ
ajst-20195	103	12	band	band	NOUN
ajst-20195	103	13	with	with	ADP
ajst-20195	103	14	the	the	DET
ajst-20195	103	15	red	red	ADJ
ajst-20195	103	16	-	-	PUNCT
ajst-20195	103	17	edge	edge	NOUN
ajst-20195	103	18	band	band	NOUN
ajst-20195	103	19	(	(	PUNCT
ajst-20195	103	20	fig	fig	NOUN
ajst-20195	103	21	.	.	PUNCT
ajst-20195	104	1	2	2	NUM
ajst-20195	104	2	)	)	PUNCT
ajst-20195	104	3	.	.	PUNCT
ajst-20195	105	1	the	the	DET
ajst-20195	105	2	introduction	introduction	NOUN
ajst-20195	105	3	of	of	ADP
ajst-20195	105	4	the	the	DET
ajst-20195	105	5	red	red	ADJ
ajst-20195	105	6	-	-	PUNCT
ajst-20195	105	7	edge	edge	NOUN
ajst-20195	105	8	band	band	NOUN
ajst-20195	105	9	enhanced	enhance	VERB
ajst-20195	105	10	the	the	DET
ajst-20195	105	11	sensitivity	sensitivity	NOUN
ajst-20195	105	12	of	of	ADP
ajst-20195	105	13	the	the	DET
ajst-20195	105	14	salinity	salinity	NOUN
ajst-20195	105	15	index	index	NOUN
ajst-20195	105	16	to	to	PART
ajst-20195	105	17	soil	soil	NOUN
ajst-20195	105	18	salinity	salinity	NOUN
ajst-20195	105	19	,	,	PUNCT
ajst-20195	105	20	probably	probably	ADV
ajst-20195	105	21	because	because	SCONJ
ajst-20195	105	22	of	of	ADP
ajst-20195	105	23	the	the	DET
ajst-20195	105	24	novel	novel	ADJ
ajst-20195	105	25	spectral	spectral	ADJ
ajst-20195	105	26	information	information	NOUN
ajst-20195	105	27	and	and	CCONJ
ajst-20195	105	28	higher	high	ADJ
ajst-20195	105	29	signalto	signalto	NOUN
ajst-20195	105	30	-	-	PUNCT
ajst-20195	105	31	noise	noise	NOUN
ajst-20195	105	32	ratio	ratio	NOUN
ajst-20195	105	33	in	in	ADP
ajst-20195	105	34	the	the	DET
ajst-20195	105	35	red	red	ADJ
ajst-20195	105	36	-	-	PUNCT
ajst-20195	105	37	edge	edge	NOUN
ajst-20195	105	38	region	region	NOUN
ajst-20195	105	39	.	.	PUNCT
ajst-20195	106	1	for	for	ADP
ajst-20195	106	2	the	the	DET
ajst-20195	106	3	three	three	NUM
ajst-20195	106	4	less	less	ADV
ajst-20195	106	5	desirable	desirable	ADJ
ajst-20195	106	6	ones	one	NOUN
ajst-20195	106	7	(	(	PUNCT
ajst-20195	106	8	ndsi	ndsi	PROPN
ajst-20195	106	9	,	,	PUNCT
ajst-20195	106	10	s1	s1	NOUN
ajst-20195	106	11	and	and	CCONJ
ajst-20195	106	12	s2	s2	PROPN
ajst-20195	106	13	)	)	PUNCT
ajst-20195	106	14	,	,	PUNCT
ajst-20195	106	15	the	the	DET
ajst-20195	106	16	improvement	improvement	NOUN
ajst-20195	106	17	with	with	ADP
ajst-20195	106	18	the	the	DET
ajst-20195	106	19	introduction	introduction	NOUN
ajst-20195	106	20	of	of	ADP
ajst-20195	106	21	the	the	DET
ajst-20195	106	22	red	red	ADJ
ajst-20195	106	23	-	-	PUNCT
ajst-20195	106	24	edge	edge	NOUN
ajst-20195	106	25	bands	band	NOUN
ajst-20195	106	26	was	be	AUX
ajst-20195	106	27	not	not	PART
ajst-20195	106	28	satisfactory	satisfactory	ADJ
ajst-20195	106	29	.	.	PUNCT
ajst-20195	107	1	however	however	ADV
ajst-20195	107	2	,	,	PUNCT
ajst-20195	107	3	these	these	DET
ajst-20195	107	4	less	less	ADV
ajst-20195	107	5	predictive	predictive	ADJ
ajst-20195	107	6	spectral	spectral	ADJ
ajst-20195	107	7	covariates	covariate	NOUN
ajst-20195	107	8	were	be	AUX
ajst-20195	107	9	not	not	PART
ajst-20195	107	10	excluded	exclude	VERB
ajst-20195	107	11	from	from	ADP
ajst-20195	107	12	this	this	DET
ajst-20195	107	13	study	study	NOUN
ajst-20195	107	14	.	.	PUNCT
ajst-20195	108	1	figure	figure	NOUN
ajst-20195	108	2	2	2	NUM
ajst-20195	108	3	.	.	PUNCT
ajst-20195	108	4	correlation	correlation	NOUN
ajst-20195	108	5	between	between	ADP
ajst-20195	108	6	electrical	electrical	ADJ
ajst-20195	108	7	conductivity	conductivity	NOUN
ajst-20195	108	8	and	and	CCONJ
ajst-20195	108	9	different	different	ADJ
ajst-20195	108	10	soil	soil	NOUN
ajst-20195	108	11	salinity	salinity	NOUN
ajst-20195	108	12	indices	index	NOUN
ajst-20195	108	13	(	(	PUNCT
ajst-20195	108	14	existing	exist	VERB
ajst-20195	108	15	and	and	CCONJ
ajst-20195	108	16	derived	derive	VERB
ajst-20195	108	17	red	red	ADJ
ajst-20195	108	18	-	-	PUNCT
ajst-20195	108	19	edge	edge	NOUN
ajst-20195	108	20	indices	index	NOUN
ajst-20195	108	21	)	)	PUNCT
ajst-20195	108	22	3.3	3.3	NUM
ajst-20195	108	23	.	.	PUNCT
ajst-20195	109	1	spectral	spectral	ADJ
ajst-20195	109	2	index	index	NOUN
ajst-20195	109	3	combinations	combination	NOUN
ajst-20195	109	4	based	base	VERB
ajst-20195	109	5	on	on	ADP
ajst-20195	109	6	correlation	correlation	NOUN
ajst-20195	109	7	analysis	analysis	NOUN
ajst-20195	109	8	the	the	DET
ajst-20195	109	9	study	study	NOUN
ajst-20195	109	10	used	use	VERB
ajst-20195	109	11	a	a	DET
ajst-20195	109	12	screening	screening	NOUN
ajst-20195	109	13	method	method	NOUN
ajst-20195	109	14	based	base	VERB
ajst-20195	109	15	on	on	ADP
ajst-20195	109	16	the	the	DET
ajst-20195	109	17	pls	pls	ADJ
ajst-20195	109	18	-	-	PUNCT
ajst-20195	109	19	vip	vip	NOUN
ajst-20195	109	20	criterion	criterion	NOUN
ajst-20195	109	21	for	for	ADP
ajst-20195	109	22	44	44	NUM
ajst-20195	109	23	spectral	spectral	ADJ
ajst-20195	109	24	covariates	covariate	NOUN
ajst-20195	109	25	(	(	PUNCT
ajst-20195	109	26	11	11	NUM
ajst-20195	109	27	existing	exist	VERB
ajst-20195	109	28	soil	soil	NOUN
ajst-20195	109	29	salinity	salinity	NOUN
ajst-20195	109	30	indices	index	NOUN
ajst-20195	109	31	,	,	PUNCT
ajst-20195	109	32	33	33	NUM
ajst-20195	109	33	red	red	ADJ
ajst-20195	109	34	-	-	PUNCT
ajst-20195	109	35	edge	edge	NOUN
ajst-20195	109	36	indices	index	NOUN
ajst-20195	109	37	)	)	PUNCT
ajst-20195	109	38	.	.	PUNCT
ajst-20195	110	1	variables	variable	NOUN
ajst-20195	110	2	with	with	ADP
ajst-20195	110	3	results	result	NOUN
ajst-20195	110	4	greater	great	ADJ
ajst-20195	110	5	than	than	ADP
ajst-20195	110	6	1	1	NUM
ajst-20195	110	7	calculated	calculate	VERB
ajst-20195	110	8	by	by	ADP
ajst-20195	110	9	pls	pls	NOUN
ajst-20195	110	10	-	-	PUNCT
ajst-20195	110	11	vip	vip	NOUN
ajst-20195	110	12	were	be	AUX
ajst-20195	110	13	considered	consider	VERB
ajst-20195	110	14	as	as	ADP
ajst-20195	110	15	more	more	ADV
ajst-20195	110	16	important	important	ADJ
ajst-20195	110	17	variables	variable	NOUN
ajst-20195	110	18	for	for	ADP
ajst-20195	110	19	the	the	DET
ajst-20195	110	20	measured	measure	VERB
ajst-20195	110	21	soil	soil	NOUN
ajst-20195	110	22	salinity	salinity	NOUN
ajst-20195	110	23	and	and	CCONJ
ajst-20195	110	24	were	be	AUX
ajst-20195	110	25	used	use	VERB
ajst-20195	110	26	as	as	ADP
ajst-20195	110	27	independent	independent	ADJ
ajst-20195	110	28	variables	variable	NOUN
ajst-20195	110	29	in	in	ADP
ajst-20195	110	30	the	the	DET
ajst-20195	110	31	satellite	satellite	NOUN
ajst-20195	110	32	remote	remote	ADJ
ajst-20195	110	33	sensing	sense	VERB
ajst-20195	110	34	inversion	inversion	NOUN
ajst-20195	110	35	model.the	model.the	DET
ajst-20195	110	36	results	result	NOUN
ajst-20195	110	37	of	of	ADP
ajst-20195	110	38	the	the	DET
ajst-20195	110	39	pls	pls	ADJ
ajst-20195	110	40	-	-	PUNCT
ajst-20195	110	41	vip	vip	NOUN
ajst-20195	110	42	criterion	criterion	NOUN
ajst-20195	110	43	screening	screening	NOUN
ajst-20195	110	44	are	be	AUX
ajst-20195	110	45	shown	show	VERB
ajst-20195	110	46	in	in	ADP
ajst-20195	110	47	fig	fig	NOUN
ajst-20195	110	48	.	.	PUNCT
ajst-20195	111	1	3	3	NUM
ajst-20195	111	2	,	,	PUNCT
ajst-20195	111	3	and	and	CCONJ
ajst-20195	111	4	a	a	DET
ajst-20195	111	5	total	total	NOUN
ajst-20195	111	6	of	of	ADP
ajst-20195	111	7	11	11	NUM
ajst-20195	111	8	variables	variable	NOUN
ajst-20195	111	9	were	be	AUX
ajst-20195	111	10	screened	screen	VERB
ajst-20195	111	11	(	(	PUNCT
ajst-20195	111	12	int2	int2	NOUN
ajst-20195	111	13	,	,	PUNCT
ajst-20195	111	14	si2	si2	PROPN
ajst-20195	111	15	,	,	PUNCT
ajst-20195	111	16	s2	s2	PROPN
ajst-20195	111	17	,	,	PUNCT
ajst-20195	111	18	int1re1	int1re1	PROPN
ajst-20195	111	19	,	,	PUNCT
ajst-20195	111	20	ndsi	ndsi	PROPN
ajst-20195	111	21	re1	re1	PROPN
ajst-20195	111	22	,	,	PUNCT
ajst-20195	111	23	s2	s2	PROPN
ajst-20195	111	24	re2	re2	PROPN
ajst-20195	111	25	,	,	PUNCT
ajst-20195	111	26	s3	s3	PROPN
ajst-20195	111	27	re3	re3	PROPN
ajst-20195	111	28	,	,	PUNCT
ajst-20195	111	29	si	si	PROPN
ajst-20195	111	30	re2	re2	PROPN
ajst-20195	111	31	,	,	PUNCT
ajst-20195	111	32	si1	si1	PROPN
ajst-20195	111	33	re1	re1	PROPN
ajst-20195	111	34	,	,	PUNCT
ajst-20195	111	35	si2	si2	PROPN
ajst-20195	111	36	re2	re2	PROPN
ajst-20195	111	37	,	,	PUNCT
ajst-20195	111	38	si3	si3	PROPN
ajst-20195	111	39	re1	re1	PROPN
ajst-20195	111	40	)	)	PUNCT
ajst-20195	111	41	.	.	PUNCT
ajst-20195	112	1	compared	compare	VERB
ajst-20195	112	2	with	with	ADP
ajst-20195	112	3	the	the	DET
ajst-20195	112	4	initial	initial	ADJ
ajst-20195	112	5	44	44	NUM
ajst-20195	112	6	variables	variable	NOUN
ajst-20195	112	7	provided	provide	VERB
ajst-20195	112	8	,	,	PUNCT
ajst-20195	112	9	the	the	DET
ajst-20195	112	10	screening	screening	NOUN
ajst-20195	112	11	method	method	NOUN
ajst-20195	112	12	based	base	VERB
ajst-20195	112	13	on	on	ADP
ajst-20195	112	14	the	the	DET
ajst-20195	112	15	plsvip	plsvip	NOUN
ajst-20195	112	16	criterion	criterion	NOUN
ajst-20195	112	17	greatly	greatly	ADV
ajst-20195	112	18	reduces	reduce	VERB
ajst-20195	112	19	the	the	DET
ajst-20195	112	20	number	number	NOUN
ajst-20195	112	21	of	of	ADP
ajst-20195	112	22	variables	variable	NOUN
ajst-20195	112	23	,	,	PUNCT
ajst-20195	112	24	which	which	PRON
ajst-20195	112	25	effectively	effectively	ADV
ajst-20195	112	26	reduces	reduce	VERB
ajst-20195	112	27	the	the	DET
ajst-20195	112	28	amount	amount	NOUN
ajst-20195	112	29	of	of	ADP
ajst-20195	112	30	model	model	NOUN
ajst-20195	112	31	calculations	calculation	NOUN
ajst-20195	112	32	and	and	CCONJ
ajst-20195	112	33	saves	save	VERB
ajst-20195	112	34	time	time	NOUN
ajst-20195	112	35	for	for	SCONJ
ajst-20195	112	36	the	the	DET
ajst-20195	112	37	study	study	NOUN
ajst-20195	112	38	to	to	PART
ajst-20195	112	39	construct	construct	VERB
ajst-20195	112	40	the	the	DET
ajst-20195	112	41	model	model	NOUN
ajst-20195	112	42	.	.	PUNCT
ajst-20195	113	1	it	it	PRON
ajst-20195	113	2	can	can	AUX
ajst-20195	113	3	also	also	ADV
ajst-20195	113	4	be	be	AUX
ajst-20195	113	5	seen	see	VERB
ajst-20195	113	6	that	that	SCONJ
ajst-20195	113	7	the	the	DET
ajst-20195	113	8	calculation	calculation	NOUN
ajst-20195	113	9	results	result	NOUN
ajst-20195	113	10	of	of	ADP
ajst-20195	113	11	the	the	DET
ajst-20195	113	12	newly	newly	ADV
ajst-20195	113	13	proposed	propose	VERB
ajst-20195	113	14	rededge	rededge	PROPN
ajst-20195	113	15	spectral	spectral	ADJ
ajst-20195	113	16	index	index	NOUN
ajst-20195	113	17	are	be	AUX
ajst-20195	113	18	overall	overall	ADV
ajst-20195	113	19	greater	great	ADJ
ajst-20195	113	20	than	than	ADP
ajst-20195	113	21	the	the	DET
ajst-20195	113	22	existing	exist	VERB
ajst-20195	113	23	soil	soil	NOUN
ajst-20195	113	24	salinity	salinity	NOUN
ajst-20195	113	25	index	index	NOUN
ajst-20195	113	26	,	,	PUNCT
ajst-20195	113	27	thanks	thank	NOUN
ajst-20195	113	28	to	to	ADP
ajst-20195	113	29	the	the	DET
ajst-20195	113	30	fact	fact	NOUN
ajst-20195	113	31	that	that	SCONJ
ajst-20195	113	32	this	this	DET
ajst-20195	113	33	additional	additional	ADJ
ajst-20195	113	34	spectral	spectral	ADJ
ajst-20195	113	35	information	information	NOUN
ajst-20195	113	36	can	can	AUX
ajst-20195	113	37	provide	provide	VERB
ajst-20195	113	38	more	more	ADJ
ajst-20195	113	39	spectral	spectral	ADJ
ajst-20195	113	40	information	information	NOUN
ajst-20195	113	41	for	for	ADP
ajst-20195	113	42	analysis	analysis	NOUN
ajst-20195	113	43	and	and	CCONJ
ajst-20195	113	44	identification	identification	NOUN
ajst-20195	113	45	.	.	PUNCT
ajst-20195	114	1	at	at	ADP
ajst-20195	114	2	the	the	DET
ajst-20195	114	3	same	same	ADJ
ajst-20195	114	4	time	time	NOUN
ajst-20195	114	5	,	,	PUNCT
ajst-20195	114	6	the	the	DET
ajst-20195	114	7	b4	b4	NOUN
ajst-20195	114	8	band	band	NOUN
ajst-20195	114	9	may	may	AUX
ajst-20195	114	10	be	be	AUX
ajst-20195	114	11	affected	affect	VERB
ajst-20195	114	12	by	by	ADP
ajst-20195	114	13	atmospheric	atmospheric	ADJ
ajst-20195	114	14	influences	influence	NOUN
ajst-20195	114	15	,	,	PUNCT
ajst-20195	114	16	resulting	result	VERB
ajst-20195	114	17	in	in	ADP
ajst-20195	114	18	masked	mask	VERB
ajst-20195	114	19	or	or	CCONJ
ajst-20195	114	20	distorted	distorted	ADJ
ajst-20195	114	21	signals	signal	NOUN
ajst-20195	114	22	.	.	PUNCT
ajst-20195	115	1	the	the	DET
ajst-20195	115	2	use	use	NOUN
ajst-20195	115	3	of	of	ADP
ajst-20195	115	4	the	the	DET
ajst-20195	115	5	b5	b5	PROPN
ajst-20195	115	6	-	-	PUNCT
ajst-20195	115	7	b7	b7	PROPN
ajst-20195	115	8	bands	band	NOUN
ajst-20195	115	9	may	may	AUX
ajst-20195	115	10	reduce	reduce	VERB
ajst-20195	115	11	atmospheric	atmospheric	ADJ
ajst-20195	115	12	effects	effect	NOUN
ajst-20195	115	13	.	.	PUNCT
ajst-20195	116	1	figure	figure	VERB
ajst-20195	116	2	3	3	NUM
ajst-20195	116	3	.	.	PUNCT
ajst-20195	116	4	pls	pls	ADJ
ajst-20195	116	5	-	-	PUNCT
ajst-20195	116	6	vip	vip	NOUN
ajst-20195	116	7	calculation	calculation	NOUN
ajst-20195	116	8	result	result	VERB
ajst-20195	116	9	3.4	3.4	NUM
ajst-20195	116	10	.	.	PUNCT
ajst-20195	117	1	establishment	establishment	NOUN
ajst-20195	117	2	and	and	CCONJ
ajst-20195	117	3	comparison	comparison	NOUN
ajst-20195	117	4	of	of	ADP
ajst-20195	117	5	soil	soil	NOUN
ajst-20195	117	6	salinity	salinity	NOUN
ajst-20195	117	7	inversion	inversion	NOUN
ajst-20195	117	8	models	model	NOUN
ajst-20195	117	9	the	the	DET
ajst-20195	117	10	combination	combination	NOUN
ajst-20195	117	11	of	of	ADP
ajst-20195	117	12	spectral	spectral	ADJ
ajst-20195	117	13	variables	variable	NOUN
ajst-20195	117	14	determined	determine	VERB
ajst-20195	117	15	by	by	ADP
ajst-20195	117	16	the	the	DET
ajst-20195	117	17	screening	screening	NOUN
ajst-20195	117	18	method	method	NOUN
ajst-20195	117	19	based	base	VERB
ajst-20195	117	20	on	on	ADP
ajst-20195	117	21	the	the	DET
ajst-20195	117	22	pls	pls	ADJ
ajst-20195	117	23	-	-	PUNCT
ajst-20195	117	24	vip	vip	NOUN
ajst-20195	117	25	criterion	criterion	NOUN
ajst-20195	117	26	was	be	AUX
ajst-20195	117	27	used	use	VERB
ajst-20195	117	28	as	as	ADP
ajst-20195	117	29	the	the	DET
ajst-20195	117	30	input	input	NOUN
ajst-20195	117	31	independent	independent	ADJ
ajst-20195	117	32	variables	variable	NOUN
ajst-20195	117	33	,	,	PUNCT
ajst-20195	117	34	and	and	CCONJ
ajst-20195	117	35	the	the	DET
ajst-20195	117	36	corresponding	corresponding	ADJ
ajst-20195	117	37	inversion	inversion	NOUN
ajst-20195	117	38	models	model	NOUN
ajst-20195	117	39	were	be	AUX
ajst-20195	117	40	established	establish	VERB
ajst-20195	117	41	for	for	ADP
ajst-20195	117	42	the	the	DET
ajst-20195	117	43	measured	measure	VERB
ajst-20195	117	44	soil	soil	NOUN
ajst-20195	117	45	salinity	salinity	NOUN
ajst-20195	117	46	values	value	NOUN
ajst-20195	117	47	in	in	ADP
ajst-20195	117	48	spring	spring	NOUN
ajst-20195	117	49	and	and	CCONJ
ajst-20195	117	50	summer	summer	NOUN
ajst-20195	117	51	seasons	season	NOUN
ajst-20195	117	52	using	use	VERB
ajst-20195	117	53	three	three	NUM
ajst-20195	117	54	modelling	modelling	NOUN
ajst-20195	117	55	methods	method	NOUN
ajst-20195	117	56	,	,	PUNCT
ajst-20195	117	57	namely	namely	ADV
ajst-20195	117	58	rf	rf	ADJ
ajst-20195	117	59	,	,	PUNCT
ajst-20195	117	60	svm	svm	NOUN
ajst-20195	117	61	and	and	CCONJ
ajst-20195	117	62	elm	elm	PROPN
ajst-20195	117	63	.	.	PUNCT
ajst-20195	118	1	these	these	DET
ajst-20195	118	2	inverse	inverse	NOUN
ajst-20195	118	3	models	model	NOUN
ajst-20195	118	4	were	be	AUX
ajst-20195	118	5	comprehensively	comprehensively	ADV
ajst-20195	118	6	evaluated	evaluate	VERB
ajst-20195	118	7	and	and	CCONJ
ajst-20195	118	8	statistically	statistically	ADV
ajst-20195	118	9	analysed	analyse	VERB
ajst-20195	118	10	by	by	ADP
ajst-20195	118	11	comparing	compare	VERB
ajst-20195	118	12	the	the	DET
ajst-20195	118	13	predicted	predict	VERB
ajst-20195	118	14	values	value	NOUN
ajst-20195	118	15	of	of	ADP
ajst-20195	118	16	the	the	DET
ajst-20195	118	17	validation	validation	NOUN
ajst-20195	118	18	set	set	VERB
ajst-20195	118	19	with	with	ADP
ajst-20195	118	20	the	the	DET
ajst-20195	118	21	actual	actual	ADJ
ajst-20195	118	22	soil	soil	NOUN
ajst-20195	118	23	salinity	salinity	NOUN
ajst-20195	118	24	,	,	PUNCT
ajst-20195	118	25	and	and	CCONJ
ajst-20195	118	26	the	the	DET
ajst-20195	118	27	results	result	NOUN
ajst-20195	118	28	are	be	AUX
ajst-20195	118	29	displayed	display	VERB
ajst-20195	118	30	in	in	ADP
ajst-20195	118	31	fig.4	fig.4	PROPN
ajst-20195	118	32	.	.	PUNCT
ajst-20195	119	1	from	from	ADP
ajst-20195	119	2	the	the	DET
ajst-20195	119	3	figure	figure	NOUN
ajst-20195	119	4	,	,	PUNCT
ajst-20195	119	5	it	it	PRON
ajst-20195	119	6	can	can	AUX
ajst-20195	119	7	be	be	AUX
ajst-20195	119	8	seen	see	VERB
ajst-20195	119	9	that	that	SCONJ
ajst-20195	119	10	most	most	ADJ
ajst-20195	119	11	of	of	ADP
ajst-20195	119	12	the	the	DET
ajst-20195	119	13	models	model	NOUN
ajst-20195	119	14	have	have	VERB
ajst-20195	119	15	good	good	ADJ
ajst-20195	119	16	stability	stability	NOUN
ajst-20195	119	17	when	when	SCONJ
ajst-20195	119	18	it	it	PRON
ajst-20195	119	19	comes	come	VERB
ajst-20195	119	20	to	to	ADP
ajst-20195	119	21	the	the	DET
ajst-20195	119	22	processed	process	VERB
ajst-20195	119	23	soil	soil	NOUN
ajst-20195	119	24	inversion	inversion	NOUN
ajst-20195	119	25	models	model	NOUN
ajst-20195	119	26	,	,	PUNCT
ajst-20195	119	27	and	and	CCONJ
ajst-20195	119	28	their	their	PRON
ajst-20195	119	29	coefficients	coefficient	NOUN
ajst-20195	119	30	of	of	ADP
ajst-20195	119	31	determination	determination	NOUN
ajst-20195	119	32	,	,	PUNCT
ajst-20195	119	33	r2	r2	PROPN
ajst-20195	119	34	,	,	PUNCT
ajst-20195	119	35	are	be	AUX
ajst-20195	119	36	within	within	ADP
ajst-20195	119	37	a	a	DET
ajst-20195	119	38	reasonable	reasonable	ADJ
ajst-20195	119	39	range	range	NOUN
ajst-20195	119	40	from	from	ADP
ajst-20195	119	41	the	the	DET
ajst-20195	119	42	perspective	perspective	NOUN
ajst-20195	119	43	of	of	ADP
ajst-20195	119	44	the	the	DET
ajst-20195	119	45	three	three	NUM
ajst-20195	119	46	depths	depth	NOUN
ajst-20195	119	47	,	,	PUNCT
ajst-20195	119	48	among	among	ADP
ajst-20195	119	49	the	the	DET
ajst-20195	119	50	inversion	inversion	NOUN
ajst-20195	119	51	models	model	NOUN
ajst-20195	119	52	of	of	ADP
ajst-20195	119	53	soil	soil	NOUN
ajst-20195	119	54	salinity	salinity	NOUN
ajst-20195	119	55	established	establish	VERB
ajst-20195	119	56	by	by	ADP
ajst-20195	119	57	spectral	spectral	ADJ
ajst-20195	119	58	covariates	covariate	NOUN
ajst-20195	119	59	screened	screen	VERB
ajst-20195	119	60	by	by	ADP
ajst-20195	119	61	the	the	DET
ajst-20195	119	62	screening	screening	NOUN
ajst-20195	119	63	method	method	NOUN
ajst-20195	119	64	based	base	VERB
ajst-20195	119	65	on	on	ADP
ajst-20195	119	66	the	the	DET
ajst-20195	119	67	pls	pls	ADJ
ajst-20195	119	68	-	-	PUNCT
ajst-20195	119	69	vip	vip	NOUN
ajst-20195	119	70	criterion	criterion	NOUN
ajst-20195	119	71	,	,	PUNCT
ajst-20195	119	72	the	the	DET
ajst-20195	119	73	rf	rf	NOUN
ajst-20195	119	74	model	model	NOUN
ajst-20195	119	75	has	have	VERB
ajst-20195	119	76	the	the	DET
ajst-20195	119	77	highest	high	ADJ
ajst-20195	119	78	inversion	inversion	NOUN
ajst-20195	119	79	accuracy	accuracy	NOUN
ajst-20195	119	80	,	,	PUNCT
ajst-20195	119	81	followed	follow	VERB
ajst-20195	119	82	by	by	ADP
ajst-20195	119	83	the	the	DET
ajst-20195	119	84	104	104	NUM
ajst-20195	119	85	svm	svm	PROPN
ajst-20195	119	86	model	model	NOUN
ajst-20195	119	87	,	,	PUNCT
ajst-20195	119	88	while	while	SCONJ
ajst-20195	119	89	the	the	DET
ajst-20195	119	90	elm	elm	NOUN
ajst-20195	119	91	model	model	NOUN
ajst-20195	119	92	performs	perform	VERB
ajst-20195	119	93	the	the	DET
ajst-20195	119	94	worst	bad	ADJ
ajst-20195	119	95	.	.	PUNCT
ajst-20195	120	1	in	in	ADP
ajst-20195	120	2	addition	addition	NOUN
ajst-20195	120	3	,	,	PUNCT
ajst-20195	120	4	the	the	DET
ajst-20195	120	5	accuracy	accuracy	NOUN
ajst-20195	120	6	of	of	ADP
ajst-20195	120	7	these	these	DET
ajst-20195	120	8	models	model	NOUN
ajst-20195	120	9	was	be	AUX
ajst-20195	120	10	significantly	significantly	ADV
ajst-20195	120	11	higher	high	ADJ
ajst-20195	120	12	in	in	ADP
ajst-20195	120	13	spring	spring	NOUN
ajst-20195	120	14	than	than	ADP
ajst-20195	120	15	in	in	ADP
ajst-20195	120	16	summer	summer	NOUN
ajst-20195	120	17	.	.	PUNCT
ajst-20195	121	1	the	the	DET
ajst-20195	121	2	possible	possible	ADJ
ajst-20195	121	3	reason	reason	NOUN
ajst-20195	121	4	for	for	ADP
ajst-20195	121	5	this	this	PRON
ajst-20195	121	6	is	be	AUX
ajst-20195	121	7	that	that	SCONJ
ajst-20195	121	8	there	there	PRON
ajst-20195	121	9	is	be	VERB
ajst-20195	121	10	mainly	mainly	ADV
ajst-20195	121	11	vegetation	vegetation	NOUN
ajst-20195	121	12	cover	cover	NOUN
ajst-20195	121	13	in	in	ADP
ajst-20195	121	14	summer	summer	NOUN
ajst-20195	121	15	,	,	PUNCT
ajst-20195	121	16	which	which	PRON
ajst-20195	121	17	causes	cause	VERB
ajst-20195	121	18	a	a	DET
ajst-20195	121	19	decrease	decrease	NOUN
ajst-20195	121	20	in	in	ADP
ajst-20195	121	21	the	the	DET
ajst-20195	121	22	accuracy	accuracy	NOUN
ajst-20195	121	23	of	of	ADP
ajst-20195	121	24	the	the	DET
ajst-20195	121	25	models	model	NOUN
ajst-20195	121	26	.	.	PUNCT
ajst-20195	122	1	comparing	compare	VERB
ajst-20195	122	2	the	the	DET
ajst-20195	122	3	three	three	NUM
ajst-20195	122	4	inversion	inversion	NOUN
ajst-20195	122	5	models	model	NOUN
ajst-20195	122	6	together	together	ADV
ajst-20195	122	7	,	,	PUNCT
ajst-20195	122	8	it	it	PRON
ajst-20195	122	9	can	can	AUX
ajst-20195	122	10	be	be	AUX
ajst-20195	122	11	concluded	conclude	VERB
ajst-20195	122	12	that	that	SCONJ
ajst-20195	122	13	the	the	DET
ajst-20195	122	14	random	random	ADJ
ajst-20195	122	15	forest	forest	NOUN
ajst-20195	122	16	model	model	NOUN
ajst-20195	122	17	screened	screen	VERB
ajst-20195	122	18	based	base	VERB
ajst-20195	122	19	on	on	ADP
ajst-20195	122	20	the	the	DET
ajst-20195	122	21	pls	pls	ADJ
ajst-20195	122	22	-	-	PUNCT
ajst-20195	122	23	vip	vip	NOUN
ajst-20195	122	24	criterion	criterion	NOUN
ajst-20195	122	25	shows	show	VERB
ajst-20195	122	26	better	well	ADJ
ajst-20195	122	27	results	result	NOUN
ajst-20195	122	28	both	both	CCONJ
ajst-20195	122	29	in	in	ADP
ajst-20195	122	30	spring	spring	NOUN
ajst-20195	122	31	and	and	CCONJ
ajst-20195	122	32	in	in	ADP
ajst-20195	122	33	summer	summer	NOUN
ajst-20195	122	34	.	.	PUNCT
ajst-20195	123	1	therefore	therefore	ADV
ajst-20195	123	2	,	,	PUNCT
ajst-20195	123	3	for	for	ADP
ajst-20195	123	4	the	the	DET
ajst-20195	123	5	sentinel-2	sentinel-2	NUM
ajst-20195	123	6	satellite	satellite	NOUN
ajst-20195	123	7	remote	remote	ADJ
ajst-20195	123	8	sensing	sensing	NOUN
ajst-20195	123	9	images	image	NOUN
ajst-20195	123	10	during	during	ADP
ajst-20195	123	11	the	the	DET
ajst-20195	123	12	whole	whole	ADJ
ajst-20195	123	13	spring	spring	NOUN
ajst-20195	123	14	and	and	CCONJ
ajst-20195	123	15	summer	summer	NOUN
ajst-20195	123	16	seasons	season	NOUN
ajst-20195	123	17	,	,	PUNCT
ajst-20195	123	18	the	the	DET
ajst-20195	123	19	screening	screening	NOUN
ajst-20195	123	20	method	method	NOUN
ajst-20195	123	21	based	base	VERB
ajst-20195	123	22	on	on	ADP
ajst-20195	123	23	the	the	DET
ajst-20195	123	24	pls	pls	ADJ
ajst-20195	123	25	-	-	PUNCT
ajst-20195	123	26	vip	vip	NOUN
ajst-20195	123	27	criterion	criterion	NOUN
ajst-20195	123	28	was	be	AUX
ajst-20195	123	29	used	use	VERB
ajst-20195	123	30	to	to	PART
ajst-20195	123	31	determine	determine	VERB
ajst-20195	123	32	the	the	DET
ajst-20195	123	33	combination	combination	NOUN
ajst-20195	123	34	of	of	ADP
ajst-20195	123	35	spectral	spectral	ADJ
ajst-20195	123	36	variables	variable	NOUN
ajst-20195	123	37	in	in	ADP
ajst-20195	123	38	the	the	DET
ajst-20195	123	39	spring	spring	NOUN
ajst-20195	123	40	and	and	CCONJ
ajst-20195	123	41	summer	summer	NOUN
ajst-20195	123	42	seasons	season	NOUN
ajst-20195	123	43	and	and	CCONJ
ajst-20195	123	44	to	to	PART
ajst-20195	123	45	establish	establish	VERB
ajst-20195	123	46	the	the	DET
ajst-20195	123	47	rf	rf	NOUN
ajst-20195	123	48	-	-	PUNCT
ajst-20195	123	49	based	base	VERB
ajst-20195	123	50	inversion	inversion	NOUN
ajst-20195	123	51	model	model	NOUN
ajst-20195	123	52	for	for	ADP
ajst-20195	123	53	soil	soil	NOUN
ajst-20195	123	54	salinity	salinity	NOUN
ajst-20195	123	55	.	.	PUNCT
ajst-20195	124	1	the	the	DET
ajst-20195	124	2	inversion	inversion	NOUN
ajst-20195	124	3	effect	effect	NOUN
ajst-20195	124	4	is	be	AUX
ajst-20195	124	5	shown	show	VERB
ajst-20195	124	6	in	in	ADP
ajst-20195	124	7	fig	fig	NOUN
ajst-20195	124	8	.	.	PUNCT
ajst-20195	125	1	5	5	NUM
ajst-20195	125	2	.	.	X
ajst-20195	125	3	as	as	SCONJ
ajst-20195	125	4	can	can	AUX
ajst-20195	125	5	be	be	AUX
ajst-20195	125	6	seen	see	VERB
ajst-20195	125	7	from	from	ADP
ajst-20195	125	8	fig	fig	NOUN
ajst-20195	125	9	.	.	PUNCT
ajst-20195	126	1	5	5	NUM
ajst-20195	126	2	,	,	PUNCT
ajst-20195	126	3	within	within	ADP
ajst-20195	126	4	the	the	DET
ajst-20195	126	5	four	four	NUM
ajst-20195	126	6	months	month	NOUN
ajst-20195	126	7	,	,	PUNCT
ajst-20195	126	8	the	the	DET
ajst-20195	126	9	rfbased	rfbased	ADJ
ajst-20195	126	10	model	model	NOUN
ajst-20195	126	11	has	have	VERB
ajst-20195	126	12	a	a	DET
ajst-20195	126	13	deep	deep	ADJ
ajst-20195	126	14	inversion	inversion	NOUN
ajst-20195	126	15	accuracy	accuracy	NOUN
ajst-20195	126	16	,	,	PUNCT
ajst-20195	126	17	the	the	DET
ajst-20195	126	18	r2	r2	NOUN
ajst-20195	126	19	of	of	ADP
ajst-20195	126	20	the	the	DET
ajst-20195	126	21	validation	validation	NOUN
ajst-20195	126	22	set	set	NOUN
ajst-20195	126	23	is	be	AUX
ajst-20195	126	24	between	between	ADP
ajst-20195	126	25	0.641	0.641	NUM
ajst-20195	126	26	and	and	CCONJ
ajst-20195	126	27	0.825	0.825	NUM
ajst-20195	126	28	,	,	PUNCT
ajst-20195	126	29	with	with	ADP
ajst-20195	126	30	a	a	DET
ajst-20195	126	31	better	well	ADV
ajst-20195	126	32	fitting	fitting	ADJ
ajst-20195	126	33	ability	ability	NOUN
ajst-20195	126	34	,	,	PUNCT
ajst-20195	126	35	and	and	CCONJ
ajst-20195	126	36	the	the	DET
ajst-20195	126	37	re	re	NOUN
ajst-20195	126	38	is	be	AUX
ajst-20195	126	39	between	between	ADP
ajst-20195	126	40	0.197	0.197	NUM
ajst-20195	126	41	and	and	CCONJ
ajst-20195	126	42	0.319	0.319	NUM
ajst-20195	126	43	,	,	PUNCT
ajst-20195	126	44	with	with	ADP
ajst-20195	126	45	a	a	DET
ajst-20195	126	46	smaller	small	ADJ
ajst-20195	126	47	model	model	NOUN
ajst-20195	126	48	error	error	NOUN
ajst-20195	126	49	,	,	PUNCT
ajst-20195	126	50	and	and	CCONJ
ajst-20195	126	51	the	the	DET
ajst-20195	126	52	inversion	inversion	NOUN
ajst-20195	126	53	accuracy	accuracy	NOUN
ajst-20195	126	54	of	of	ADP
ajst-20195	126	55	the	the	DET
ajst-20195	126	56	model	model	NOUN
ajst-20195	126	57	is	be	AUX
ajst-20195	126	58	high	high	ADJ
ajst-20195	126	59	.	.	PUNCT
ajst-20195	127	1	figure	figure	NOUN
ajst-20195	127	2	5	5	NUM
ajst-20195	127	3	.	.	PUNCT
ajst-20195	127	4	predictive	predictive	ADJ
ajst-20195	127	5	performance	performance	NOUN
ajst-20195	127	6	of	of	ADP
ajst-20195	127	7	the	the	DET
ajst-20195	127	8	model	model	NOUN
ajst-20195	127	9	in	in	ADP
ajst-20195	127	10	the	the	DET
ajst-20195	127	11	study	study	NOUN
ajst-20195	127	12	,	,	PUNCT
ajst-20195	127	13	variables	variable	NOUN
ajst-20195	127	14	with	with	ADP
ajst-20195	127	15	results	result	NOUN
ajst-20195	127	16	greater	great	ADJ
ajst-20195	127	17	than	than	ADP
ajst-20195	127	18	1	1	NUM
ajst-20195	127	19	obtained	obtain	VERB
ajst-20195	127	20	through	through	ADP
ajst-20195	127	21	pls	pls	ADJ
ajst-20195	127	22	-	-	PUNCT
ajst-20195	127	23	vip	vip	NOUN
ajst-20195	127	24	calculations	calculation	NOUN
ajst-20195	127	25	were	be	AUX
ajst-20195	127	26	considered	consider	VERB
ajst-20195	127	27	as	as	ADP
ajst-20195	127	28	variables	variable	NOUN
ajst-20195	127	29	important	important	ADJ
ajst-20195	127	30	to	to	ADP
ajst-20195	127	31	the	the	DET
ajst-20195	127	32	measured	measure	VERB
ajst-20195	127	33	soil	soil	NOUN
ajst-20195	127	34	salinity	salinity	NOUN
ajst-20195	127	35	and	and	CCONJ
ajst-20195	127	36	were	be	AUX
ajst-20195	127	37	used	use	VERB
ajst-20195	127	38	as	as	ADP
ajst-20195	127	39	independent	independent	ADJ
ajst-20195	127	40	variables	variable	NOUN
ajst-20195	127	41	in	in	ADP
ajst-20195	127	42	the	the	DET
ajst-20195	127	43	satellite	satellite	NOUN
ajst-20195	127	44	remote	remote	ADJ
ajst-20195	127	45	sensing	sense	VERB
ajst-20195	127	46	inversion	inversion	NOUN
ajst-20195	127	47	model	model	NOUN
ajst-20195	127	48	.	.	PUNCT
ajst-20195	128	1	sampling	sample	VERB
ajst-20195	128	2	random	random	ADJ
ajst-20195	128	3	forest	forest	NOUN
ajst-20195	128	4	(	(	PUNCT
ajst-20195	128	5	rf	rf	NOUN
ajst-20195	128	6	)	)	PUNCT
ajst-20195	128	7	for	for	ADP
ajst-20195	128	8	model	model	NOUN
ajst-20195	128	9	building	building	NOUN
ajst-20195	128	10	and	and	CCONJ
ajst-20195	128	11	inversion	inversion	NOUN
ajst-20195	128	12	of	of	ADP
ajst-20195	128	13	soil	soil	NOUN
ajst-20195	128	14	salinity	salinity	NOUN
ajst-20195	128	15	using	use	VERB
ajst-20195	128	16	the	the	DET
ajst-20195	128	17	trained	train	VERB
ajst-20195	128	18	model	model	NOUN
ajst-20195	128	19	,	,	PUNCT
ajst-20195	128	20	soil	soil	NOUN
ajst-20195	128	21	salinity	salinity	NOUN
ajst-20195	128	22	values	value	NOUN
ajst-20195	128	23	were	be	AUX
ajst-20195	128	24	calculated	calculate	VERB
ajst-20195	128	25	for	for	ADP
ajst-20195	128	26	each	each	DET
ajst-20195	128	27	image	image	NOUN
ajst-20195	128	28	element	element	NOUN
ajst-20195	128	29	in	in	ADP
ajst-20195	128	30	the	the	DET
ajst-20195	128	31	study	study	NOUN
ajst-20195	128	32	area	area	NOUN
ajst-20195	128	33	and	and	CCONJ
ajst-20195	128	34	spatial	spatial	ADJ
ajst-20195	128	35	distribution	distribution	NOUN
ajst-20195	128	36	map	map	NOUN
ajst-20195	128	37	of	of	ADP
ajst-20195	128	38	soil	soil	NOUN
ajst-20195	128	39	salinity	salinity	NOUN
ajst-20195	128	40	was	be	AUX
ajst-20195	128	41	generated	generate	VERB
ajst-20195	128	42	as	as	SCONJ
ajst-20195	128	43	shown	show	VERB
ajst-20195	128	44	in	in	ADP
ajst-20195	128	45	fig	fig	NOUN
ajst-20195	128	46	.	.	PUNCT
ajst-20195	129	1	6	6	NUM
ajst-20195	129	2	.	.	PUNCT
ajst-20195	129	3	the	the	DET
ajst-20195	129	4	mean	mean	ADJ
ajst-20195	129	5	value	value	NOUN
ajst-20195	129	6	of	of	ADP
ajst-20195	129	7	soil	soil	NOUN
ajst-20195	129	8	salinity	salinity	NOUN
ajst-20195	129	9	was	be	AUX
ajst-20195	129	10	found	find	VERB
ajst-20195	129	11	to	to	PART
ajst-20195	129	12	be	be	AUX
ajst-20195	129	13	4.855	4.855	NUM
ajst-20195	129	14	g	g	NOUN
ajst-20195	129	15	/	/	SYM
ajst-20195	129	16	kg	kg	NOUN
ajst-20195	129	17	in	in	ADP
ajst-20195	129	18	spring	spring	NOUN
ajst-20195	129	19	and	and	CCONJ
ajst-20195	129	20	2.548	2.548	NUM
ajst-20195	129	21	g	g	NOUN
ajst-20195	129	22	/	/	SYM
ajst-20195	129	23	kg	kg	NOUN
ajst-20195	129	24	in	in	ADP
ajst-20195	129	25	summer.most	summer.most	NOUN
ajst-20195	129	26	of	of	ADP
ajst-20195	129	27	the	the	DET
ajst-20195	129	28	study	study	NOUN
ajst-20195	129	29	area	area	NOUN
ajst-20195	129	30	is	be	AUX
ajst-20195	129	31	moderately	moderately	ADV
ajst-20195	129	32	salinised	salinise	VERB
ajst-20195	129	33	land	land	NOUN
ajst-20195	129	34	and	and	CCONJ
ajst-20195	129	35	a	a	DET
ajst-20195	129	36	small	small	ADJ
ajst-20195	129	37	portion	portion	NOUN
ajst-20195	129	38	of	of	ADP
ajst-20195	129	39	heavily	heavily	ADV
ajst-20195	129	40	salinised	salinise	VERB
ajst-20195	129	41	land	land	NOUN
ajst-20195	129	42	.	.	PUNCT
ajst-20195	130	1	this	this	PRON
ajst-20195	130	2	is	be	AUX
ajst-20195	130	3	in	in	ADP
ajst-20195	130	4	general	general	ADJ
ajst-20195	130	5	agreement	agreement	NOUN
ajst-20195	130	6	with	with	ADP
ajst-20195	130	7	the	the	DET
ajst-20195	130	8	findings	finding	NOUN
ajst-20195	130	9	of	of	ADP
ajst-20195	130	10	jia	jia	PROPN
ajst-20195	130	11	zhuangzhuang[14	zhuangzhuang[14	PROPN
ajst-20195	130	12	]	]	PUNCT
ajst-20195	130	13	in	in	ADP
ajst-20195	130	14	2023	2023	NUM
ajst-20195	130	15	.	.	PUNCT
ajst-20195	131	1	the	the	DET
ajst-20195	131	2	main	main	ADJ
ajst-20195	131	3	causes	cause	NOUN
ajst-20195	131	4	of	of	ADP
ajst-20195	131	5	salinisation	salinisation	NOUN
ajst-20195	131	6	in	in	ADP
ajst-20195	131	7	this	this	DET
ajst-20195	131	8	area	area	NOUN
ajst-20195	131	9	are	be	AUX
ajst-20195	131	10	as	as	SCONJ
ajst-20195	131	11	follows	follow	VERB
ajst-20195	131	12	:	:	PUNCT
ajst-20195	131	13	firstly	firstly	ADV
ajst-20195	131	14	,	,	PUNCT
ajst-20195	131	15	the	the	DET
ajst-20195	131	16	topographic	topographic	ADJ
ajst-20195	131	17	conditions	condition	NOUN
ajst-20195	131	18	make	make	VERB
ajst-20195	131	19	it	it	PRON
ajst-20195	131	20	downstream	downstream	ADJ
ajst-20195	131	21	of	of	ADP
ajst-20195	131	22	the	the	DET
ajst-20195	131	23	irrigation	irrigation	NOUN
ajst-20195	131	24	area	area	NOUN
ajst-20195	131	25	,	,	PUNCT
ajst-20195	131	26	while	while	SCONJ
ajst-20195	131	27	pooling	pool	VERB
ajst-20195	131	28	drainage	drainage	NOUN
ajst-20195	131	29	and	and	CCONJ
ajst-20195	131	30	salt	salt	NOUN
ajst-20195	131	31	removal	removal	NOUN
ajst-20195	131	32	from	from	ADP
ajst-20195	131	33	upstream	upstream	ADJ
ajst-20195	131	34	,	,	PUNCT
ajst-20195	131	35	and	and	CCONJ
ajst-20195	131	36	the	the	DET
ajst-20195	131	37	relatively	relatively	ADV
ajst-20195	131	38	low	low	ADJ
ajst-20195	131	39	-	-	PUNCT
ajst-20195	131	40	lying	lie	VERB
ajst-20195	131	41	areas	area	NOUN
ajst-20195	131	42	of	of	ADP
ajst-20195	131	43	the	the	DET
ajst-20195	131	44	helan	helan	PROPN
ajst-20195	131	45	mountain	mountain	PROPN
ajst-20195	131	46	hilly	hilly	ADV
ajst-20195	131	47	land	land	NOUN
ajst-20195	131	48	and	and	CCONJ
ajst-20195	131	49	areas	area	NOUN
ajst-20195	131	50	along	along	ADP
ajst-20195	131	51	the	the	DET
ajst-20195	131	52	yellow	yellow	PROPN
ajst-20195	131	53	river	river	NOUN
ajst-20195	131	54	,	,	PUNCT
ajst-20195	131	55	where	where	SCONJ
ajst-20195	131	56	the	the	DET
ajst-20195	131	57	water	water	NOUN
ajst-20195	131	58	flow	flow	NOUN
ajst-20195	131	59	pooling	pooling	NOUN
ajst-20195	131	60	and	and	CCONJ
ajst-20195	131	61	drainage	drainage	NOUN
ajst-20195	131	62	are	be	AUX
ajst-20195	131	63	obstructed	obstruct	VERB
ajst-20195	131	64	,	,	PUNCT
ajst-20195	131	65	leading	lead	VERB
ajst-20195	131	66	to	to	ADP
ajst-20195	131	67	the	the	DET
ajst-20195	131	68	formation	formation	NOUN
ajst-20195	131	69	of	of	ADP
ajst-20195	131	70	moderately	moderately	ADV
ajst-20195	131	71	and	and	CCONJ
ajst-20195	131	72	heavily	heavily	ADV
ajst-20195	131	73	saline	saline	ADJ
ajst-20195	131	74	land	land	NOUN
ajst-20195	131	75	.	.	PUNCT
ajst-20195	132	1	secondly	secondly	ADV
ajst-20195	132	2	,	,	PUNCT
ajst-20195	132	3	soil	soil	NOUN
ajst-20195	132	4	characteristics	characteristic	NOUN
ajst-20195	132	5	are	be	AUX
ajst-20195	132	6	also	also	ADV
ajst-20195	132	7	a	a	DET
ajst-20195	132	8	key	key	ADJ
ajst-20195	132	9	factor	factor	NOUN
ajst-20195	132	10	.	.	PUNCT
ajst-20195	133	1	the	the	DET
ajst-20195	133	2	soils	soil	NOUN
ajst-20195	133	3	around	around	ADP
ajst-20195	133	4	yanzidun	yanzidun	PROPN
ajst-20195	133	5	township	township	PROPN
ajst-20195	133	6	and	and	CCONJ
ajst-20195	133	7	lihe	lihe	PROPN
ajst-20195	133	8	township	township	NOUN
ajst-20195	133	9	are	be	AUX
ajst-20195	133	10	sticky	sticky	ADJ
ajst-20195	133	11	and	and	CCONJ
ajst-20195	133	12	heavy	heavy	ADJ
ajst-20195	133	13	,	,	PUNCT
ajst-20195	133	14	with	with	ADP
ajst-20195	133	15	poor	poor	ADJ
ajst-20195	133	16	infiltration	infiltration	NOUN
ajst-20195	133	17	properties	property	NOUN
ajst-20195	133	18	,	,	PUNCT
ajst-20195	133	19	and	and	CCONJ
ajst-20195	133	20	the	the	DET
ajst-20195	133	21	lateral	lateral	ADJ
ajst-20195	133	22	flow	flow	NOUN
ajst-20195	133	23	of	of	ADP
ajst-20195	133	24	groundwater	groundwater	NOUN
ajst-20195	133	25	is	be	AUX
ajst-20195	133	26	difficult	difficult	ADJ
ajst-20195	133	27	,	,	PUNCT
ajst-20195	133	28	resulting	result	VERB
ajst-20195	133	29	in	in	ADP
ajst-20195	133	30	the	the	DET
ajst-20195	133	31	formation	formation	NOUN
ajst-20195	133	32	of	of	ADP
ajst-20195	133	33	partially	partially	ADV
ajst-20195	133	34	alkaline	alkaline	NOUN
ajst-20195	133	35	soils	soil	NOUN
ajst-20195	133	36	.	.	PUNCT
ajst-20195	134	1	in	in	ADP
ajst-20195	134	2	addition	addition	NOUN
ajst-20195	134	3	,	,	PUNCT
ajst-20195	134	4	soil	soil	NOUN
ajst-20195	134	5	salinity	salinity	NOUN
ajst-20195	134	6	in	in	ADP
ajst-20195	134	7	huinong	huinong	PROPN
ajst-20195	134	8	district	district	NOUN
ajst-20195	134	9	ranges	range	VERB
ajst-20195	134	10	from	from	ADP
ajst-20195	134	11	1.78	1.78	NUM
ajst-20195	134	12	to	to	ADP
ajst-20195	134	13	5.60	5.60	NUM
ajst-20195	134	14	g	g	NOUN
ajst-20195	134	15	/	/	SYM
ajst-20195	134	16	kg[15	kg[15	PROPN
ajst-20195	134	17	]	]	PUNCT
ajst-20195	134	18	,	,	PUNCT
ajst-20195	134	19	with	with	ADP
ajst-20195	134	20	mildly	mildly	ADV
ajst-20195	134	21	saline	saline	ADJ
ajst-20195	134	22	soils	soil	NOUN
ajst-20195	134	23	occupying	occupy	VERB
ajst-20195	134	24	62	62	NUM
ajst-20195	134	25	%	%	NOUN
ajst-20195	134	26	of	of	ADP
ajst-20195	134	27	the	the	DET
ajst-20195	134	28	total	total	ADJ
ajst-20195	134	29	saline	saline	NOUN
ajst-20195	134	30	area	area	NOUN
ajst-20195	134	31	.	.	PUNCT
ajst-20195	135	1	secondly	secondly	ADV
ajst-20195	135	2	,	,	PUNCT
ajst-20195	135	3	the	the	DET
ajst-20195	135	4	groundwater	groundwater	NOUN
ajst-20195	135	5	table	table	NOUN
ajst-20195	135	6	is	be	AUX
ajst-20195	135	7	shallow	shallow	ADJ
ajst-20195	135	8	and	and	CCONJ
ajst-20195	135	9	affected	affect	VERB
ajst-20195	135	10	by	by	ADP
ajst-20195	135	11	the	the	DET
ajst-20195	135	12	top	top	ADJ
ajst-20195	135	13	support	support	NOUN
ajst-20195	135	14	of	of	ADP
ajst-20195	135	15	the	the	DET
ajst-20195	135	16	yellow	yellow	PROPN
ajst-20195	135	17	river	river	NOUN
ajst-20195	135	18	water	water	NOUN
ajst-20195	135	19	,	,	PUNCT
ajst-20195	135	20	with	with	ADP
ajst-20195	135	21	high	high	ADJ
ajst-20195	135	22	mineralisation	mineralisation	NOUN
ajst-20195	135	23	and	and	CCONJ
ajst-20195	135	24	widespread	widespread	ADJ
ajst-20195	135	25	salt	salt	NOUN
ajst-20195	135	26	return	return	NOUN
ajst-20195	135	27	.	.	PUNCT
ajst-20195	136	1	yellow	yellow	ADJ
ajst-20195	136	2	river	river	NOUN
ajst-20195	136	3	water	water	NOUN
ajst-20195	136	4	breaks	break	NOUN
ajst-20195	136	5	or	or	CCONJ
ajst-20195	136	6	excessive	excessive	ADJ
ajst-20195	136	7	upstream	upstream	ADJ
ajst-20195	136	8	water	water	NOUN
ajst-20195	136	9	consumption	consumption	NOUN
ajst-20195	136	10	leads	lead	VERB
ajst-20195	136	11	to	to	ADP
ajst-20195	136	12	insufficient	insufficient	ADJ
ajst-20195	136	13	downstream	downstream	ADJ
ajst-20195	136	14	irrigation	irrigation	NOUN
ajst-20195	136	15	water	water	NOUN
ajst-20195	136	16	,	,	PUNCT
ajst-20195	136	17	which	which	PRON
ajst-20195	136	18	affects	affect	VERB
ajst-20195	136	19	the	the	DET
ajst-20195	136	20	salt	salt	NOUN
ajst-20195	136	21	discharge	discharge	NOUN
ajst-20195	136	22	from	from	ADP
ajst-20195	136	23	the	the	DET
ajst-20195	136	24	arable	arable	ADJ
ajst-20195	136	25	land	land	NOUN
ajst-20195	136	26	and	and	CCONJ
ajst-20195	136	27	also	also	ADV
ajst-20195	136	28	creates	create	VERB
ajst-20195	136	29	poor	poor	ADJ
ajst-20195	136	30	drainage	drainage	NOUN
ajst-20195	136	31	problems	problem	NOUN
ajst-20195	136	32	.	.	PUNCT
ajst-20195	137	1	4	4	X
ajst-20195	137	2	.	.	X
ajst-20195	137	3	conclusion	conclusion	NOUN
ajst-20195	137	4	in	in	ADP
ajst-20195	137	5	this	this	DET
ajst-20195	137	6	study	study	NOUN
ajst-20195	137	7	,	,	PUNCT
ajst-20195	137	8	the	the	DET
ajst-20195	137	9	fitted	fit	VERB
ajst-20195	137	10	relationships	relationship	NOUN
ajst-20195	137	11	between	between	ADP
ajst-20195	137	12	bands	band	NOUN
ajst-20195	137	13	and	and	CCONJ
ajst-20195	137	14	salinity	salinity	NOUN
ajst-20195	137	15	indices	index	NOUN
ajst-20195	137	16	and	and	CCONJ
ajst-20195	137	17	soil	soil	NOUN
ajst-20195	137	18	salinity	salinity	NOUN
ajst-20195	137	19	were	be	AUX
ajst-20195	137	20	explored	explore	VERB
ajst-20195	137	21	using	use	VERB
ajst-20195	137	22	field	field	NOUN
ajst-20195	137	23	sampling	sample	VERB
ajst-20195	137	24	data	datum	NOUN
ajst-20195	137	25	and	and	CCONJ
ajst-20195	137	26	sentinel-2	sentinel-2	ADJ
ajst-20195	137	27	data	datum	NOUN
ajst-20195	137	28	.	.	PUNCT
ajst-20195	138	1	considering	consider	VERB
ajst-20195	138	2	the	the	DET
ajst-20195	138	3	new	new	ADJ
ajst-20195	138	4	spectral	spectral	ADJ
ajst-20195	138	5	functions	function	NOUN
ajst-20195	138	6	of	of	ADP
ajst-20195	138	7	three	three	NUM
ajst-20195	138	8	additional	additional	ADJ
ajst-20195	138	9	red	red	ADJ
ajst-20195	138	10	-	-	PUNCT
ajst-20195	138	11	edge	edge	NOUN
ajst-20195	138	12	bands	band	NOUN
ajst-20195	138	13	,	,	PUNCT
ajst-20195	138	14	three	three	NUM
ajst-20195	138	15	bands	band	NOUN
ajst-20195	138	16	(	(	PUNCT
ajst-20195	138	17	b5	b5	PROPN
ajst-20195	138	18	-	-	PUNCT
ajst-20195	138	19	b7	b7	PROPN
ajst-20195	138	20	)	)	PUNCT
ajst-20195	138	21	were	be	AUX
ajst-20195	138	22	used	use	VERB
ajst-20195	138	23	instead	instead	ADV
ajst-20195	138	24	of	of	ADP
ajst-20195	138	25	b4	b4	NOUN
ajst-20195	138	26	,	,	PUNCT
ajst-20195	138	27	and	and	CCONJ
ajst-20195	138	28	various	various	ADJ
ajst-20195	138	29	possible	possible	ADJ
ajst-20195	138	30	combinations	combination	NOUN
ajst-20195	138	31	of	of	ADP
ajst-20195	138	32	these	these	DET
ajst-20195	138	33	new	new	ADJ
ajst-20195	138	34	red	red	ADJ
ajst-20195	138	35	-	-	PUNCT
ajst-20195	138	36	edge	edge	NOUN
ajst-20195	138	37	bands	band	NOUN
ajst-20195	138	38	were	be	AUX
ajst-20195	138	39	calculated	calculate	VERB
ajst-20195	138	40	to	to	PART
ajst-20195	138	41	generate	generate	VERB
ajst-20195	138	42	potential	potential	ADJ
ajst-20195	138	43	soil	soil	NOUN
ajst-20195	138	44	salinity	salinity	NOUN
ajst-20195	138	45	indices	indice	VERB
ajst-20195	138	46	for	for	ADP
ajst-20195	138	47	estimating	estimate	VERB
ajst-20195	138	48	conductivity	conductivity	NOUN
ajst-20195	138	49	.	.	PUNCT
ajst-20195	139	1	the	the	DET
ajst-20195	139	2	quantitative	quantitative	ADJ
ajst-20195	139	3	inversion	inversion	NOUN
ajst-20195	139	4	of	of	ADP
ajst-20195	139	5	soil	soil	NOUN
ajst-20195	139	6	salinity	salinity	NOUN
ajst-20195	139	7	and	and	CCONJ
ajst-20195	139	8	model	model	NOUN
ajst-20195	139	9	accuracy	accuracy	NOUN
ajst-20195	139	10	validation	validation	NOUN
ajst-20195	139	11	were	be	AUX
ajst-20195	139	12	also	also	ADV
ajst-20195	139	13	carried	carry	VERB
ajst-20195	139	14	out	out	ADP
ajst-20195	139	15	in	in	ADP
ajst-20195	139	16	yinbei	yinbei	NOUN
ajst-20195	139	17	huinong	huinong	PROPN
ajst-20195	139	18	district	district	PROPN
ajst-20195	139	19	,	,	PUNCT
ajst-20195	139	20	ningxia	ningxia	PROPN
ajst-20195	139	21	.	.	PUNCT
ajst-20195	140	1	the	the	DET
ajst-20195	140	2	combinations	combination	NOUN
ajst-20195	140	3	of	of	ADP
ajst-20195	140	4	spectral	spectral	ADJ
ajst-20195	140	5	variables	variable	NOUN
ajst-20195	140	6	identified	identify	VERB
ajst-20195	140	7	by	by	ADP
ajst-20195	140	8	the	the	DET
ajst-20195	140	9	screening	screening	NOUN
ajst-20195	140	10	method	method	NOUN
ajst-20195	140	11	based	base	VERB
ajst-20195	140	12	on	on	ADP
ajst-20195	140	13	the	the	DET
ajst-20195	140	14	pls	pls	ADJ
ajst-20195	140	15	-	-	PUNCT
ajst-20195	140	16	vip	vip	NOUN
ajst-20195	140	17	criterion	criterion	NOUN
ajst-20195	140	18	were	be	AUX
ajst-20195	140	19	used	use	VERB
ajst-20195	140	20	as	as	ADP
ajst-20195	140	21	input	input	NOUN
ajst-20195	140	22	independent	independent	ADJ
ajst-20195	140	23	variables	variable	NOUN
ajst-20195	140	24	,	,	PUNCT
ajst-20195	140	25	and	and	CCONJ
ajst-20195	140	26	three	three	NUM
ajst-20195	140	27	machine	machine	NOUN
ajst-20195	140	28	learning	learning	NOUN
ajst-20195	140	29	methods	method	NOUN
ajst-20195	140	30	,	,	PUNCT
ajst-20195	140	31	namely	namely	ADV
ajst-20195	140	32	,	,	PUNCT
ajst-20195	140	33	random	random	ADJ
ajst-20195	140	34	forest	forest	NOUN
ajst-20195	140	35	(	(	PUNCT
ajst-20195	140	36	rf	rf	NOUN
ajst-20195	140	37	)	)	PUNCT
ajst-20195	140	38	,	,	PUNCT
ajst-20195	140	39	support	support	NOUN
ajst-20195	140	40	vector	vector	NOUN
ajst-20195	140	41	machine	machine	NOUN
ajst-20195	140	42	(	(	PUNCT
ajst-20195	140	43	svm	svm	PROPN
ajst-20195	140	44	)	)	PUNCT
ajst-20195	140	45	,	,	PUNCT
ajst-20195	140	46	and	and	CCONJ
ajst-20195	140	47	extreme	extreme	ADJ
ajst-20195	140	48	learning	learning	NOUN
ajst-20195	140	49	machine	machine	NOUN
ajst-20195	140	50	(	(	PUNCT
ajst-20195	140	51	eml	eml	PROPN
ajst-20195	140	52	)	)	PUNCT
ajst-20195	140	53	,	,	PUNCT
ajst-20195	140	54	were	be	AUX
ajst-20195	140	55	introduced	introduce	VERB
ajst-20195	140	56	for	for	ADP
ajst-20195	140	57	modelling	modelling	NOUN
ajst-20195	140	58	.	.	PUNCT
ajst-20195	141	1	the	the	DET
ajst-20195	141	2	combination	combination	NOUN
ajst-20195	141	3	of	of	ADP
ajst-20195	141	4	sensitive	sensitive	ADJ
ajst-20195	141	5	spectral	spectral	ADJ
ajst-20195	141	6	variables	variable	NOUN
ajst-20195	141	7	in	in	ADP
ajst-20195	141	8	spring	spring	NOUN
ajst-20195	141	9	and	and	CCONJ
ajst-20195	141	10	summer	summer	NOUN
ajst-20195	141	11	seasons	season	NOUN
ajst-20195	141	12	was	be	AUX
ajst-20195	141	13	constructed	construct	VERB
ajst-20195	141	14	,	,	PUNCT
ajst-20195	141	15	and	and	CCONJ
ajst-20195	141	16	the	the	DET
ajst-20195	141	17	inverse	inverse	NOUN
ajst-20195	141	18	model	model	NOUN
ajst-20195	141	19	of	of	ADP
ajst-20195	141	20	soil	soil	NOUN
ajst-20195	141	21	salt	salt	NOUN
ajst-20195	141	22	content	content	NOUN
ajst-20195	141	23	was	be	AUX
ajst-20195	141	24	established	establish	VERB
ajst-20195	141	25	.	.	PUNCT
ajst-20195	142	1	finally	finally	ADV
ajst-20195	142	2	,	,	PUNCT
ajst-20195	142	3	the	the	DET
ajst-20195	142	4	distribution	distribution	NOUN
ajst-20195	142	5	of	of	ADP
ajst-20195	142	6	soil	soil	NOUN
ajst-20195	142	7	salt	salt	NOUN
ajst-20195	142	8	content	content	NOUN
ajst-20195	142	9	in	in	ADP
ajst-20195	142	10	spring	spring	NOUN
ajst-20195	142	11	and	and	CCONJ
ajst-20195	142	12	summer	summer	NOUN
ajst-20195	142	13	seasons	season	NOUN
ajst-20195	142	14	in	in	ADP
ajst-20195	142	15	the	the	DET
ajst-20195	142	16	study	study	NOUN
ajst-20195	142	17	area	area	NOUN
ajst-20195	142	18	was	be	AUX
ajst-20195	142	19	mapped	map	VERB
ajst-20195	142	20	based	base	VERB
ajst-20195	142	21	on	on	ADP
ajst-20195	142	22	the	the	DET
ajst-20195	142	23	optimal	optimal	ADJ
ajst-20195	142	24	model	model	NOUN
ajst-20195	142	25	.	.	PUNCT
ajst-20195	143	1	the	the	DET
ajst-20195	143	2	results	result	NOUN
ajst-20195	143	3	showed	show	VERB
ajst-20195	143	4	that	that	SCONJ
ajst-20195	143	5	among	among	ADP
ajst-20195	143	6	the	the	DET
ajst-20195	143	7	soil	soil	NOUN
ajst-20195	143	8	salt	salt	NOUN
ajst-20195	143	9	content	content	NOUN
ajst-20195	143	10	inversion	inversion	NOUN
ajst-20195	143	11	models	model	NOUN
ajst-20195	143	12	established	establish	VERB
ajst-20195	143	13	based	base	VERB
ajst-20195	143	14	on	on	ADP
ajst-20195	143	15	the	the	DET
ajst-20195	143	16	spectral	spectral	ADJ
ajst-20195	143	17	bands	band	NOUN
ajst-20195	143	18	and	and	CCONJ
ajst-20195	143	19	spectral	spectral	ADJ
ajst-20195	143	20	indices	index	NOUN
ajst-20195	143	21	of	of	ADP
ajst-20195	143	22	sentinel-2	sentinel-2	ADJ
ajst-20195	143	23	imagery	imagery	NOUN
ajst-20195	143	24	,	,	PUNCT
ajst-20195	143	25	the	the	DET
ajst-20195	143	26	model	model	NOUN
ajst-20195	143	27	established	establish	VERB
ajst-20195	143	28	by	by	ADP
ajst-20195	143	29	using	use	VERB
ajst-20195	143	30	random	random	ADJ
ajst-20195	143	31	forest	forest	NOUN
ajst-20195	143	32	(	(	PUNCT
ajst-20195	143	33	rf	rf	NOUN
ajst-20195	143	34	)	)	PUNCT
ajst-20195	143	35	had	have	VERB
ajst-20195	143	36	the	the	DET
ajst-20195	143	37	best	good	ADJ
ajst-20195	143	38	accuracy	accuracy	NOUN
ajst-20195	143	39	and	and	CCONJ
ajst-20195	143	40	good	good	ADJ
ajst-20195	143	41	prediction	prediction	NOUN
ajst-20195	143	42	effect	effect	NOUN
ajst-20195	143	43	.	.	PUNCT
ajst-20195	144	1	this	this	PRON
ajst-20195	144	2	indicates	indicate	VERB
ajst-20195	144	3	that	that	SCONJ
ajst-20195	144	4	the	the	DET
ajst-20195	144	5	sentinel-2	sentinel-2	ADJ
ajst-20195	144	6	data	datum	NOUN
ajst-20195	144	7	can	can	AUX
ajst-20195	144	8	reliably	reliably	ADV
ajst-20195	144	9	predict	predict	VERB
ajst-20195	144	10	the	the	DET
ajst-20195	144	11	distribution	distribution	NOUN
ajst-20195	144	12	of	of	ADP
ajst-20195	144	13	soil	soil	NOUN
ajst-20195	144	14	salinity	salinity	NOUN
ajst-20195	144	15	,	,	PUNCT
ajst-20195	144	16	while	while	SCONJ
ajst-20195	144	17	the	the	DET
ajst-20195	144	18	machine	machine	NOUN
ajst-20195	144	19	learning	learning	NOUN
ajst-20195	144	20	model	model	NOUN
ajst-20195	144	21	is	be	AUX
ajst-20195	144	22	able	able	ADJ
ajst-20195	144	23	to	to	PART
ajst-20195	144	24	deal	deal	VERB
ajst-20195	144	25	with	with	ADP
ajst-20195	144	26	the	the	DET
ajst-20195	144	27	nonlinear	nonlinear	ADJ
ajst-20195	144	28	relationship	relationship	NOUN
ajst-20195	144	29	between	between	ADP
ajst-20195	144	30	spectral	spectral	ADJ
ajst-20195	144	31	information	information	NOUN
ajst-20195	144	32	and	and	CCONJ
ajst-20195	144	33	soil	soil	NOUN
ajst-20195	144	34	salt	salt	NOUN
ajst-20195	144	35	content	content	NOUN
ajst-20195	144	36	and	and	CCONJ
ajst-20195	144	37	reduce	reduce	VERB
ajst-20195	144	38	the	the	DET
ajst-20195	144	39	covariance	covariance	NOUN
ajst-20195	144	40	between	between	ADP
ajst-20195	144	41	variables	variable	NOUN
ajst-20195	144	42	,	,	PUNCT
ajst-20195	144	43	thus	thus	ADV
ajst-20195	144	44	greatly	greatly	ADV
ajst-20195	144	45	improving	improve	VERB
ajst-20195	144	46	the	the	DET
ajst-20195	144	47	accuracy	accuracy	NOUN
ajst-20195	144	48	and	and	CCONJ
ajst-20195	144	49	efficiency	efficiency	NOUN
ajst-20195	144	50	of	of	ADP
ajst-20195	144	51	prediction	prediction	NOUN
ajst-20195	144	52	.	.	PUNCT
ajst-20195	145	1	these	these	DET
ajst-20195	145	2	findings	finding	NOUN
ajst-20195	145	3	provide	provide	VERB
ajst-20195	145	4	a	a	DET
ajst-20195	145	5	reliable	reliable	ADJ
ajst-20195	145	6	reference	reference	NOUN
ajst-20195	145	7	for	for	ADP
ajst-20195	145	8	land	land	NOUN
ajst-20195	145	9	use	use	NOUN
ajst-20195	145	10	planning	planning	NOUN
ajst-20195	145	11	and	and	CCONJ
ajst-20195	145	12	management	management	NOUN
ajst-20195	145	13	.	.	PUNCT
ajst-20195	146	1	the	the	DET
ajst-20195	146	2	size	size	NOUN
ajst-20195	146	3	of	of	ADP
ajst-20195	146	4	spatial	spatial	ADJ
ajst-20195	146	5	resolution	resolution	NOUN
ajst-20195	146	6	and	and	CCONJ
ajst-20195	146	7	different	different	ADJ
ajst-20195	146	8	scales	scale	NOUN
ajst-20195	146	9	will	will	AUX
ajst-20195	146	10	have	have	VERB
ajst-20195	146	11	an	an	DET
ajst-20195	146	12	impact	impact	NOUN
ajst-20195	146	13	on	on	ADP
ajst-20195	146	14	the	the	DET
ajst-20195	146	15	fitting	fitting	ADJ
ajst-20195	146	16	results	result	NOUN
ajst-20195	146	17	.	.	PUNCT
ajst-20195	147	1	this	this	DET
ajst-20195	147	2	study	study	NOUN
ajst-20195	147	3	was	be	AUX
ajst-20195	147	4	conducted	conduct	VERB
ajst-20195	147	5	only	only	ADV
ajst-20195	147	6	at	at	ADP
ajst-20195	147	7	the	the	DET
ajst-20195	147	8	same	same	ADJ
ajst-20195	147	9	scale	scale	NOUN
ajst-20195	147	10	,	,	PUNCT
ajst-20195	147	11	but	but	CCONJ
ajst-20195	147	12	considering	consider	VERB
ajst-20195	147	13	the	the	DET
ajst-20195	147	14	variability	variability	NOUN
ajst-20195	147	15	of	of	ADP
ajst-20195	147	16	geographic	geographic	ADJ
ajst-20195	147	17	environments	environment	NOUN
ajst-20195	147	18	,	,	PUNCT
ajst-20195	147	19	multiple	multiple	ADJ
ajst-20195	147	20	scales	scale	NOUN
ajst-20195	147	21	should	should	AUX
ajst-20195	147	22	be	be	AUX
ajst-20195	147	23	tried	try	VERB
ajst-20195	147	24	in	in	ADP
ajst-20195	147	25	future	future	ADJ
ajst-20195	147	26	studies	study	NOUN
ajst-20195	147	27	to	to	PART
ajst-20195	147	28	better	well	ADV
ajst-20195	147	29	understand	understand	VERB
ajst-20195	147	30	the	the	DET
ajst-20195	147	31	correlation	correlation	NOUN
ajst-20195	147	32	between	between	ADP
ajst-20195	147	33	spectral	spectral	ADJ
ajst-20195	147	34	variables	variable	NOUN
ajst-20195	147	35	and	and	CCONJ
ajst-20195	147	36	soil	soil	NOUN
ajst-20195	147	37	salinity	salinity	NOUN
ajst-20195	147	38	in	in	ADP
ajst-20195	147	39	this	this	DET
ajst-20195	147	40	region	region	NOUN
ajst-20195	147	41	.	.	PUNCT
ajst-20195	148	1	in	in	ADP
ajst-20195	148	2	addition	addition	NOUN
ajst-20195	148	3	,	,	PUNCT
ajst-20195	148	4	the	the	DET
ajst-20195	148	5	failure	failure	NOUN
ajst-20195	148	6	to	to	PART
ajst-20195	148	7	overcome	overcome	VERB
ajst-20195	148	8	the	the	DET
ajst-20195	148	9	poor	poor	ADJ
ajst-20195	148	10	correlation	correlation	NOUN
ajst-20195	148	11	between	between	ADP
ajst-20195	148	12	soil	soil	NOUN
ajst-20195	148	13	salt	salt	NOUN
ajst-20195	148	14	content	content	NOUN
ajst-20195	148	15	and	and	CCONJ
ajst-20195	148	16	spectral	spectral	ADJ
ajst-20195	148	17	reflectance	reflectance	NOUN
ajst-20195	148	18	under	under	ADP
ajst-20195	148	19	vegetation	vegetation	NOUN
ajst-20195	148	20	cover	cover	NOUN
ajst-20195	148	21	conditions	condition	NOUN
ajst-20195	148	22	resulted	result	VERB
ajst-20195	148	23	in	in	ADP
ajst-20195	148	24	the	the	DET
ajst-20195	148	25	poor	poor	ADJ
ajst-20195	148	26	accuracy	accuracy	NOUN
ajst-20195	148	27	of	of	ADP
ajst-20195	148	28	the	the	DET
ajst-20195	148	29	summer	summer	NOUN
ajst-20195	148	30	inversion	inversion	NOUN
ajst-20195	148	31	model	model	NOUN
ajst-20195	148	32	constructed	construct	VERB
ajst-20195	148	33	on	on	ADP
ajst-20195	148	34	the	the	DET
ajst-20195	148	35	basis	basis	NOUN
ajst-20195	148	36	of	of	ADP
ajst-20195	148	37	these	these	DET
ajst-20195	148	38	images	image	NOUN
ajst-20195	148	39	in	in	ADP
ajst-20195	148	40	monitoring	monitor	VERB
ajst-20195	148	41	the	the	DET
ajst-20195	148	42	soil	soil	NOUN
ajst-20195	148	43	salt	salt	NOUN
ajst-20195	148	44	content	content	NOUN
ajst-20195	148	45	,	,	PUNCT
ajst-20195	148	46	which	which	PRON
ajst-20195	148	47	is	be	AUX
ajst-20195	148	48	difficult	difficult	ADJ
ajst-20195	148	49	to	to	PART
ajst-20195	148	50	accurately	accurately	ADV
ajst-20195	148	51	reflect	reflect	VERB
ajst-20195	148	52	the	the	DET
ajst-20195	148	53	actual	actual	ADJ
ajst-20195	148	54	spatial	spatial	ADJ
ajst-20195	148	55	pattern	pattern	NOUN
ajst-20195	148	56	.	.	PUNCT
ajst-20195	149	1	in	in	ADP
ajst-20195	149	2	order	order	NOUN
ajst-20195	149	3	to	to	PART
ajst-20195	149	4	improve	improve	VERB
ajst-20195	149	5	the	the	DET
ajst-20195	149	6	accuracy	accuracy	NOUN
ajst-20195	149	7	,	,	PUNCT
ajst-20195	149	8	a	a	DET
ajst-20195	149	9	decision	decision	NOUN
ajst-20195	149	10	tree	tree	NOUN
ajst-20195	149	11	of	of	ADP
ajst-20195	149	12	salt	salt	NOUN
ajst-20195	149	13	depth	depth	NOUN
ajst-20195	149	14	with	with	ADP
ajst-20195	149	15	the	the	DET
ajst-20195	149	16	normalised	normalise	VERB
ajst-20195	149	17	vegetation	vegetation	NOUN
ajst-20195	149	18	index	index	NOUN
ajst-20195	149	19	(	(	PUNCT
ajst-20195	149	20	ndvi	ndvi	NOUN
ajst-20195	149	21	)	)	PUNCT
ajst-20195	149	22	as	as	SCONJ
ajst-20195	149	23	the	the	DET
ajst-20195	149	24	branching	branch	VERB
ajst-20195	149	25	criterion	criterion	NOUN
ajst-20195	149	26	can	can	AUX
ajst-20195	149	27	be	be	AUX
ajst-20195	149	28	constructed	construct	VERB
ajst-20195	149	29	to	to	PART
ajst-20195	149	30	determine	determine	VERB
ajst-20195	149	31	the	the	DET
ajst-20195	149	32	optimal	optimal	ADJ
ajst-20195	149	33	depth	depth	NOUN
ajst-20195	149	34	for	for	ADP
ajst-20195	149	35	soil	soil	NOUN
ajst-20195	149	36	salt	salt	NOUN
ajst-20195	149	37	content	content	NOUN
ajst-20195	149	38	inversion	inversion	NOUN
ajst-20195	149	39	.	.	PUNCT
ajst-20195	150	1	subsequently	subsequently	ADV
ajst-20195	150	2	,	,	PUNCT
ajst-20195	150	3	a	a	DET
ajst-20195	150	4	category	category	NOUN
ajst-20195	150	5	decision	decision	NOUN
ajst-20195	150	6	tree	tree	NOUN
ajst-20195	150	7	with	with	ADP
ajst-20195	150	8	ndvi	ndvi	NOUN
ajst-20195	150	9	and	and	CCONJ
ajst-20195	150	10	surface	surface	NOUN
ajst-20195	150	11	soil	soil	NOUN
ajst-20195	150	12	water	water	NOUN
ajst-20195	150	13	content	content	NOUN
ajst-20195	150	14	as	as	ADP
ajst-20195	150	15	branching	branch	VERB
ajst-20195	150	16	criteria	criterion	NOUN
ajst-20195	150	17	can	can	AUX
ajst-20195	150	18	be	be	AUX
ajst-20195	150	19	constructed	construct	VERB
ajst-20195	150	20	to	to	PART
ajst-20195	150	21	divide	divide	VERB
ajst-20195	150	22	the	the	DET
ajst-20195	150	23	soil	soil	NOUN
ajst-20195	150	24	samples	sample	NOUN
ajst-20195	150	25	into	into	ADP
ajst-20195	150	26	different	different	ADJ
ajst-20195	150	27	categories	category	NOUN
ajst-20195	150	28	,	,	PUNCT
ajst-20195	150	29	so	so	SCONJ
ajst-20195	150	30	as	as	SCONJ
ajst-20195	150	31	to	to	PART
ajst-20195	150	32	establish	establish	VERB
ajst-20195	150	33	soil	soil	NOUN
ajst-20195	150	34	salt	salt	NOUN
ajst-20195	150	35	inversion	inversion	NOUN
ajst-20195	150	36	models	model	NOUN
ajst-20195	150	37	separately	separately	ADV
ajst-20195	150	38	.	.	PUNCT
ajst-20195	151	1	references	reference	NOUN
ajst-20195	151	2	[	[	X
ajst-20195	151	3	1	1	NUM
ajst-20195	151	4	]	]	PUNCT
ajst-20195	151	5	metternicht	metternicht	NOUN
ajst-20195	151	6	g	g	PROPN
ajst-20195	151	7	i	i	PROPN
ajst-20195	151	8	,	,	PUNCT
ajst-20195	151	9	zinck	zinck	PROPN
ajst-20195	151	10	j	j	PROPN
ajst-20195	151	11	a.	a.	NOUN
ajst-20195	151	12	remote	remote	NOUN
ajst-20195	151	13	sensing	sensing	NOUN
ajst-20195	151	14	of	of	ADP
ajst-20195	151	15	soil	soil	NOUN
ajst-20195	151	16	salinity	salinity	NOUN
ajst-20195	151	17	:	:	PUNCT
ajst-20195	151	18	potentials	potential	NOUN
ajst-20195	151	19	and	and	CCONJ
ajst-20195	151	20	constraints[j	constraints[j	NOUN
ajst-20195	151	21	]	]	PUNCT
ajst-20195	151	22	.	.	PUNCT
ajst-20195	152	1	remote	remote	ADJ
ajst-20195	152	2	sensing	sensing	NOUN
ajst-20195	152	3	of	of	ADP
ajst-20195	152	4	environment	environment	NOUN
ajst-20195	152	5	,	,	PUNCT
ajst-20195	152	6	2003	2003	NUM
ajst-20195	152	7	,	,	PUNCT
ajst-20195	152	8	85(1	85(1	NOUN
ajst-20195	152	9	):	):	PUNCT
ajst-20195	152	10	1	1	NUM
ajst-20195	152	11	-	-	SYM
ajst-20195	152	12	20	20	NUM
ajst-20195	152	13	.	.	PUNCT
ajst-20195	153	1	105	105	NUM
ajst-20195	154	1	[	[	X
ajst-20195	154	2	2	2	NUM
ajst-20195	154	3	]	]	X
ajst-20195	154	4	zhitao	zhitao	PROPN
ajst-20195	154	5	z	z	PROPN
ajst-20195	154	6	,	,	PUNCT
ajst-20195	154	7	guangfei	guangfei	PROPN
ajst-20195	154	8	w	w	PROPN
ajst-20195	154	9	,	,	PUNCT
ajst-20195	154	10	zhihua	zhihua	PROPN
ajst-20195	154	11	y	y	PROPN
ajst-20195	154	12	,	,	PUNCT
ajst-20195	154	13	et	et	NOUN
ajst-20195	154	14	al.soil	al.soil	PUNCT
ajst-20195	154	15	salt	salt	NOUN
ajst-20195	154	16	inversion	inversion	NOUN
ajst-20195	154	17	model	model	NOUN
ajst-20195	154	18	based	base	VERB
ajst-20195	154	19	on	on	ADP
ajst-20195	154	20	uav	uav	PROPN
ajst-20195	154	21	multispectral	multispectral	ADJ
ajst-20195	154	22	remote	remote	ADJ
ajst-20195	154	23	sensing[j].transactions	sensing[j].transaction	NOUN
ajst-20195	154	24	of	of	ADP
ajst-20195	154	25	the	the	DET
ajst-20195	154	26	chinese	chinese	ADJ
ajst-20195	154	27	society	society	NOUN
ajst-20195	154	28	for	for	ADP
ajst-20195	154	29	agricultural	agricultural	ADJ
ajst-20195	154	30	machinery	machinery	NOUN
ajst-20195	154	31	,	,	PUNCT
ajst-20195	154	32	2019	2019	NUM
ajst-20195	154	33	.	.	PUNCT
ajst-20195	155	1	[	[	X
ajst-20195	155	2	3	3	X
ajst-20195	155	3	]	]	PUNCT
ajst-20195	155	4	gorji	gorji	NOUN
ajst-20195	155	5	t	t	PROPN
ajst-20195	155	6	,	,	PUNCT
ajst-20195	155	7	yildirim	yildirim	PROPN
ajst-20195	155	8	a	a	PROPN
ajst-20195	155	9	,	,	PUNCT
ajst-20195	155	10	hamzehpour	hamzehpour	NOUN
ajst-20195	155	11	n	n	CCONJ
ajst-20195	155	12	,	,	PUNCT
ajst-20195	155	13	et	et	PROPN
ajst-20195	155	14	al	al	PROPN
ajst-20195	155	15	.	.	PUNCT
ajst-20195	155	16	soil	soil	NOUN
ajst-20195	155	17	salinity	salinity	NOUN
ajst-20195	155	18	analysis	analysis	NOUN
ajst-20195	155	19	of	of	ADP
ajst-20195	155	20	urmia	urmia	PROPN
ajst-20195	155	21	lake	lake	PROPN
ajst-20195	155	22	basin	basin	PROPN
ajst-20195	155	23	using	use	VERB
ajst-20195	155	24	landsat-8	landsat-8	PROPN
ajst-20195	155	25	oli	oli	NOUN
ajst-20195	155	26	and	and	CCONJ
ajst-20195	155	27	sentinel-2a	sentinel-2a	ADJ
ajst-20195	155	28	based	base	VERB
ajst-20195	155	29	spectral	spectral	ADJ
ajst-20195	155	30	indices	index	NOUN
ajst-20195	155	31	and	and	CCONJ
ajst-20195	155	32	electrical	electrical	ADJ
ajst-20195	155	33	conductivity	conductivity	NOUN
ajst-20195	155	34	measurements[j	measurements[j	NOUN
ajst-20195	155	35	]	]	PUNCT
ajst-20195	155	36	.	.	PUNCT
ajst-20195	156	1	ecological	ecological	ADJ
ajst-20195	156	2	indicators	indicator	NOUN
ajst-20195	156	3	,	,	PUNCT
ajst-20195	156	4	2020	2020	NUM
ajst-20195	156	5	,	,	PUNCT
ajst-20195	156	6	112	112	NUM
ajst-20195	156	7	:	:	SYM
ajst-20195	156	8	106173	106173	NUM
ajst-20195	156	9	.	.	PUNCT
ajst-20195	157	1	[	[	X
ajst-20195	157	2	4	4	X
ajst-20195	157	3	]	]	X
ajst-20195	157	4	wang	wang	PROPN
ajst-20195	157	5	y	y	PROPN
ajst-20195	157	6	,	,	PUNCT
ajst-20195	157	7	deng	deng	PROPN
ajst-20195	157	8	c	c	PROPN
ajst-20195	157	9	,	,	PUNCT
ajst-20195	157	10	liu	liu	PROPN
ajst-20195	157	11	y	y	PROPN
ajst-20195	157	12	,	,	PUNCT
ajst-20195	157	13	et	et	PROPN
ajst-20195	157	14	al	al	PROPN
ajst-20195	157	15	.	.	PUNCT
ajst-20195	157	16	identifying	identify	VERB
ajst-20195	157	17	change	change	NOUN
ajst-20195	157	18	in	in	ADP
ajst-20195	157	19	spatial	spatial	ADJ
ajst-20195	157	20	accumulation	accumulation	NOUN
ajst-20195	157	21	of	of	ADP
ajst-20195	157	22	soil	soil	NOUN
ajst-20195	157	23	salinity	salinity	NOUN
ajst-20195	157	24	in	in	ADP
ajst-20195	157	25	an	an	DET
ajst-20195	157	26	inland	inland	ADJ
ajst-20195	157	27	river	river	NOUN
ajst-20195	157	28	watershed	watershe	VERB
ajst-20195	157	29	,	,	PUNCT
ajst-20195	157	30	china[j	china[j	PROPN
ajst-20195	157	31	]	]	PUNCT
ajst-20195	157	32	.	.	PUNCT
ajst-20195	158	1	science	science	NOUN
ajst-20195	158	2	of	of	ADP
ajst-20195	158	3	the	the	DET
ajst-20195	158	4	total	total	ADJ
ajst-20195	158	5	environment	environment	NOUN
ajst-20195	158	6	,	,	PUNCT
ajst-20195	158	7	2018	2018	NUM
ajst-20195	158	8	,	,	PUNCT
ajst-20195	158	9	621（15	621（15	NUM
ajst-20195	158	10	）	）	NOUN
ajst-20195	158	11	:	:	PUNCT
ajst-20195	158	12	177	177	NUM
ajst-20195	158	13	-	-	SYM
ajst-20195	158	14	185	185	NUM
ajst-20195	158	15	.	.	PUNCT
ajst-20195	159	1	[	[	X
ajst-20195	159	2	5	5	X
ajst-20195	159	3	]	]	X
ajst-20195	159	4	bannari	bannari	PROPN
ajst-20195	159	5	a	a	PROPN
ajst-20195	159	6	,	,	PUNCT
ajst-20195	159	7	el	el	PROPN
ajst-20195	159	8	-	-	NOUN
ajst-20195	159	9	battay	battay	NOUN
ajst-20195	159	10	a	a	PRON
ajst-20195	159	11	,	,	PUNCT
ajst-20195	159	12	bannari	bannari	PROPN
ajst-20195	159	13	r	r	PROPN
ajst-20195	159	14	,	,	PUNCT
ajst-20195	159	15	et	et	PROPN
ajst-20195	159	16	al	al	PROPN
ajst-20195	159	17	.	.	PUNCT
ajst-20195	159	18	sentinel	sentinel	PROPN
ajst-20195	159	19	-	-	PUNCT
ajst-20195	159	20	msi	msi	NOUN
ajst-20195	159	21	vnir	vnir	NOUN
ajst-20195	159	22	and	and	CCONJ
ajst-20195	159	23	swir	swir	NOUN
ajst-20195	159	24	bands	band	NOUN
ajst-20195	159	25	sensitivity	sensitivity	NOUN
ajst-20195	159	26	analysis	analysis	NOUN
ajst-20195	159	27	for	for	ADP
ajst-20195	159	28	soil	soil	NOUN
ajst-20195	159	29	salinity	salinity	NOUN
ajst-20195	159	30	discrimination	discrimination	NOUN
ajst-20195	159	31	in	in	ADP
ajst-20195	159	32	an	an	DET
ajst-20195	159	33	arid	arid	NOUN
ajst-20195	159	34	landscape[j	landscape[j	NOUN
ajst-20195	159	35	]	]	PUNCT
ajst-20195	159	36	.	.	PUNCT
ajst-20195	160	1	remote	remote	ADJ
ajst-20195	160	2	sensing	sensing	NOUN
ajst-20195	160	3	,	,	PUNCT
ajst-20195	160	4	2018	2018	NUM
ajst-20195	160	5	,	,	PUNCT
ajst-20195	160	6	10(6	10(6	NUM
ajst-20195	160	7	):	):	PUNCT
ajst-20195	160	8	855	855	NUM
ajst-20195	160	9	.	.	PUNCT
ajst-20195	161	1	[	[	X
ajst-20195	161	2	6	6	NUM
ajst-20195	161	3	]	]	X
ajst-20195	161	4	hoa	hoa	NOUN
ajst-20195	161	5	p	p	PROPN
ajst-20195	161	6	v	v	PROPN
ajst-20195	161	7	,	,	PUNCT
ajst-20195	161	8	giang	giang	PROPN
ajst-20195	161	9	n	n	PROPN
ajst-20195	161	10	v	v	PROPN
ajst-20195	161	11	,	,	PUNCT
ajst-20195	161	12	binh	binh	PROPN
ajst-20195	161	13	n	n	ADV
ajst-20195	161	14	a	a	PROPN
ajst-20195	161	15	,	,	PUNCT
ajst-20195	161	16	et	et	PROPN
ajst-20195	161	17	al	al	PROPN
ajst-20195	161	18	.	.	PUNCT
ajst-20195	161	19	soil	soil	NOUN
ajst-20195	161	20	salinity	salinity	NOUN
ajst-20195	161	21	map	map	NOUN
ajst-20195	161	22	*	*	NOUN
ajst-20195	161	23	*	*	PUNCT
ajst-20195	161	24	using	use	VERB
ajst-20195	161	25	sar	sar	PROPN
ajst-20195	161	26	sentinel-1	sentinel-1	NUM
ajst-20195	161	27	data	datum	NOUN
ajst-20195	161	28	and	and	CCONJ
ajst-20195	161	29	advanced	advanced	ADJ
ajst-20195	161	30	machine	machine	NOUN
ajst-20195	161	31	learning	learn	VERB
ajst-20195	161	32	algorithms	algorithm	NOUN
ajst-20195	161	33	:	:	PUNCT
ajst-20195	161	34	a	a	DET
ajst-20195	161	35	case	case	NOUN
ajst-20195	161	36	study	study	NOUN
ajst-20195	161	37	at	at	ADP
ajst-20195	161	38	ben	ben	PROPN
ajst-20195	161	39	tre	tre	PROPN
ajst-20195	161	40	province	province	NOUN
ajst-20195	161	41	of	of	ADP
ajst-20195	161	42	the	the	DET
ajst-20195	161	43	mekong	mekong	PROPN
ajst-20195	161	44	river	river	PROPN
ajst-20195	161	45	delta	delta	NOUN
ajst-20195	161	46	(	(	PUNCT
ajst-20195	161	47	vietnam)[j	vietnam)[j	PROPN
ajst-20195	161	48	]	]	PUNCT
ajst-20195	161	49	.	.	PUNCT
ajst-20195	162	1	remote	remote	ADJ
ajst-20195	162	2	sensing	sensing	NOUN
ajst-20195	162	3	,	,	PUNCT
ajst-20195	162	4	2019	2019	NUM
ajst-20195	162	5	,	,	PUNCT
ajst-20195	162	6	11(2	11(2	NUM
ajst-20195	162	7	):	):	PUNCT
ajst-20195	162	8	128	128	NUM
ajst-20195	162	9	.	.	PUNCT
ajst-20195	163	1	[	[	X
ajst-20195	163	2	7	7	X
ajst-20195	163	3	]	]	X
ajst-20195	163	4	hong	hong	PROPN
ajst-20195	163	5	y	y	PROPN
ajst-20195	163	6	,	,	PUNCT
ajst-20195	163	7	liu	liu	PROPN
ajst-20195	163	8	y	y	PROPN
ajst-20195	163	9	,	,	PUNCT
ajst-20195	163	10	chen	chen	PROPN
ajst-20195	163	11	y	y	PROPN
ajst-20195	163	12	,	,	PUNCT
ajst-20195	163	13	et	et	PROPN
ajst-20195	164	1	al	al	PROPN
ajst-20195	164	2	.	.	PUNCT
ajst-20195	164	3	application	application	NOUN
ajst-20195	164	4	of	of	ADP
ajst-20195	164	5	fractional	fractional	ADJ
ajst-20195	164	6	-	-	PUNCT
ajst-20195	164	7	order	order	NOUN
ajst-20195	164	8	derivative	derivative	NOUN
ajst-20195	164	9	in	in	ADP
ajst-20195	164	10	the	the	DET
ajst-20195	164	11	quantitative	quantitative	ADJ
ajst-20195	164	12	estimation	estimation	NOUN
ajst-20195	164	13	of	of	ADP
ajst-20195	164	14	soil	soil	NOUN
ajst-20195	164	15	organic	organic	ADJ
ajst-20195	164	16	matter	matter	NOUN
ajst-20195	164	17	content	content	NOUN
ajst-20195	164	18	through	through	ADP
ajst-20195	164	19	visible	visible	ADJ
ajst-20195	164	20	and	and	CCONJ
ajst-20195	164	21	near	near	ADV
ajst-20195	164	22	-	-	PUNCT
ajst-20195	164	23	infrared	infrared	ADJ
ajst-20195	164	24	spectroscopy[j	spectroscopy[j	NOUN
ajst-20195	164	25	]	]	PUNCT
ajst-20195	164	26	.	.	PUNCT
ajst-20195	165	1	geoderma	geoderma	PROPN
ajst-20195	165	2	,	,	PUNCT
ajst-20195	165	3	2019	2019	NUM
ajst-20195	165	4	,	,	PUNCT
ajst-20195	165	5	337	337	NUM
ajst-20195	165	6	:	:	PUNCT
ajst-20195	165	7	758	758	NUM
ajst-20195	165	8	-	-	SYM
ajst-20195	165	9	769	769	NUM
ajst-20195	165	10	.	.	PUNCT
ajst-20195	166	1	[	[	X
ajst-20195	166	2	8	8	NUM
ajst-20195	166	3	]	]	X
ajst-20195	166	4	wang	wang	PROPN
ajst-20195	166	5	m	m	PROPN
ajst-20195	166	6	,	,	PUNCT
ajst-20195	166	7	wang	wang	PROPN
ajst-20195	166	8	j	j	PROPN
ajst-20195	166	9	,	,	PUNCT
ajst-20195	166	10	chen	chen	PROPN
ajst-20195	166	11	j	j	PROPN
ajst-20195	166	12	,	,	PUNCT
ajst-20195	166	13	et	et	PROPN
ajst-20195	166	14	al	al	PROPN
ajst-20195	166	15	.	.	PROPN
ajst-20195	166	16	effect	effect	NOUN
ajst-20195	166	17	of	of	ADP
ajst-20195	166	18	commercial	commercial	ADJ
ajst-20195	166	19	yeast	yeast	NOUN
ajst-20195	166	20	starter	starter	ADJ
ajst-20195	166	21	cultures	culture	NOUN
ajst-20195	166	22	on	on	ADP
ajst-20195	166	23	cabernet	cabernet	NOUN
ajst-20195	166	24	sauvignon	sauvignon	NOUN
ajst-20195	166	25	wine	wine	NOUN
ajst-20195	166	26	aroma	aroma	NOUN
ajst-20195	166	27	compounds	compound	NOUN
ajst-20195	166	28	and	and	CCONJ
ajst-20195	166	29	microbiota[j	microbiota[j	NOUN
ajst-20195	166	30	]	]	PUNCT
ajst-20195	166	31	.	.	PUNCT
ajst-20195	167	1	foods	food	NOUN
ajst-20195	167	2	,	,	PUNCT
ajst-20195	167	3	2022	2022	NUM
ajst-20195	167	4	,	,	PUNCT
ajst-20195	167	5	11(12	11(12	NUM
ajst-20195	167	6	):	):	PUNCT
ajst-20195	167	7	1725	1725	NUM
ajst-20195	167	8	.	.	PUNCT
ajst-20195	168	1	[	[	X
ajst-20195	168	2	9	9	NUM
ajst-20195	168	3	]	]	X
ajst-20195	168	4	tao	tao	PROPN
ajst-20195	168	5	z	z	PROPN
ajst-20195	168	6	,	,	PUNCT
ajst-20195	168	7	cun	cun	PROPN
ajst-20195	168	8	-	-	PUNCT
ajst-20195	168	9	yong	yong	PROPN
ajst-20195	168	10	j	j	PROPN
ajst-20195	168	11	u	u	PROPN
ajst-20195	168	12	,	,	PUNCT
ajst-20195	168	13	ti	ti	PROPN
ajst-20195	168	14	-	-	NOUN
ajst-20195	168	15	jiu	jiu	NOUN
ajst-20195	168	16	c	c	PROPN
ajst-20195	168	17	a	a	PROPN
ajst-20195	168	18	i	i	PROPN
ajst-20195	168	19	,	,	PUNCT
ajst-20195	168	20	et	et	PROPN
ajst-20195	168	21	al	al	PROPN
ajst-20195	168	22	.	.	PROPN
ajst-20195	168	23	selection	selection	NOUN
ajst-20195	168	24	of	of	ADP
ajst-20195	168	25	parameters	parameter	NOUN
ajst-20195	168	26	for	for	ADP
ajst-20195	168	27	estimating	estimate	VERB
ajst-20195	168	28	canopy	canopy	NOUN
ajst-20195	168	29	closure	closure	NOUN
ajst-20195	168	30	density	density	NOUN
ajst-20195	168	31	using	use	VERB
ajst-20195	168	32	variable	variable	ADJ
ajst-20195	168	33	importance	importance	NOUN
ajst-20195	168	34	of	of	ADP
ajst-20195	168	35	projection	projection	NOUN
ajst-20195	168	36	criterion[j	criterion[j	PROPN
ajst-20195	168	37	]	]	PUNCT
ajst-20195	168	38	.	.	PUNCT
ajst-20195	169	1	journal	journal	PROPN
ajst-20195	169	2	of	of	ADP
ajst-20195	169	3	beijing	beijing	PROPN
ajst-20195	169	4	forestry	forestry	PROPN
ajst-20195	169	5	university	university	PROPN
ajst-20195	169	6	,	,	PUNCT
ajst-20195	169	7	2010	2010	NUM
ajst-20195	169	8	,	,	PUNCT
ajst-20195	169	9	32(6	32(6	NUM
ajst-20195	169	10	):	):	PUNCT
ajst-20195	169	11	37	37	NUM
ajst-20195	169	12	-	-	SYM
ajst-20195	169	13	41	41	NUM
ajst-20195	169	14	.	.	PUNCT
ajst-20195	170	1	[	[	X
ajst-20195	170	2	10	10	NUM
ajst-20195	170	3	]	]	X
ajst-20195	170	4	jia	jia	PROPN
ajst-20195	170	5	p	p	PROPN
ajst-20195	170	6	,	,	PUNCT
ajst-20195	170	7	shang	shang	PROPN
ajst-20195	170	8	t	t	PROPN
ajst-20195	170	9	,	,	PUNCT
ajst-20195	170	10	zhang	zhang	PROPN
ajst-20195	170	11	j	j	PROPN
ajst-20195	170	12	,	,	PUNCT
ajst-20195	170	13	et	et	PROPN
ajst-20195	170	14	al	al	PROPN
ajst-20195	170	15	.	.	PUNCT
ajst-20195	170	16	inversion	inversion	NOUN
ajst-20195	170	17	of	of	ADP
ajst-20195	170	18	soil	soil	NOUN
ajst-20195	170	19	ph	ph	VERB
ajst-20195	170	20	during	during	ADP
ajst-20195	170	21	the	the	DET
ajst-20195	170	22	dry	dry	ADJ
ajst-20195	170	23	and	and	CCONJ
ajst-20195	170	24	wet	wet	ADJ
ajst-20195	170	25	seasons	season	NOUN
ajst-20195	170	26	in	in	ADP
ajst-20195	170	27	the	the	DET
ajst-20195	170	28	yinbei	yinbei	NOUN
ajst-20195	170	29	region	region	NOUN
ajst-20195	170	30	of	of	ADP
ajst-20195	170	31	ningxia	ningxia	PROPN
ajst-20195	170	32	,	,	PUNCT
ajst-20195	170	33	china	china	PROPN
ajst-20195	170	34	,	,	PUNCT
ajst-20195	170	35	based	base	VERB
ajst-20195	170	36	on	on	ADP
ajst-20195	170	37	multi	multi	ADJ
ajst-20195	170	38	-	-	ADJ
ajst-20195	170	39	source	source	NOUN
ajst-20195	170	40	remote	remote	ADJ
ajst-20195	170	41	sensing	sense	VERB
ajst-20195	170	42	data[j	data[j	NOUN
ajst-20195	170	43	]	]	PUNCT
ajst-20195	170	44	.	.	PUNCT
ajst-20195	171	1	geoderma	geoderma	PROPN
ajst-20195	171	2	regional	regional	ADJ
ajst-20195	171	3	,	,	PUNCT
ajst-20195	171	4	2021	2021	NUM
ajst-20195	171	5	,	,	PUNCT
ajst-20195	171	6	25	25	NUM
ajst-20195	171	7	:	:	PUNCT
ajst-20195	171	8	e00399	e00399	NOUN
ajst-20195	171	9	.	.	PUNCT
ajst-20195	172	1	[	[	X
ajst-20195	172	2	11	11	NUM
ajst-20195	172	3	]	]	X
ajst-20195	172	4	bannari	bannari	PROPN
ajst-20195	172	5	a	a	PROPN
ajst-20195	172	6	,	,	PUNCT
ajst-20195	172	7	el	el	PROPN
ajst-20195	172	8	-	-	NOUN
ajst-20195	172	9	battay	battay	NOUN
ajst-20195	172	10	a	a	PRON
ajst-20195	172	11	,	,	PUNCT
ajst-20195	172	12	bannari	bannari	PROPN
ajst-20195	172	13	r	r	PROPN
ajst-20195	172	14	,	,	PUNCT
ajst-20195	172	15	et	et	PROPN
ajst-20195	172	16	al	al	PROPN
ajst-20195	172	17	.	.	PUNCT
ajst-20195	172	18	sentinel	sentinel	PROPN
ajst-20195	172	19	-	-	PUNCT
ajst-20195	172	20	msi	msi	NOUN
ajst-20195	172	21	vnir	vnir	NOUN
ajst-20195	172	22	and	and	CCONJ
ajst-20195	172	23	swir	swir	NOUN
ajst-20195	172	24	bands	band	NOUN
ajst-20195	172	25	sensitivity	sensitivity	NOUN
ajst-20195	172	26	analysis	analysis	NOUN
ajst-20195	172	27	for	for	ADP
ajst-20195	172	28	soil	soil	NOUN
ajst-20195	172	29	salinity	salinity	NOUN
ajst-20195	172	30	discrimination	discrimination	NOUN
ajst-20195	172	31	in	in	ADP
ajst-20195	172	32	an	an	DET
ajst-20195	172	33	arid	arid	NOUN
ajst-20195	172	34	landscape[j	landscape[j	NOUN
ajst-20195	172	35	]	]	PUNCT
ajst-20195	172	36	.	.	PUNCT
ajst-20195	173	1	remote	remote	ADJ
ajst-20195	173	2	sensing	sensing	NOUN
ajst-20195	173	3	,	,	PUNCT
ajst-20195	173	4	2018	2018	NUM
ajst-20195	173	5	,	,	PUNCT
ajst-20195	173	6	10(6	10(6	NUM
ajst-20195	173	7	):	):	PUNCT
ajst-20195	173	8	855	855	NUM
ajst-20195	173	9	.	.	PUNCT
ajst-20195	174	1	[	[	X
ajst-20195	174	2	12	12	NUM
ajst-20195	174	3	]	]	X
ajst-20195	174	4	wang	wang	PROPN
ajst-20195	174	5	j	j	PROPN
ajst-20195	174	6	,	,	PUNCT
ajst-20195	174	7	ding	ding	PROPN
ajst-20195	174	8	j	j	PROPN
ajst-20195	174	9	,	,	PUNCT
ajst-20195	174	10	abulimiti	abulimiti	PROPN
ajst-20195	174	11	a	a	X
ajst-20195	174	12	,	,	PUNCT
ajst-20195	174	13	et	et	PROPN
ajst-20195	174	14	al	al	PROPN
ajst-20195	174	15	.	.	PROPN
ajst-20195	174	16	quantitative	quantitative	ADJ
ajst-20195	174	17	estimation	estimation	NOUN
ajst-20195	174	18	of	of	ADP
ajst-20195	174	19	soil	soil	NOUN
ajst-20195	174	20	salinity	salinity	NOUN
ajst-20195	174	21	by	by	ADP
ajst-20195	174	22	means	mean	NOUN
ajst-20195	174	23	of	of	ADP
ajst-20195	174	24	different	different	ADJ
ajst-20195	174	25	modeling	modeling	NOUN
ajst-20195	174	26	methods	method	NOUN
ajst-20195	174	27	and	and	CCONJ
ajst-20195	174	28	visible	visible	ADJ
ajst-20195	174	29	-	-	PUNCT
ajst-20195	174	30	near	near	ADV
ajst-20195	174	31	infrared	infrared	NOUN
ajst-20195	174	32	(	(	PUNCT
ajst-20195	174	33	vis	vis	X
ajst-20195	174	34	–	–	PUNCT
ajst-20195	174	35	nir	nir	ADJ
ajst-20195	174	36	)	)	PUNCT
ajst-20195	174	37	spectroscopy	spectroscopy	NOUN
ajst-20195	174	38	,	,	PUNCT
ajst-20195	174	39	ebinur	ebinur	NOUN
ajst-20195	174	40	lake	lake	PROPN
ajst-20195	174	41	wetland	wetland	PROPN
ajst-20195	174	42	,	,	PUNCT
ajst-20195	174	43	northwest	northwest	PROPN
ajst-20195	174	44	china[j	china[j	PROPN
ajst-20195	174	45	]	]	PUNCT
ajst-20195	174	46	.	.	PUNCT
ajst-20195	175	1	peerj	peerj	PROPN
ajst-20195	175	2	,	,	PUNCT
ajst-20195	175	3	2018	2018	NUM
ajst-20195	175	4	,	,	PUNCT
ajst-20195	175	5	6	6	NUM
ajst-20195	175	6	:	:	PUNCT
ajst-20195	175	7	e4703	e4703	NOUN
ajst-20195	175	8	.	.	PUNCT
ajst-20195	176	1	[	[	X
ajst-20195	176	2	13	13	NUM
ajst-20195	176	3	]	]	X
ajst-20195	176	4	jia	jia	PROPN
ajst-20195	176	5	z	z	PROPN
ajst-20195	176	6	,	,	PUNCT
ajst-20195	176	7	tan	tan	PROPN
ajst-20195	176	8	y	y	PROPN
ajst-20195	176	9	,	,	PUNCT
ajst-20195	176	10	guan	guan	PROPN
ajst-20195	176	11	x	x	PROPN
ajst-20195	176	12	,	,	PUNCT
ajst-20195	176	13	et	et	PROPN
ajst-20195	176	14	al	al	PROPN
ajst-20195	176	15	.	.	PROPN
ajst-20195	176	16	saline	saline	NOUN
ajst-20195	176	17	-	-	PUNCT
ajst-20195	176	18	alkali	alkali	ADJ
ajst-20195	176	19	soil	soil	NOUN
ajst-20195	176	20	formation	formation	NOUN
ajst-20195	176	21	and	and	CCONJ
ajst-20195	176	22	its	its	PRON
ajst-20195	176	23	remediation	remediation	NOUN
ajst-20195	176	24	strategies	strategy	NOUN
ajst-20195	176	25	in	in	ADP
ajst-20195	176	26	different	different	ADJ
ajst-20195	176	27	regions	region	NOUN
ajst-20195	176	28	of	of	ADP
ajst-20195	176	29	ningxia	ningxia	NOUN
ajst-20195	176	30	:	:	PUNCT
ajst-20195	176	31	a	a	DET
ajst-20195	176	32	comprehensive	comprehensive	ADJ
ajst-20195	176	33	review[j	review[j	NOUN
ajst-20195	176	34	]	]	PUNCT
ajst-20195	176	35	.	.	PUNCT
ajst-20195	177	1	j.	j.	PROPN
ajst-20195	177	2	irrig	irrig	PROPN
ajst-20195	177	3	.	.	PUNCT
ajst-20195	178	1	drain	drain	PROPN
ajst-20195	178	2	,	,	PUNCT
ajst-20195	178	3	2023	2023	NUM
ajst-20195	178	4	,	,	PUNCT
ajst-20195	178	5	42	42	NUM
ajst-20195	178	6	:	:	SYM
ajst-20195	178	7	122	122	NUM
ajst-20195	178	8	-	-	SYM
ajst-20195	178	9	134	134	NUM
ajst-20195	178	10	.	.	PUNCT
ajst-20195	179	1	[	[	X
ajst-20195	179	2	14	14	NUM
ajst-20195	179	3	]	]	PUNCT
ajst-20195	179	4	tibin	tibin	PROPN
ajst-20195	179	5	z	z	PROPN
ajst-20195	179	6	,	,	PUNCT
ajst-20195	179	7	yaohu	yaohu	PROPN
ajst-20195	179	8	k	k	PROPN
ajst-20195	179	9	,	,	PUNCT
ajst-20195	179	10	wei	wei	PROPN
ajst-20195	179	11	h.	h.	PROPN
ajst-20195	179	12	study	study	PROPN
ajst-20195	179	13	on	on	ADP
ajst-20195	179	14	salinity	salinity	NOUN
ajst-20195	179	15	characteristics	characteristic	NOUN
ajst-20195	179	16	of	of	ADP
ajst-20195	179	17	takyric	takyric	ADJ
ajst-20195	179	18	solonetz	solonetz	ADJ
ajst-20195	179	19	in	in	ADP
ajst-20195	179	20	ningxia	ningxia	PROPN
ajst-20195	179	21	yinbei	yinbei	PROPN
ajst-20195	179	22	region[j	region[j	PROPN
ajst-20195	179	23	]	]	PUNCT
ajst-20195	179	24	.	.	PUNCT
ajst-20195	180	1	soil	soil	NOUN
ajst-20195	180	2	,	,	PUNCT
ajst-20195	180	3	2012	2012	NUM
ajst-20195	180	4	,	,	PUNCT
ajst-20195	180	5	44(6	44(6	NOUN
ajst-20195	180	6	):	):	PUNCT
ajst-20195	180	7	1001	1001	NUM
ajst-20195	180	8	-	-	SYM
ajst-20195	180	9	1008	1008	NUM
ajst-20195	180	10	.	.	PUNCT
ajst-20195	181	1	[	[	X
ajst-20195	181	2	15	15	NUM
ajst-20195	181	3	]	]	X
ajst-20195	181	4	zhao	zhao	PROPN
ajst-20195	181	5	w	w	PROPN
ajst-20195	181	6	,	,	PUNCT
ajst-20195	181	7	hu	hu	PROPN
ajst-20195	181	8	j	j	PROPN
ajst-20195	181	9	,	,	PUNCT
ajst-20195	181	10	li	li	PROPN
ajst-20195	181	11	z	z	PROPN
ajst-20195	181	12	,	,	PUNCT
ajst-20195	181	13	et	et	PROPN
ajst-20195	181	14	al	al	PROPN
ajst-20195	181	15	.	.	PUNCT
ajst-20195	181	16	variability	variability	NOUN
ajst-20195	181	17	and	and	CCONJ
ajst-20195	181	18	modelling	modelling	NOUN
ajst-20195	181	19	of	of	ADP
ajst-20195	181	20	soil	soil	NOUN
ajst-20195	181	21	moisture	moisture	NOUN
ajst-20195	181	22	,	,	PUNCT
ajst-20195	181	23	salt	salt	NOUN
ajst-20195	181	24	and	and	CCONJ
ajst-20195	181	25	organic	organic	ADJ
ajst-20195	181	26	matter	matter	NOUN
ajst-20195	181	27	content	content	NOUN
ajst-20195	181	28	in	in	ADP
ajst-20195	181	29	a	a	DET
ajst-20195	181	30	gravel	gravel	NOUN
ajst-20195	181	31	-	-	PUNCT
ajst-20195	181	32	sand	sand	NOUN
ajst-20195	181	33	mulched	mulch	VERB
ajst-20195	181	34	jujube	jujube	PROPN
ajst-20195	181	35	orchard[j	orchard[j	PROPN
ajst-20195	181	36	]	]	PUNCT
ajst-20195	181	37	.	.	PUNCT
ajst-20195	182	1	nature	nature	PROPN
ajst-20195	182	2	environment	environment	PROPN
ajst-20195	182	3	&	&	CCONJ
ajst-20195	182	4	pollution	pollution	NOUN
ajst-20195	182	5	technology	technology	NOUN
ajst-20195	182	6	,	,	PUNCT
ajst-20195	182	7	2020	2020	NUM
ajst-20195	182	8	,	,	PUNCT
ajst-20195	182	9	19(4	19(4	NUM
ajst-20195	182	10	)	)	PUNCT
ajst-20195	182	11	.	.	PUNCT