id	sid	tid	token	lemma	pos
ajst-11953	1	1	academic	academic	ADJ
ajst-11953	1	2	journal	journal	NOUN
ajst-11953	1	3	of	of	ADP
ajst-11953	1	4	science	science	NOUN
ajst-11953	1	5	and	and	CCONJ
ajst-11953	1	6	technology	technology	NOUN
ajst-11953	1	7	issn	issn	NOUN
ajst-11953	1	8	:	:	PUNCT
ajst-11953	1	9	2771	2771	NUM
ajst-11953	1	10	-	-	SYM
ajst-11953	1	11	3032	3032	NUM
ajst-11953	1	12	|	|	NOUN
ajst-11953	1	13	vol	vol	NOUN
ajst-11953	1	14	.	.	PROPN
ajst-11953	2	1	7	7	NUM
ajst-11953	2	2	,	,	PUNCT
ajst-11953	2	3	no	no	INTJ
ajst-11953	2	4	.	.	NOUN
ajst-11953	2	5	2	2	NUM
ajst-11953	2	6	,	,	PUNCT
ajst-11953	2	7	2023	2023	NUM
ajst-11953	2	8	111	111	NUM
ajst-11953	2	9	research	research	NOUN
ajst-11953	2	10	on	on	ADP
ajst-11953	2	11	land	land	NOUN
ajst-11953	2	12	use	use	VERB
ajst-11953	2	13	classification	classification	NOUN
ajst-11953	2	14	method	method	NOUN
ajst-11953	2	15	of	of	ADP
ajst-11953	2	16	high	high	ADJ
ajst-11953	2	17	resolution	resolution	NOUN
ajst-11953	2	18	remote	remote	ADJ
ajst-11953	2	19	sensing	sense	VERB
ajst-11953	2	20	image	image	NOUN
ajst-11953	2	21	based	base	VERB
ajst-11953	2	22	on	on	ADP
ajst-11953	2	23	svm	svm	PROPN
ajst-11953	2	24	hui	hui	PROPN
ajst-11953	2	25	kong1	kong1	PROPN
ajst-11953	2	26	,	,	PUNCT
ajst-11953	2	27	2	2	NUM
ajst-11953	2	28	,	,	PUNCT
ajst-11953	2	29	3	3	NUM
ajst-11953	2	30	,	,	PUNCT
ajst-11953	2	31	4	4	NUM
ajst-11953	2	32	,	,	PUNCT
ajst-11953	2	33	dan	dan	PROPN
ajst-11953	2	34	wu1	wu1	PROPN
ajst-11953	2	35	,	,	PUNCT
ajst-11953	2	36	2	2	NUM
ajst-11953	2	37	,	,	PUNCT
ajst-11953	2	38	3	3	NUM
ajst-11953	2	39	,	,	PUNCT
ajst-11953	2	40	4	4	NUM
ajst-11953	2	41	1	1	NUM
ajst-11953	2	42	shaanxi	shaanxi	NOUN
ajst-11953	2	43	provincial	provincial	ADJ
ajst-11953	2	44	land	land	NOUN
ajst-11953	2	45	engineering	engineering	NOUN
ajst-11953	2	46	construction	construction	PROPN
ajst-11953	2	47	group	group	PROPN
ajst-11953	2	48	co.	co.	PROPN
ajst-11953	2	49	,	,	PUNCT
ajst-11953	2	50	ltd	ltd	PROPN
ajst-11953	2	51	.	.	PROPN
ajst-11953	2	52	,	,	PUNCT
ajst-11953	2	53	xi'an	xi'an	PROPN
ajst-11953	2	54	710075	710075	NUM
ajst-11953	2	55	,	,	PUNCT
ajst-11953	2	56	china	china	PROPN
ajst-11953	2	57	2	2	NUM
ajst-11953	2	58	institute	institute	NOUN
ajst-11953	2	59	of	of	ADP
ajst-11953	2	60	land	land	NOUN
ajst-11953	2	61	engineering	engineering	NOUN
ajst-11953	2	62	and	and	CCONJ
ajst-11953	2	63	technology	technology	NOUN
ajst-11953	2	64	,	,	PUNCT
ajst-11953	2	65	shaanxi	shaanxi	PROPN
ajst-11953	2	66	provincial	provincial	ADJ
ajst-11953	2	67	land	land	NOUN
ajst-11953	2	68	engineering	engineering	NOUN
ajst-11953	2	69	construction	construction	PROPN
ajst-11953	2	70	group	group	PROPN
ajst-11953	2	71	co.	co.	PROPN
ajst-11953	2	72	,	,	PUNCT
ajst-11953	2	73	ltd	ltd	PROPN
ajst-11953	2	74	.	.	PROPN
ajst-11953	2	75	,	,	PUNCT
ajst-11953	2	76	xi'an	xi'an	PROPN
ajst-11953	2	77	710021	710021	NUM
ajst-11953	2	78	,	,	PUNCT
ajst-11953	2	79	china	china	PROPN
ajst-11953	2	80	3	3	NUM
ajst-11953	2	81	key	key	ADJ
ajst-11953	2	82	laboratory	laboratory	NOUN
ajst-11953	2	83	of	of	ADP
ajst-11953	2	84	degraded	degraded	ADJ
ajst-11953	2	85	and	and	CCONJ
ajst-11953	2	86	unused	unused	ADJ
ajst-11953	2	87	land	land	NOUN
ajst-11953	2	88	consolidation	consolidation	NOUN
ajst-11953	2	89	engineering	engineering	NOUN
ajst-11953	2	90	,	,	PUNCT
ajst-11953	2	91	the	the	DET
ajst-11953	2	92	ministry	ministry	PROPN
ajst-11953	2	93	of	of	ADP
ajst-11953	2	94	land	land	NOUN
ajst-11953	2	95	and	and	CCONJ
ajst-11953	2	96	resources	resource	NOUN
ajst-11953	2	97	,	,	PUNCT
ajst-11953	2	98	xi'an	xi'an	PROPN
ajst-11953	2	99	710021	710021	NUM
ajst-11953	2	100	,	,	PUNCT
ajst-11953	2	101	china	china	PROPN
ajst-11953	2	102	4	4	NUM
ajst-11953	2	103	shaanxi	shaanxi	PROPN
ajst-11953	2	104	provincial	provincial	ADJ
ajst-11953	2	105	land	land	NOUN
ajst-11953	2	106	consolidation	consolidation	NOUN
ajst-11953	2	107	engineering	engineering	NOUN
ajst-11953	2	108	technology	technology	NOUN
ajst-11953	2	109	research	research	NOUN
ajst-11953	2	110	center	center	NOUN
ajst-11953	2	111	,	,	PUNCT
ajst-11953	2	112	xi'an	xi'an	PROPN
ajst-11953	2	113	710021	710021	NUM
ajst-11953	2	114	,	,	PUNCT
ajst-11953	2	115	china	china	PROPN
ajst-11953	2	116	abstract	abstract	NOUN
ajst-11953	2	117	:	:	PUNCT
ajst-11953	2	118	considering	consider	VERB
ajst-11953	2	119	the	the	DET
ajst-11953	2	120	high	high	ADJ
ajst-11953	2	121	spatial	spatial	ADJ
ajst-11953	2	122	resolution	resolution	NOUN
ajst-11953	2	123	remote	remote	ADJ
ajst-11953	2	124	sensing	sense	VERB
ajst-11953	2	125	image	image	NOUN
ajst-11953	2	126	has	have	VERB
ajst-11953	2	127	huge	huge	ADJ
ajst-11953	2	128	amounts	amount	NOUN
ajst-11953	2	129	of	of	ADP
ajst-11953	2	130	data	datum	NOUN
ajst-11953	2	131	and	and	CCONJ
ajst-11953	2	132	complex	complex	ADJ
ajst-11953	2	133	spectral	spectral	ADJ
ajst-11953	2	134	distribution	distribution	NOUN
ajst-11953	2	135	and	and	CCONJ
ajst-11953	2	136	the	the	DET
ajst-11953	2	137	characteristics	characteristic	NOUN
ajst-11953	2	138	of	of	ADP
ajst-11953	2	139	the	the	DET
ajst-11953	2	140	space	space	NOUN
ajst-11953	2	141	characteristics	characteristic	NOUN
ajst-11953	2	142	of	of	ADP
ajst-11953	2	143	the	the	DET
ajst-11953	2	144	rich	rich	ADJ
ajst-11953	2	145	,	,	PUNCT
ajst-11953	2	146	in	in	ADP
ajst-11953	2	147	combination	combination	NOUN
ajst-11953	2	148	with	with	ADP
ajst-11953	2	149	support	support	NOUN
ajst-11953	2	150	vector	vector	NOUN
ajst-11953	2	151	machine	machine	NOUN
ajst-11953	2	152	(	(	PUNCT
ajst-11953	2	153	svm	svm	PROPN
ajst-11953	2	154	)	)	PUNCT
ajst-11953	2	155	in	in	ADP
ajst-11953	2	156	tackling	tackle	VERB
ajst-11953	2	157	small	small	ADJ
ajst-11953	2	158	sample	sample	NOUN
ajst-11953	2	159	,	,	PUNCT
ajst-11953	2	160	nonlinear	nonlinear	ADJ
ajst-11953	2	161	and	and	CCONJ
ajst-11953	2	162	high	high	ADJ
ajst-11953	2	163	dimensional	dimensional	ADJ
ajst-11953	2	164	pattern	pattern	NOUN
ajst-11953	2	165	recognition	recognition	NOUN
ajst-11953	2	166	problems	problem	NOUN
ajst-11953	2	167	show	show	VERB
ajst-11953	2	168	unique	unique	ADJ
ajst-11953	2	169	advantages	advantage	NOUN
ajst-11953	2	170	,	,	PUNCT
ajst-11953	2	171	in	in	ADP
ajst-11953	2	172	this	this	DET
ajst-11953	2	173	chapter	chapter	NOUN
ajst-11953	2	174	will	will	AUX
ajst-11953	2	175	experiment	experiment	VERB
ajst-11953	2	176	data	datum	NOUN
ajst-11953	2	177	by	by	ADP
ajst-11953	2	178	using	use	VERB
ajst-11953	2	179	support	support	NOUN
ajst-11953	2	180	vector	vector	NOUN
ajst-11953	2	181	machine	machine	NOUN
ajst-11953	2	182	(	(	PUNCT
ajst-11953	2	183	svm	svm	PROPN
ajst-11953	2	184	)	)	PUNCT
ajst-11953	2	185	for	for	ADP
ajst-11953	2	186	high	high	ADJ
ajst-11953	2	187	spatial	spatial	ADJ
ajst-11953	2	188	resolution	resolution	NOUN
ajst-11953	2	189	remote	remote	ADJ
ajst-11953	2	190	sensing	sense	VERB
ajst-11953	2	191	image	image	NOUN
ajst-11953	2	192	classification	classification	NOUN
ajst-11953	2	193	.	.	PUNCT
ajst-11953	3	1	keywords	keyword	NOUN
ajst-11953	3	2	:	:	PUNCT
ajst-11953	3	3	high	high	ADJ
ajst-11953	3	4	spatial	spatial	ADJ
ajst-11953	3	5	resolution	resolution	NOUN
ajst-11953	3	6	,	,	PUNCT
ajst-11953	3	7	support	support	NOUN
ajst-11953	3	8	vector	vector	NOUN
ajst-11953	3	9	machine	machine	NOUN
ajst-11953	3	10	,	,	PUNCT
ajst-11953	3	11	image	image	NOUN
ajst-11953	3	12	classification	classification	NOUN
ajst-11953	3	13	,	,	PUNCT
ajst-11953	3	14	dag	dag	PROPN
ajst-11953	3	15	method	method	NOUN
ajst-11953	3	16	.	.	PUNCT
ajst-11953	4	1	1	1	X
ajst-11953	4	2	.	.	X
ajst-11953	4	3	introduction	introduction	NOUN
ajst-11953	4	4	with	with	ADP
ajst-11953	4	5	the	the	DET
ajst-11953	4	6	continuous	continuous	ADJ
ajst-11953	4	7	improvement	improvement	NOUN
ajst-11953	4	8	of	of	ADP
ajst-11953	4	9	the	the	DET
ajst-11953	4	10	spatial	spatial	ADJ
ajst-11953	4	11	resolution	resolution	NOUN
ajst-11953	4	12	of	of	ADP
ajst-11953	4	13	remote	remote	ADJ
ajst-11953	4	14	sensing	sensing	NOUN
ajst-11953	4	15	images	image	NOUN
ajst-11953	4	16	,	,	PUNCT
ajst-11953	4	17	the	the	DET
ajst-11953	4	18	detailed	detailed	ADJ
ajst-11953	4	19	information	information	NOUN
ajst-11953	4	20	contained	contain	VERB
ajst-11953	4	21	in	in	ADP
ajst-11953	4	22	the	the	DET
ajst-11953	4	23	images	image	NOUN
ajst-11953	4	24	is	be	AUX
ajst-11953	4	25	more	more	ADV
ajst-11953	4	26	and	and	CCONJ
ajst-11953	4	27	more	more	ADV
ajst-11953	4	28	rich	rich	ADJ
ajst-11953	4	29	.	.	PUNCT
ajst-11953	5	1	compared	compare	VERB
ajst-11953	5	2	with	with	ADP
ajst-11953	5	3	the	the	DET
ajst-11953	5	4	past	past	ADJ
ajst-11953	5	5	low	low	ADJ
ajst-11953	5	6	and	and	CCONJ
ajst-11953	5	7	medium	medium	ADJ
ajst-11953	5	8	spatial	spatial	ADJ
ajst-11953	5	9	resolution	resolution	NOUN
ajst-11953	5	10	images	image	NOUN
ajst-11953	5	11	,	,	PUNCT
ajst-11953	5	12	the	the	DET
ajst-11953	5	13	images	image	NOUN
ajst-11953	5	14	can	can	AUX
ajst-11953	5	15	better	well	ADV
ajst-11953	5	16	represent	represent	VERB
ajst-11953	5	17	the	the	DET
ajst-11953	5	18	texture	texture	NOUN
ajst-11953	5	19	,	,	PUNCT
ajst-11953	5	20	shape	shape	NOUN
ajst-11953	5	21	and	and	CCONJ
ajst-11953	5	22	geometric	geometric	ADJ
ajst-11953	5	23	structure	structure	NOUN
ajst-11953	5	24	information	information	NOUN
ajst-11953	5	25	of	of	ADP
ajst-11953	5	26	the	the	DET
ajst-11953	5	27	target.at	target.at	NOUN
ajst-11953	5	28	the	the	DET
ajst-11953	5	29	same	same	ADJ
ajst-11953	5	30	time	time	NOUN
ajst-11953	5	31	,	,	PUNCT
ajst-11953	5	32	the	the	DET
ajst-11953	5	33	improvement	improvement	NOUN
ajst-11953	5	34	of	of	ADP
ajst-11953	5	35	spatial	spatial	ADJ
ajst-11953	5	36	resolution	resolution	NOUN
ajst-11953	5	37	of	of	ADP
ajst-11953	5	38	remote	remote	ADJ
ajst-11953	5	39	sensing	sensing	NOUN
ajst-11953	5	40	images	image	NOUN
ajst-11953	5	41	is	be	AUX
ajst-11953	5	42	accompanied	accompany	VERB
ajst-11953	5	43	by	by	ADP
ajst-11953	5	44	the	the	DET
ajst-11953	5	45	surge	surge	NOUN
ajst-11953	5	46	of	of	ADP
ajst-11953	5	47	data	datum	NOUN
ajst-11953	5	48	volume	volume	NOUN
ajst-11953	5	49	,	,	PUNCT
ajst-11953	5	50	which	which	PRON
ajst-11953	5	51	requires	require	VERB
ajst-11953	5	52	efficient	efficient	ADJ
ajst-11953	5	53	automatic	automatic	ADJ
ajst-11953	5	54	classification	classification	NOUN
ajst-11953	5	55	technology	technology	NOUN
ajst-11953	5	56	to	to	PART
ajst-11953	5	57	replace	replace	VERB
ajst-11953	5	58	the	the	DET
ajst-11953	5	59	traditional	traditional	ADJ
ajst-11953	5	60	manual	manual	ADJ
ajst-11953	5	61	visual	visual	ADJ
ajst-11953	5	62	interpretation	interpretation	NOUN
ajst-11953	5	63	to	to	PART
ajst-11953	5	64	extract	extract	VERB
ajst-11953	5	65	useful	useful	ADJ
ajst-11953	5	66	information	information	NOUN
ajst-11953	5	67	from	from	ADP
ajst-11953	5	68	images.on	images.on	NOUN
ajst-11953	5	69	the	the	DET
ajst-11953	5	70	other	other	ADJ
ajst-11953	5	71	hand	hand	NOUN
ajst-11953	5	72	,	,	PUNCT
ajst-11953	5	73	high	high	ADJ
ajst-11953	5	74	spatial	spatial	ADJ
ajst-11953	5	75	resolution	resolution	NOUN
ajst-11953	5	76	remote	remote	ADJ
ajst-11953	5	77	sensing	sensing	NOUN
ajst-11953	5	78	images	image	NOUN
ajst-11953	5	79	contain	contain	VERB
ajst-11953	5	80	a	a	DET
ajst-11953	5	81	large	large	ADJ
ajst-11953	5	82	amount	amount	NOUN
ajst-11953	5	83	of	of	ADP
ajst-11953	5	84	detailed	detailed	ADJ
ajst-11953	5	85	information	information	NOUN
ajst-11953	5	86	,	,	PUNCT
ajst-11953	5	87	resulting	result	VERB
ajst-11953	5	88	in	in	ADP
ajst-11953	5	89	unusually	unusually	ADV
ajst-11953	5	90	complex	complex	ADJ
ajst-11953	5	91	spectral	spectral	ADJ
ajst-11953	5	92	distribution	distribution	NOUN
ajst-11953	5	93	,	,	PUNCT
ajst-11953	5	94	which	which	PRON
ajst-11953	5	95	reduces	reduce	VERB
ajst-11953	5	96	the	the	DET
ajst-11953	5	97	separability	separability	NOUN
ajst-11953	5	98	of	of	ADP
ajst-11953	5	99	ground	ground	NOUN
ajst-11953	5	100	objects	object	NOUN
ajst-11953	5	101	in	in	ADP
ajst-11953	5	102	the	the	DET
ajst-11953	5	103	spectral	spectral	ADJ
ajst-11953	5	104	domain.in	domain.in	PRON
ajst-11953	5	105	order	order	NOUN
ajst-11953	5	106	to	to	PART
ajst-11953	5	107	solve	solve	VERB
ajst-11953	5	108	this	this	DET
ajst-11953	5	109	problem	problem	NOUN
ajst-11953	5	110	,	,	PUNCT
ajst-11953	5	111	automatic	automatic	ADJ
ajst-11953	5	112	classification	classification	NOUN
ajst-11953	5	113	technology	technology	NOUN
ajst-11953	5	114	needs	need	VERB
ajst-11953	5	115	to	to	PART
ajst-11953	5	116	make	make	VERB
ajst-11953	5	117	full	full	ADJ
ajst-11953	5	118	use	use	NOUN
ajst-11953	5	119	of	of	ADP
ajst-11953	5	120	the	the	DET
ajst-11953	5	121	hidden	hide	VERB
ajst-11953	5	122	information	information	NOUN
ajst-11953	5	123	in	in	ADP
ajst-11953	5	124	the	the	DET
ajst-11953	5	125	image	image	NOUN
ajst-11953	5	126	and	and	CCONJ
ajst-11953	5	127	make	make	VERB
ajst-11953	5	128	up	up	ADP
ajst-11953	5	129	for	for	ADP
ajst-11953	5	130	the	the	DET
ajst-11953	5	131	deficiency	deficiency	NOUN
ajst-11953	5	132	of	of	ADP
ajst-11953	5	133	spectral	spectral	ADJ
ajst-11953	5	134	features	feature	NOUN
ajst-11953	5	135	.	.	PUNCT
ajst-11953	6	1	in	in	ADP
ajst-11953	6	2	this	this	DET
ajst-11953	6	3	paper	paper	NOUN
ajst-11953	6	4	,	,	PUNCT
ajst-11953	6	5	considering	consider	VERB
ajst-11953	6	6	the	the	DET
ajst-11953	6	7	advantages	advantage	NOUN
ajst-11953	6	8	of	of	ADP
ajst-11953	6	9	support	support	NOUN
ajst-11953	6	10	vector	vector	NOUN
ajst-11953	6	11	machine	machine	NOUN
ajst-11953	6	12	in	in	ADP
ajst-11953	6	13	solving	solve	VERB
ajst-11953	6	14	small	small	ADJ
ajst-11953	6	15	sample	sample	NOUN
ajst-11953	6	16	,	,	PUNCT
ajst-11953	6	17	nonlinear	nonlinear	ADJ
ajst-11953	6	18	and	and	CCONJ
ajst-11953	6	19	highdimensional	highdimensional	ADJ
ajst-11953	6	20	pattern	pattern	NOUN
ajst-11953	6	21	recognition	recognition	NOUN
ajst-11953	6	22	problems	problem	NOUN
ajst-11953	6	23	,	,	PUNCT
ajst-11953	6	24	this	this	DET
ajst-11953	6	25	machine	machine	NOUN
ajst-11953	6	26	learning	learn	VERB
ajst-11953	6	27	algorithm	algorithm	NOUN
ajst-11953	6	28	is	be	AUX
ajst-11953	6	29	used	use	VERB
ajst-11953	6	30	as	as	ADP
ajst-11953	6	31	a	a	DET
ajst-11953	6	32	classifier	classifier	NOUN
ajst-11953	6	33	to	to	PART
ajst-11953	6	34	classify	classify	VERB
ajst-11953	6	35	high	high	ADJ
ajst-11953	6	36	spatial	spatial	ADJ
ajst-11953	6	37	resolution	resolution	NOUN
ajst-11953	6	38	remote	remote	ADJ
ajst-11953	6	39	sensing	sensing	NOUN
ajst-11953	6	40	images	image	NOUN
ajst-11953	6	41	from	from	ADP
ajst-11953	6	42	the	the	DET
ajst-11953	6	43	perspective	perspective	NOUN
ajst-11953	6	44	of	of	ADP
ajst-11953	6	45	spectral	spectral	ADJ
ajst-11953	6	46	domain.according	domain.accorde	VERB
ajst-11953	6	47	to	to	ADP
ajst-11953	6	48	the	the	DET
ajst-11953	6	49	experimental	experimental	ADJ
ajst-11953	6	50	results	result	NOUN
ajst-11953	6	51	,	,	PUNCT
ajst-11953	6	52	it	it	PRON
ajst-11953	6	53	is	be	AUX
ajst-11953	6	54	not	not	PART
ajst-11953	6	55	reliable	reliable	ADJ
ajst-11953	6	56	to	to	PART
ajst-11953	6	57	distinguish	distinguish	VERB
ajst-11953	6	58	the	the	DET
ajst-11953	6	59	ground	ground	NOUN
ajst-11953	6	60	object	object	NOUN
ajst-11953	6	61	in	in	ADP
ajst-11953	6	62	the	the	DET
ajst-11953	6	63	image	image	NOUN
ajst-11953	6	64	only	only	ADV
ajst-11953	6	65	by	by	ADP
ajst-11953	6	66	the	the	DET
ajst-11953	6	67	difference	difference	NOUN
ajst-11953	6	68	of	of	ADP
ajst-11953	6	69	spectral	spectral	ADJ
ajst-11953	6	70	characteristics	characteristic	NOUN
ajst-11953	6	71	,	,	PUNCT
ajst-11953	6	72	and	and	CCONJ
ajst-11953	6	73	the	the	DET
ajst-11953	6	74	different	different	ADJ
ajst-11953	6	75	ground	ground	NOUN
ajst-11953	6	76	object	object	NOUN
ajst-11953	6	77	with	with	ADP
ajst-11953	6	78	similar	similar	ADJ
ajst-11953	6	79	spectral	spectral	ADJ
ajst-11953	6	80	characteristics	characteristic	NOUN
ajst-11953	6	81	will	will	AUX
ajst-11953	6	82	be	be	AUX
ajst-11953	6	83	confused	confuse	VERB
ajst-11953	6	84	.	.	PUNCT
ajst-11953	7	1	2	2	X
ajst-11953	7	2	.	.	X
ajst-11953	7	3	multi	multi	ADJ
ajst-11953	7	4	-	-	ADJ
ajst-11953	7	5	classification	classification	ADJ
ajst-11953	7	6	problem	problem	NOUN
ajst-11953	7	7	of	of	ADP
ajst-11953	7	8	support	support	NOUN
ajst-11953	7	9	vector	vector	NOUN
ajst-11953	7	10	machines	machine	NOUN
ajst-11953	7	11	2.1	2.1	NUM
ajst-11953	7	12	.	.	PUNCT
ajst-11953	8	1	"	"	PUNCT
ajst-11953	8	2	one	one	NUM
ajst-11953	8	3	-	-	PUNCT
ajst-11953	8	4	to	to	ADP
ajst-11953	8	5	-	-	PUNCT
ajst-11953	8	6	many	many	ADJ
ajst-11953	8	7	"	"	PUNCT
ajst-11953	8	8	approach	approach	NOUN
ajst-11953	8	9	a	a	DET
ajst-11953	8	10	one	one	NUM
ajst-11953	8	11	-	-	PUNCT
ajst-11953	8	12	to	to	ADP
ajst-11953	8	13	-	-	PUNCT
ajst-11953	8	14	many	many	ADJ
ajst-11953	8	15	approach	approach	NOUN
ajst-11953	8	16	is	be	AUX
ajst-11953	8	17	more	more	ADV
ajst-11953	8	18	specifically	specifically	ADV
ajst-11953	8	19	a	a	DET
ajst-11953	8	20	one	one	NUM
ajst-11953	8	21	-	-	PUNCT
ajst-11953	8	22	toothers	toother	NOUN
ajst-11953	8	23	approach.assuming	approach.assume	VERB
ajst-11953	8	24	that	that	SCONJ
ajst-11953	8	25	there	there	PRON
ajst-11953	8	26	are	be	VERB
ajst-11953	8	27	n	n	PRON
ajst-11953	8	28	categories	category	NOUN
ajst-11953	8	29	to	to	PART
ajst-11953	8	30	be	be	AUX
ajst-11953	8	31	classified	classify	VERB
ajst-11953	8	32	,	,	PUNCT
ajst-11953	8	33	the	the	DET
ajst-11953	8	34	samples	sample	NOUN
ajst-11953	8	35	of	of	ADP
ajst-11953	8	36	one	one	NUM
ajst-11953	8	37	category	category	NOUN
ajst-11953	8	38	are	be	AUX
ajst-11953	8	39	classified	classify	VERB
ajst-11953	8	40	as	as	ADP
ajst-11953	8	41	positive	positive	ADJ
ajst-11953	8	42	samples	sample	NOUN
ajst-11953	8	43	for	for	ADP
ajst-11953	8	44	the	the	DET
ajst-11953	8	45	first	first	ADJ
ajst-11953	8	46	time	time	NOUN
ajst-11953	8	47	,	,	PUNCT
ajst-11953	8	48	and	and	CCONJ
ajst-11953	8	49	the	the	DET
ajst-11953	8	50	samples	sample	NOUN
ajst-11953	8	51	of	of	ADP
ajst-11953	8	52	the	the	DET
ajst-11953	8	53	other	other	ADJ
ajst-11953	8	54	n-1	n-1	NOUN
ajst-11953	8	55	categories	category	NOUN
ajst-11953	8	56	are	be	AUX
ajst-11953	8	57	collectively	collectively	ADV
ajst-11953	8	58	classified	classify	VERB
ajst-11953	8	59	as	as	ADP
ajst-11953	8	60	negative	negative	ADJ
ajst-11953	8	61	samples	sample	NOUN
ajst-11953	8	62	.	.	PUNCT
ajst-11953	9	1	thus	thus	ADV
ajst-11953	9	2	,	,	PUNCT
ajst-11953	9	3	a	a	DET
ajst-11953	9	4	binary	binary	ADJ
ajst-11953	9	5	support	support	NOUN
ajst-11953	9	6	vector	vector	NOUN
ajst-11953	9	7	machine	machine	NOUN
ajst-11953	9	8	is	be	AUX
ajst-11953	9	9	obtained	obtain	VERB
ajst-11953	9	10	,	,	PUNCT
ajst-11953	9	11	which	which	PRON
ajst-11953	9	12	can	can	AUX
ajst-11953	9	13	identify	identify	VERB
ajst-11953	9	14	whether	whether	SCONJ
ajst-11953	9	15	unknown	unknown	ADJ
ajst-11953	9	16	data	datum	NOUN
ajst-11953	9	17	belongs	belong	VERB
ajst-11953	9	18	to	to	ADP
ajst-11953	9	19	the	the	DET
ajst-11953	9	20	category	category	NOUN
ajst-11953	9	21	of	of	ADP
ajst-11953	9	22	positive	positive	ADJ
ajst-11953	9	23	samples.the	samples.the	DET
ajst-11953	9	24	rest	rest	NOUN
ajst-11953	9	25	of	of	ADP
ajst-11953	9	26	the	the	DET
ajst-11953	9	27	n-1	n-1	ADJ
ajst-11953	9	28	classes	class	NOUN
ajst-11953	9	29	and	and	CCONJ
ajst-11953	9	30	so	so	ADV
ajst-11953	9	31	on	on	ADV
ajst-11953	9	32	,	,	PUNCT
ajst-11953	9	33	resulting	result	VERB
ajst-11953	9	34	in	in	ADP
ajst-11953	9	35	n	n	ADP
ajst-11953	9	36	support	support	NOUN
ajst-11953	9	37	vector	vector	NOUN
ajst-11953	9	38	machines	machine	NOUN
ajst-11953	9	39	corresponding	correspond	VERB
ajst-11953	9	40	to	to	ADP
ajst-11953	9	41	n	n	PROPN
ajst-11953	9	42	classes.when	classes.when	PRON
ajst-11953	9	43	the	the	DET
ajst-11953	9	44	unknown	unknown	ADJ
ajst-11953	9	45	data	data	NOUN
ajst-11953	9	46	is	be	AUX
ajst-11953	9	47	classified	classify	VERB
ajst-11953	9	48	,	,	PUNCT
ajst-11953	9	49	the	the	DET
ajst-11953	9	50	unknown	unknown	ADJ
ajst-11953	9	51	data	datum	NOUN
ajst-11953	9	52	are	be	AUX
ajst-11953	9	53	input	input	VERB
ajst-11953	9	54	into	into	ADP
ajst-11953	9	55	n	n	ADP
ajst-11953	9	56	support	support	NOUN
ajst-11953	9	57	vector	vector	NOUN
ajst-11953	9	58	machines	machine	NOUN
ajst-11953	9	59	respectively	respectively	ADV
ajst-11953	9	60	to	to	PART
ajst-11953	9	61	obtain	obtain	VERB
ajst-11953	9	62	the	the	DET
ajst-11953	9	63	results	result	NOUN
ajst-11953	9	64	of	of	ADP
ajst-11953	9	65	multiple	multiple	ADJ
ajst-11953	9	66	classification	classification	NOUN
ajst-11953	9	67	.	.	PUNCT
ajst-11953	10	1	2.2	2.2	NUM
ajst-11953	10	2	.	.	PUNCT
ajst-11953	11	1	"	"	PUNCT
ajst-11953	11	2	one	one	NUM
ajst-11953	11	3	-	-	PUNCT
ajst-11953	11	4	to	to	ADP
ajst-11953	11	5	-	-	PUNCT
ajst-11953	11	6	one	one	NUM
ajst-11953	11	7	"	"	PUNCT
ajst-11953	11	8	approach	approach	NOUN
ajst-11953	11	9	the	the	DET
ajst-11953	11	10	"	"	PUNCT
ajst-11953	11	11	one	one	NUM
ajst-11953	11	12	-	-	PUNCT
ajst-11953	11	13	on	on	ADP
ajst-11953	11	14	-	-	PUNCT
ajst-11953	11	15	one	one	NUM
ajst-11953	11	16	"	"	PUNCT
ajst-11953	11	17	method	method	NOUN
ajst-11953	11	18	can	can	AUX
ajst-11953	11	19	also	also	ADV
ajst-11953	11	20	be	be	AUX
ajst-11953	11	21	called	call	VERB
ajst-11953	11	22	the	the	DET
ajst-11953	11	23	voting	voting	NOUN
ajst-11953	11	24	method.suppose	method.suppose	X
ajst-11953	11	25	there	there	PRON
ajst-11953	11	26	are	be	VERB
ajst-11953	11	27	n	n	PRON
ajst-11953	11	28	categories	category	NOUN
ajst-11953	11	29	to	to	PART
ajst-11953	11	30	be	be	AUX
ajst-11953	11	31	divided	divide	VERB
ajst-11953	11	32	,	,	PUNCT
ajst-11953	11	33	take	take	VERB
ajst-11953	11	34	samples	sample	NOUN
ajst-11953	11	35	of	of	ADP
ajst-11953	11	36	any	any	DET
ajst-11953	11	37	two	two	NUM
ajst-11953	11	38	categories	category	NOUN
ajst-11953	11	39	,	,	PUNCT
ajst-11953	11	40	and	and	CCONJ
ajst-11953	11	41	set	set	VERB
ajst-11953	11	42	one	one	NUM
ajst-11953	11	43	type	type	NOUN
ajst-11953	11	44	of	of	ADP
ajst-11953	11	45	sample	sample	NOUN
ajst-11953	11	46	as	as	ADP
ajst-11953	11	47	positive	positive	ADJ
ajst-11953	11	48	sample	sample	NOUN
ajst-11953	11	49	and	and	CCONJ
ajst-11953	11	50	the	the	DET
ajst-11953	11	51	other	other	ADJ
ajst-11953	11	52	as	as	ADP
ajst-11953	11	53	negative	negative	ADJ
ajst-11953	11	54	sample	sample	NOUN
ajst-11953	11	55	to	to	PART
ajst-11953	11	56	get	get	VERB
ajst-11953	11	57	a	a	DET
ajst-11953	11	58	binary	binary	ADJ
ajst-11953	11	59	support	support	NOUN
ajst-11953	11	60	vector	vector	NOUN
ajst-11953	11	61	machine.and	machine.and	X
ajst-11953	11	62	so	so	ADV
ajst-11953	11	63	on	on	ADV
ajst-11953	11	64	,	,	PUNCT
ajst-11953	11	65	we	we	PRON
ajst-11953	11	66	need	need	VERB
ajst-11953	11	67	to	to	PART
ajst-11953	11	68	construct	construct	VERB
ajst-11953	11	69	a	a	DET
ajst-11953	11	70	binary	binary	ADJ
ajst-11953	11	71	support	support	NOUN
ajst-11953	11	72	vector	vector	NOUN
ajst-11953	11	73	machine	machine	NOUN
ajst-11953	11	74	.	.	PUNCT
ajst-11953	12	1	when	when	SCONJ
ajst-11953	12	2	the	the	DET
ajst-11953	12	3	unknown	unknown	ADJ
ajst-11953	12	4	data	data	NOUN
ajst-11953	12	5	is	be	AUX
ajst-11953	12	6	classified	classify	VERB
ajst-11953	12	7	,	,	PUNCT
ajst-11953	12	8	the	the	DET
ajst-11953	12	9	classification	classification	NOUN
ajst-11953	12	10	of	of	ADP
ajst-11953	12	11	the	the	DET
ajst-11953	12	12	unknown	unknown	ADJ
ajst-11953	12	13	data	datum	NOUN
ajst-11953	12	14	is	be	AUX
ajst-11953	12	15	judged	judge	VERB
ajst-11953	12	16	by	by	ADP
ajst-11953	12	17	the	the	DET
ajst-11953	12	18	binary	binary	PROPN
ajst-11953	12	19	support	support	PROPN
ajst-11953	12	20	vector	vector	NOUN
ajst-11953	12	21	machine	machine	NOUN
ajst-11953	12	22	.	.	PUNCT
ajst-11953	13	1	whenever	whenever	SCONJ
ajst-11953	13	2	a	a	DET
ajst-11953	13	3	support	support	NOUN
ajst-11953	13	4	vector	vector	NOUN
ajst-11953	13	5	machine	machine	NOUN
ajst-11953	13	6	judges	judge	VERB
ajst-11953	13	7	the	the	DET
ajst-11953	13	8	unknown	unknown	ADJ
ajst-11953	13	9	data	datum	NOUN
ajst-11953	13	10	as	as	ADP
ajst-11953	13	11	a	a	DET
ajst-11953	13	12	certain	certain	ADJ
ajst-11953	13	13	category	category	NOUN
ajst-11953	13	14	,	,	PUNCT
ajst-11953	13	15	it	it	PRON
ajst-11953	13	16	votes	vote	VERB
ajst-11953	13	17	on	on	ADP
ajst-11953	13	18	the	the	DET
ajst-11953	13	19	category	category	NOUN
ajst-11953	13	20	.	.	PUNCT
ajst-11953	14	1	finally	finally	ADV
ajst-11953	14	2	,	,	PUNCT
ajst-11953	14	3	the	the	DET
ajst-11953	14	4	voting	voting	NOUN
ajst-11953	14	5	result	result	NOUN
ajst-11953	14	6	is	be	AUX
ajst-11953	14	7	counted	count	VERB
ajst-11953	14	8	,	,	PUNCT
ajst-11953	14	9	and	and	CCONJ
ajst-11953	14	10	the	the	DET
ajst-11953	14	11	category	category	NOUN
ajst-11953	14	12	with	with	ADP
ajst-11953	14	13	the	the	DET
ajst-11953	14	14	most	most	ADJ
ajst-11953	14	15	votes	vote	NOUN
ajst-11953	14	16	is	be	AUX
ajst-11953	14	17	the	the	DET
ajst-11953	14	18	category	category	NOUN
ajst-11953	14	19	of	of	ADP
ajst-11953	14	20	the	the	DET
ajst-11953	14	21	unknown	unknown	ADJ
ajst-11953	14	22	data	datum	NOUN
ajst-11953	14	23	.	.	PUNCT
ajst-11953	15	1	2.3	2.3	NUM
ajst-11953	15	2	.	.	PUNCT
ajst-11953	16	1	dag	dag	PROPN
ajst-11953	16	2	method	method	NOUN
ajst-11953	16	3	the	the	DET
ajst-11953	16	4	dag	dag	PROPN
ajst-11953	16	5	method	method	NOUN
ajst-11953	16	6	is	be	AUX
ajst-11953	16	7	proposed	propose	VERB
ajst-11953	16	8	to	to	PART
ajst-11953	16	9	address	address	VERB
ajst-11953	16	10	some	some	DET
ajst-11953	16	11	shortcomings	shortcoming	NOUN
ajst-11953	16	12	of	of	ADP
ajst-11953	16	13	the	the	DET
ajst-11953	16	14	"	"	PUNCT
ajst-11953	16	15	one	one	NUM
ajst-11953	16	16	-	-	PUNCT
ajst-11953	16	17	to	to	ADP
ajst-11953	16	18	-	-	PUNCT
ajst-11953	16	19	one	one	NUM
ajst-11953	16	20	"	"	PUNCT
ajst-11953	16	21	method.the	method.the	DET
ajst-11953	16	22	strategy	strategy	NOUN
ajst-11953	16	23	adopted	adopt	VERB
ajst-11953	16	24	in	in	ADP
ajst-11953	16	25	the	the	DET
ajst-11953	16	26	training	training	NOUN
ajst-11953	16	27	stage	stage	NOUN
ajst-11953	16	28	is	be	AUX
ajst-11953	16	29	the	the	DET
ajst-11953	16	30	same	same	ADJ
ajst-11953	16	31	as	as	ADP
ajst-11953	16	32	the	the	DET
ajst-11953	16	33	"	"	PUNCT
ajst-11953	16	34	one	one	NUM
ajst-11953	16	35	-	-	PUNCT
ajst-11953	16	36	to	to	ADP
ajst-11953	16	37	-	-	PUNCT
ajst-11953	16	38	one	one	NUM
ajst-11953	16	39	"	"	PUNCT
ajst-11953	16	40	method	method	NOUN
ajst-11953	16	41	,	,	PUNCT
ajst-11953	16	42	that	that	ADV
ajst-11953	16	43	is	is	ADV
ajst-11953	16	44	,	,	PUNCT
ajst-11953	16	45	for	for	ADP
ajst-11953	16	46	the	the	DET
ajst-11953	16	47	problem	problem	NOUN
ajst-11953	16	48	with	with	ADP
ajst-11953	16	49	n	n	ADP
ajst-11953	16	50	categories	category	NOUN
ajst-11953	16	51	to	to	PART
ajst-11953	16	52	be	be	AUX
ajst-11953	16	53	divided	divide	VERB
ajst-11953	16	54	,	,	PUNCT
ajst-11953	16	55	a	a	DET
ajst-11953	16	56	binary	binary	ADJ
ajst-11953	16	57	support	support	NOUN
ajst-11953	16	58	vector	vector	NOUN
ajst-11953	16	59	machine	machine	NOUN
ajst-11953	16	60	is	be	AUX
ajst-11953	16	61	still	still	ADV
ajst-11953	16	62	constructed.when	constructed.when	PRON
ajst-11953	16	63	the	the	DET
ajst-11953	16	64	unknown	unknown	ADJ
ajst-11953	16	65	data	datum	NOUN
ajst-11953	16	66	is	be	AUX
ajst-11953	16	67	classified	classified	ADJ
ajst-11953	16	68	,	,	PUNCT
ajst-11953	16	69	it	it	PRON
ajst-11953	16	70	is	be	AUX
ajst-11953	16	71	realized	realize	VERB
ajst-11953	16	72	by	by	ADP
ajst-11953	16	73	directed	direct	VERB
ajst-11953	16	74	acyclic	acyclic	ADJ
ajst-11953	16	75	graph	graph	NOUN
ajst-11953	16	76	.	.	PUNCT
ajst-11953	17	1	in	in	ADP
ajst-11953	17	2	view	view	NOUN
ajst-11953	17	3	of	of	ADP
ajst-11953	17	4	the	the	DET
ajst-11953	17	5	characteristics	characteristic	NOUN
ajst-11953	17	6	of	of	ADP
ajst-11953	17	7	the	the	DET
ajst-11953	17	8	three	three	NUM
ajst-11953	17	9	methods	method	NOUN
ajst-11953	17	10	to	to	PART
ajst-11953	17	11	solve	solve	VERB
ajst-11953	17	12	the	the	DET
ajst-11953	17	13	multi	multi	ADJ
ajst-11953	17	14	-	-	ADJ
ajst-11953	17	15	classification	classification	ADJ
ajst-11953	17	16	problem	problem	NOUN
ajst-11953	17	17	,	,	PUNCT
ajst-11953	17	18	this	this	DET
ajst-11953	17	19	chapter	chapter	NOUN
ajst-11953	17	20	adopts	adopt	VERB
ajst-11953	17	21	dag	dag	PROPN
ajst-11953	17	22	method	method	NOUN
ajst-11953	17	23	in	in	ADP
ajst-11953	17	24	the	the	DET
ajst-11953	17	25	experimental	experimental	ADJ
ajst-11953	17	26	part	part	NOUN
ajst-11953	17	27	to	to	PART
ajst-11953	17	28	obtain	obtain	VERB
ajst-11953	17	29	high	high	ADJ
ajst-11953	17	30	classification	classification	NOUN
ajst-11953	17	31	accuracy	accuracy	NOUN
ajst-11953	17	32	and	and	CCONJ
ajst-11953	17	33	unique	unique	ADJ
ajst-11953	17	34	classification	classification	NOUN
ajst-11953	17	35	results	result	NOUN
ajst-11953	17	36	.	.	PUNCT
ajst-11953	18	1	3	3	X
ajst-11953	18	2	.	.	X
ajst-11953	18	3	experimental	experimental	ADJ
ajst-11953	18	4	data	datum	NOUN
ajst-11953	18	5	processing	process	VERB
ajst-11953	18	6	3.1	3.1	NUM
ajst-11953	18	7	.	.	PUNCT
ajst-11953	18	8	selection	selection	NOUN
ajst-11953	18	9	of	of	ADP
ajst-11953	18	10	experimental	experimental	ADJ
ajst-11953	18	11	data	datum	NOUN
ajst-11953	18	12	the	the	DET
ajst-11953	18	13	experimental	experimental	ADJ
ajst-11953	18	14	data	datum	NOUN
ajst-11953	18	15	were	be	AUX
ajst-11953	18	16	taken	take	VERB
ajst-11953	18	17	from	from	ADP
ajst-11953	18	18	a	a	DET
ajst-11953	18	19	part	part	NOUN
ajst-11953	18	20	of	of	ADP
ajst-11953	18	21	the	the	DET
ajst-11953	18	22	highspatial	highspatial	ADJ
ajst-11953	18	23	resolution	resolution	NOUN
ajst-11953	18	24	remote	remote	ADJ
ajst-11953	18	25	sensing	sense	VERB
ajst-11953	18	26	image	image	NOUN
ajst-11953	18	27	taken	take	VERB
ajst-11953	18	28	by	by	ADP
ajst-11953	18	29	worldview2	worldview2	PROPN
ajst-11953	18	30	satellite	satellite	NOUN
ajst-11953	18	31	,	,	PUNCT
ajst-11953	18	32	the	the	DET
ajst-11953	18	33	image	image	NOUN
ajst-11953	18	34	size	size	NOUN
ajst-11953	18	35	was	be	AUX
ajst-11953	18	36	,	,	PUNCT
ajst-11953	18	37	and	and	CCONJ
ajst-11953	18	38	the	the	DET
ajst-11953	18	39	spatial	spatial	ADJ
ajst-11953	18	40	resolution	resolution	NOUN
ajst-11953	18	41	of	of	ADP
ajst-11953	18	42	the	the	DET
ajst-11953	18	43	image	image	NOUN
ajst-11953	18	44	was	be	AUX
ajst-11953	18	45	0.5	0.5	NUM
ajst-11953	18	46	meters	meter	NOUN
ajst-11953	18	47	.	.	PUNCT
ajst-11953	19	1	in	in	ADP
ajst-11953	19	2	the	the	DET
ajst-11953	19	3	experiment	experiment	NOUN
ajst-11953	19	4	,	,	PUNCT
ajst-11953	19	5	the	the	DET
ajst-11953	19	6	spectral	spectral	ADJ
ajst-11953	19	7	values	value	NOUN
ajst-11953	19	8	of	of	ADP
ajst-11953	19	9	three	three	NUM
ajst-11953	19	10	visible	visible	ADJ
ajst-11953	19	11	bands	band	NOUN
ajst-11953	19	12	,	,	PUNCT
ajst-11953	19	13	red	red	ADJ
ajst-11953	19	14	,	,	PUNCT
ajst-11953	19	15	green	green	ADJ
ajst-11953	19	16	and	and	CCONJ
ajst-11953	19	17	blue	blue	ADJ
ajst-11953	19	18	,	,	PUNCT
ajst-11953	19	19	were	be	AUX
ajst-11953	19	20	selected	select	VERB
ajst-11953	19	21	as	as	SCONJ
ajst-11953	19	22	the	the	DET
ajst-11953	19	23	spectral	spectral	ADJ
ajst-11953	19	24	characteristics	characteristic	NOUN
ajst-11953	19	25	of	of	ADP
ajst-11953	19	26	the	the	DET
ajst-11953	19	27	image.the	image.the	DET
ajst-11953	19	28	image	image	NOUN
ajst-11953	19	29	is	be	AUX
ajst-11953	19	30	shown	show	VERB
ajst-11953	19	31	in	in	ADP
ajst-11953	19	32	figure	figure	NOUN
ajst-11953	19	33	1	1	NUM
ajst-11953	19	34	.	.	SYM
ajst-11953	19	35	112	112	NUM
ajst-11953	19	36	figure	figure	NOUN
ajst-11953	19	37	1	1	NUM
ajst-11953	19	38	.	.	PUNCT
ajst-11953	19	39	experimental	experimental	ADJ
ajst-11953	19	40	image	image	NOUN
ajst-11953	19	41	3.2	3.2	NUM
ajst-11953	19	42	.	.	PUNCT
ajst-11953	20	1	selection	selection	NOUN
ajst-11953	20	2	of	of	ADP
ajst-11953	20	3	training	training	NOUN
ajst-11953	20	4	samples	sample	NOUN
ajst-11953	20	5	training	training	NOUN
ajst-11953	20	6	samples	sample	NOUN
ajst-11953	20	7	were	be	AUX
ajst-11953	20	8	selected	select	VERB
ajst-11953	20	9	for	for	ADP
ajst-11953	20	10	the	the	DET
ajst-11953	20	11	five	five	NUM
ajst-11953	20	12	types	type	NOUN
ajst-11953	20	13	of	of	ADP
ajst-11953	20	14	objectives	objective	NOUN
ajst-11953	20	15	according	accord	VERB
ajst-11953	20	16	to	to	ADP
ajst-11953	20	17	the	the	DET
ajst-11953	20	18	following	following	ADJ
ajst-11953	20	19	principles	principle	NOUN
ajst-11953	20	20	:	:	PUNCT
ajst-11953	20	21	(	(	PUNCT
ajst-11953	20	22	1	1	X
ajst-11953	20	23	)	)	PUNCT
ajst-11953	20	24	the	the	DET
ajst-11953	20	25	spatial	spatial	ADJ
ajst-11953	20	26	distribution	distribution	NOUN
ajst-11953	20	27	of	of	ADP
ajst-11953	20	28	training	training	NOUN
ajst-11953	20	29	samples	sample	NOUN
ajst-11953	20	30	is	be	AUX
ajst-11953	20	31	relatively	relatively	ADV
ajst-11953	20	32	uniform	uniform	ADJ
ajst-11953	20	33	to	to	PART
ajst-11953	20	34	avoid	avoid	VERB
ajst-11953	20	35	overlapping	overlap	VERB
ajst-11953	20	36	areas	area	NOUN
ajst-11953	20	37	.	.	PUNCT
ajst-11953	21	1	(	(	PUNCT
ajst-11953	21	2	2	2	X
ajst-11953	21	3	)	)	PUNCT
ajst-11953	21	4	the	the	DET
ajst-11953	21	5	training	training	NOUN
ajst-11953	21	6	samples	sample	NOUN
ajst-11953	21	7	should	should	AUX
ajst-11953	21	8	be	be	AUX
ajst-11953	21	9	as	as	ADV
ajst-11953	21	10	representative	representative	ADJ
ajst-11953	21	11	as	as	ADP
ajst-11953	21	12	possible	possible	ADJ
ajst-11953	21	13	,	,	PUNCT
ajst-11953	21	14	that	that	ADV
ajst-11953	21	15	is	is	ADV
ajst-11953	21	16	,	,	PUNCT
ajst-11953	21	17	the	the	DET
ajst-11953	21	18	quality	quality	NOUN
ajst-11953	21	19	of	of	ADP
ajst-11953	21	20	the	the	DET
ajst-11953	21	21	samples	sample	NOUN
ajst-11953	21	22	should	should	AUX
ajst-11953	21	23	be	be	AUX
ajst-11953	21	24	high	high	ADJ
ajst-11953	21	25	.	.	PUNCT
ajst-11953	22	1	(	(	PUNCT
ajst-11953	22	2	3	3	X
ajst-11953	22	3	)	)	PUNCT
ajst-11953	22	4	the	the	DET
ajst-11953	22	5	number	number	NOUN
ajst-11953	22	6	of	of	ADP
ajst-11953	22	7	training	training	NOUN
ajst-11953	22	8	samples	sample	NOUN
ajst-11953	22	9	is	be	AUX
ajst-11953	22	10	less	less	ADJ
ajst-11953	22	11	than	than	ADP
ajst-11953	22	12	the	the	DET
ajst-11953	22	13	total	total	ADJ
ajst-11953	22	14	pixel	pixel	NOUN
ajst-11953	22	15	number	number	NOUN
ajst-11953	22	16	of	of	ADP
ajst-11953	22	17	the	the	DET
ajst-11953	22	18	image	image	NOUN
ajst-11953	22	19	,	,	PUNCT
ajst-11953	22	20	so	so	SCONJ
ajst-11953	22	21	as	as	SCONJ
ajst-11953	22	22	to	to	PART
ajst-11953	22	23	test	test	VERB
ajst-11953	22	24	the	the	DET
ajst-11953	22	25	ability	ability	NOUN
ajst-11953	22	26	of	of	ADP
ajst-11953	22	27	svm	svm	NOUN
ajst-11953	22	28	to	to	PART
ajst-11953	22	29	solve	solve	VERB
ajst-11953	22	30	the	the	DET
ajst-11953	22	31	classification	classification	NOUN
ajst-11953	22	32	in	in	ADP
ajst-11953	22	33	the	the	DET
ajst-11953	22	34	case	case	NOUN
ajst-11953	22	35	of	of	ADP
ajst-11953	22	36	small	small	ADJ
ajst-11953	22	37	samples	sample	NOUN
ajst-11953	22	38	.	.	PUNCT
ajst-11953	23	1	the	the	DET
ajst-11953	23	2	number	number	NOUN
ajst-11953	23	3	of	of	ADP
ajst-11953	23	4	training	training	NOUN
ajst-11953	23	5	samples	sample	NOUN
ajst-11953	23	6	and	and	CCONJ
ajst-11953	23	7	populations	population	NOUN
ajst-11953	23	8	for	for	ADP
ajst-11953	23	9	each	each	DET
ajst-11953	23	10	category	category	NOUN
ajst-11953	23	11	is	be	AUX
ajst-11953	23	12	shown	show	VERB
ajst-11953	23	13	in	in	ADP
ajst-11953	23	14	the	the	DET
ajst-11953	23	15	following	follow	VERB
ajst-11953	23	16	table	table	NOUN
ajst-11953	23	17	.	.	PUNCT
ajst-11953	24	1	table	table	NOUN
ajst-11953	24	2	1	1	NUM
ajst-11953	24	3	.	.	PUNCT
ajst-11953	25	1	the	the	DET
ajst-11953	25	2	classification	classification	NOUN
ajst-11953	25	3	results	result	VERB
ajst-11953	25	4	category	category	NOUN
ajst-11953	25	5	the	the	DET
ajst-11953	25	6	training	training	NOUN
ajst-11953	25	7	sample	sample	NOUN
ajst-11953	25	8	the	the	DET
ajst-11953	25	9	overall	overall	ADJ
ajst-11953	25	10	building	build	VERB
ajst-11953	25	11	820	820	NUM
ajst-11953	25	12	66275	66275	NUM
ajst-11953	25	13	road	road	NOUN
ajst-11953	25	14	403	403	NUM
ajst-11953	25	15	45475	45475	NUM
ajst-11953	25	16	vegetation	vegetation	NOUN
ajst-11953	25	17	398	398	NUM
ajst-11953	25	18	53027	53027	NUM
ajst-11953	25	19	shadow	shadow	NOUN
ajst-11953	25	20	374	374	NUM
ajst-11953	25	21	21487	21487	NUM
ajst-11953	25	22	water	water	NOUN
ajst-11953	25	23	405	405	NUM
ajst-11953	25	24	37516	37516	NUM
ajst-11953	25	25	oa	oa	PROPN
ajst-11953	25	26	2400	2400	NUM
ajst-11953	25	27	223780	223780	NUM
ajst-11953	25	28	the	the	DET
ajst-11953	25	29	histogram	histogram	NOUN
ajst-11953	25	30	of	of	ADP
ajst-11953	25	31	spectral	spectral	ADJ
ajst-11953	25	32	characteristics	characteristic	NOUN
ajst-11953	25	33	of	of	ADP
ajst-11953	25	34	each	each	DET
ajst-11953	25	35	band	band	NOUN
ajst-11953	25	36	of	of	ADP
ajst-11953	25	37	training	training	NOUN
ajst-11953	25	38	samples	sample	NOUN
ajst-11953	25	39	of	of	ADP
ajst-11953	25	40	each	each	DET
ajst-11953	25	41	category	category	NOUN
ajst-11953	25	42	is	be	AUX
ajst-11953	25	43	shown	show	VERB
ajst-11953	25	44	in	in	ADP
ajst-11953	25	45	the	the	DET
ajst-11953	25	46	figure	figure	NOUN
ajst-11953	25	47	below	below	ADV
ajst-11953	25	48	.	.	PUNCT
ajst-11953	26	1	a	a	DET
ajst-11953	26	2	histogram	histogram	NOUN
ajst-11953	26	3	of	of	ADP
ajst-11953	26	4	rgb	rgb	PROPN
ajst-11953	26	5	band	band	NOUN
ajst-11953	26	6	of	of	ADP
ajst-11953	26	7	building	building	NOUN
ajst-11953	26	8	samples	sample	NOUN
ajst-11953	26	9	b	b	NOUN
ajst-11953	26	10	histogram	histogram	NOUN
ajst-11953	26	11	of	of	ADP
ajst-11953	26	12	rgb	rgb	PROPN
ajst-11953	26	13	band	band	NOUN
ajst-11953	26	14	of	of	ADP
ajst-11953	26	15	cement	cement	NOUN
ajst-11953	26	16	pavement	pavement	NOUN
ajst-11953	26	17	samples	sample	NOUN
ajst-11953	26	18	c	c	NOUN
ajst-11953	26	19	histogram	histogram	NOUN
ajst-11953	26	20	of	of	ADP
ajst-11953	26	21	rgb	rgb	PROPN
ajst-11953	26	22	band	band	NOUN
ajst-11953	26	23	of	of	ADP
ajst-11953	26	24	vegetation	vegetation	NOUN
ajst-11953	26	25	samples	sample	NOUN
ajst-11953	26	26	d	d	X
ajst-11953	26	27	shadow	shadow	PROPN
ajst-11953	26	28	sample	sample	PROPN
ajst-11953	26	29	rgb	rgb	PROPN
ajst-11953	26	30	band	band	PROPN
ajst-11953	26	31	histogram	histogram	NOUN
ajst-11953	26	32	e	e	PROPN
ajst-11953	26	33	histogram	histogram	NOUN
ajst-11953	26	34	of	of	ADP
ajst-11953	26	35	rgb	rgb	PROPN
ajst-11953	26	36	band	band	NOUN
ajst-11953	26	37	of	of	ADP
ajst-11953	26	38	water	water	NOUN
ajst-11953	26	39	samples	sample	NOUN
ajst-11953	26	40	figure	figure	VERB
ajst-11953	26	41	2	2	NUM
ajst-11953	26	42	.	.	PUNCT
ajst-11953	26	43	histogram	histogram	NOUN
ajst-11953	26	44	of	of	ADP
ajst-11953	26	45	samples	sample	NOUN
ajst-11953	26	46	classified	classify	VERB
ajst-11953	26	47	in	in	ADP
ajst-11953	26	48	different	different	ADJ
ajst-11953	26	49	bands	band	NOUN
ajst-11953	26	50	from	from	ADP
ajst-11953	26	51	the	the	DET
ajst-11953	26	52	rgb	rgb	PROPN
ajst-11953	26	53	band	band	NOUN
ajst-11953	26	54	histogram	histogram	NOUN
ajst-11953	26	55	of	of	ADP
ajst-11953	26	56	each	each	DET
ajst-11953	26	57	sample	sample	NOUN
ajst-11953	26	58	,	,	PUNCT
ajst-11953	26	59	it	it	PRON
ajst-11953	26	60	can	can	AUX
ajst-11953	26	61	be	be	AUX
ajst-11953	26	62	found	find	VERB
ajst-11953	26	63	that	that	SCONJ
ajst-11953	26	64	:	:	PUNCT
ajst-11953	26	65	the	the	DET
ajst-11953	26	66	distribution	distribution	NOUN
ajst-11953	26	67	of	of	ADP
ajst-11953	26	68	spectral	spectral	ADJ
ajst-11953	26	69	features	feature	NOUN
ajst-11953	26	70	of	of	ADP
ajst-11953	26	71	building	building	NOUN
ajst-11953	26	72	samples	sample	NOUN
ajst-11953	26	73	is	be	AUX
ajst-11953	26	74	complex;vegetation	complex;vegetation	NOUN
ajst-11953	26	75	samples	sample	NOUN
ajst-11953	26	76	and	and	CCONJ
ajst-11953	26	77	shadow	shadow	VERB
ajst-11953	26	78	samples	sample	NOUN
ajst-11953	26	79	and	and	CCONJ
ajst-11953	26	80	water	water	NOUN
ajst-11953	26	81	samples	sample	NOUN
ajst-11953	26	82	have	have	VERB
ajst-11953	26	83	more	more	ADJ
ajst-11953	26	84	spectral	spectral	ADJ
ajst-11953	26	85	features	feature	NOUN
ajst-11953	26	86	overlap;the	overlap;the	DET
ajst-11953	26	87	difference	difference	NOUN
ajst-11953	26	88	of	of	ADP
ajst-11953	26	89	spectral	spectral	ADJ
ajst-11953	26	90	characteristics	characteristic	NOUN
ajst-11953	26	91	between	between	ADP
ajst-11953	26	92	cement	cement	NOUN
ajst-11953	26	93	pavement	pavement	NOUN
ajst-11953	26	94	samples	sample	NOUN
ajst-11953	26	95	and	and	CCONJ
ajst-11953	26	96	shadow	shadow	NOUN
ajst-11953	26	97	samples	sample	NOUN
ajst-11953	26	98	is	be	AUX
ajst-11953	26	99	the	the	DET
ajst-11953	26	100	largest.the	largest.the	DET
ajst-11953	26	101	spectral	spectral	ADJ
ajst-11953	26	102	distribution	distribution	NOUN
ajst-11953	26	103	of	of	ADP
ajst-11953	26	104	cement	cement	NOUN
ajst-11953	26	105	pavement	pavement	NOUN
ajst-11953	26	106	samples	sample	NOUN
ajst-11953	26	107	and	and	CCONJ
ajst-11953	26	108	water	water	NOUN
ajst-11953	26	109	samples	sample	NOUN
ajst-11953	26	110	is	be	AUX
ajst-11953	26	111	relatively	relatively	ADV
ajst-11953	26	112	independent	independent	ADJ
ajst-11953	26	113	.	.	PUNCT
ajst-11953	27	1	3.3	3.3	NUM
ajst-11953	27	2	.	.	PUNCT
ajst-11953	28	1	support	support	NOUN
ajst-11953	28	2	vector	vector	NOUN
ajst-11953	28	3	machine	machine	NOUN
ajst-11953	28	4	classification	classification	NOUN
ajst-11953	28	5	according	accord	VERB
ajst-11953	28	6	to	to	ADP
ajst-11953	28	7	the	the	DET
ajst-11953	28	8	comparison	comparison	NOUN
ajst-11953	28	9	of	of	ADP
ajst-11953	28	10	three	three	NUM
ajst-11953	28	11	multi	multi	ADJ
ajst-11953	28	12	-	-	ADJ
ajst-11953	28	13	classification	classification	ADJ
ajst-11953	28	14	strategies	strategy	NOUN
ajst-11953	28	15	of	of	ADP
ajst-11953	28	16	support	support	NOUN
ajst-11953	28	17	vector	vector	NOUN
ajst-11953	28	18	machines	machine	NOUN
ajst-11953	28	19	,	,	PUNCT
ajst-11953	28	20	it	it	PRON
ajst-11953	28	21	can	can	AUX
ajst-11953	28	22	be	be	AUX
ajst-11953	28	23	found	find	VERB
ajst-11953	28	24	that	that	SCONJ
ajst-11953	28	25	dag	dag	PROPN
ajst-11953	28	26	avoids	avoid	VERB
ajst-11953	28	27	the	the	DET
ajst-11953	28	28	phenomenon	phenomenon	NOUN
ajst-11953	28	29	of	of	ADP
ajst-11953	28	30	classification	classification	NOUN
ajst-11953	28	31	overlap	overlap	NOUN
ajst-11953	28	32	,	,	PUNCT
ajst-11953	28	33	unclassification	unclassification	NOUN
ajst-11953	28	34	and	and	CCONJ
ajst-11953	28	35	data	datum	NOUN
ajst-11953	28	36	set	set	NOUN
ajst-11953	28	37	bias	bias	NOUN
ajst-11953	28	38	,	,	PUNCT
ajst-11953	28	39	and	and	CCONJ
ajst-11953	28	40	at	at	ADP
ajst-11953	28	41	the	the	DET
ajst-11953	28	42	same	same	ADJ
ajst-11953	28	43	time	time	NOUN
ajst-11953	28	44	has	have	VERB
ajst-11953	28	45	higher	high	ADJ
ajst-11953	28	46	classification	classification	NOUN
ajst-11953	28	47	efficiency.on	efficiency.on	PRON
ajst-11953	28	48	the	the	DET
ajst-11953	28	49	other	other	ADJ
ajst-11953	28	50	hand	hand	NOUN
ajst-11953	28	51	,	,	PUNCT
ajst-11953	28	52	in	in	ADP
ajst-11953	28	53	order	order	NOUN
ajst-11953	28	54	to	to	PART
ajst-11953	28	55	improve	improve	VERB
ajst-11953	28	56	the	the	DET
ajst-11953	28	57	classification	classification	NOUN
ajst-11953	28	58	accuracy	accuracy	NOUN
ajst-11953	28	59	of	of	ADP
ajst-11953	28	60	dag	dag	PROPN
ajst-11953	28	61	method	method	NOUN
ajst-11953	28	62	,	,	PUNCT
ajst-11953	28	63	it	it	PRON
ajst-11953	28	64	is	be	AUX
ajst-11953	28	65	necessary	necessary	ADJ
ajst-11953	28	66	to	to	PART
ajst-11953	28	67	select	select	VERB
ajst-11953	28	68	the	the	DET
ajst-11953	28	69	root	root	NOUN
ajst-11953	28	70	node	node	NOUN
ajst-11953	28	71	before	before	SCONJ
ajst-11953	28	72	classification.as	classification.as	PROPN
ajst-11953	28	73	can	can	AUX
ajst-11953	28	74	be	be	AUX
ajst-11953	28	75	seen	see	VERB
ajst-11953	28	76	from	from	ADP
ajst-11953	28	77	fig	fig	NOUN
ajst-11953	28	78	.	.	PUNCT
ajst-11953	29	1	2.8	2.8	NUM
ajst-11953	29	2	,	,	PUNCT
ajst-11953	29	3	there	there	PRON
ajst-11953	29	4	is	be	VERB
ajst-11953	29	5	a	a	DET
ajst-11953	29	6	significant	significant	ADJ
ajst-11953	29	7	spectral	spectral	ADJ
ajst-11953	29	8	gap	gap	NOUN
ajst-11953	29	9	113	113	NUM
ajst-11953	29	10	between	between	ADP
ajst-11953	29	11	the	the	DET
ajst-11953	29	12	training	training	NOUN
ajst-11953	29	13	samples	sample	NOUN
ajst-11953	29	14	of	of	ADP
ajst-11953	29	15	cement	cement	NOUN
ajst-11953	29	16	road	road	NOUN
ajst-11953	29	17	surface	surface	NOUN
ajst-11953	29	18	and	and	CCONJ
ajst-11953	29	19	shadow	shadow	NOUN
ajst-11953	29	20	,	,	PUNCT
ajst-11953	29	21	which	which	PRON
ajst-11953	29	22	means	mean	VERB
ajst-11953	29	23	that	that	SCONJ
ajst-11953	29	24	the	the	DET
ajst-11953	29	25	support	support	NOUN
ajst-11953	29	26	vector	vector	NOUN
ajst-11953	29	27	opportunity	opportunity	NOUN
ajst-11953	29	28	constructed	construct	VERB
ajst-11953	29	29	with	with	ADP
ajst-11953	29	30	these	these	DET
ajst-11953	29	31	two	two	NUM
ajst-11953	29	32	types	type	NOUN
ajst-11953	29	33	of	of	ADP
ajst-11953	29	34	training	training	NOUN
ajst-11953	29	35	samples	sample	NOUN
ajst-11953	29	36	has	have	VERB
ajst-11953	29	37	the	the	DET
ajst-11953	29	38	highest	high	ADJ
ajst-11953	29	39	classification	classification	NOUN
ajst-11953	29	40	accuracy	accuracy	NOUN
ajst-11953	29	41	,	,	PUNCT
ajst-11953	29	42	and	and	CCONJ
ajst-11953	29	43	the	the	DET
ajst-11953	29	44	root	root	NOUN
ajst-11953	29	45	node	node	NOUN
ajst-11953	29	46	can	can	AUX
ajst-11953	29	47	minimize	minimize	VERB
ajst-11953	29	48	the	the	DET
ajst-11953	29	49	accumulation	accumulation	NOUN
ajst-11953	29	50	of	of	ADP
ajst-11953	29	51	errors	error	NOUN
ajst-11953	29	52	.	.	PUNCT
ajst-11953	30	1	in	in	ADP
ajst-11953	30	2	view	view	NOUN
ajst-11953	30	3	of	of	ADP
ajst-11953	30	4	the	the	DET
ajst-11953	30	5	characteristics	characteristic	NOUN
ajst-11953	30	6	of	of	ADP
ajst-11953	30	7	the	the	DET
ajst-11953	30	8	four	four	NUM
ajst-11953	30	9	kernel	kernel	NOUN
ajst-11953	30	10	functions	function	NOUN
ajst-11953	30	11	,	,	PUNCT
ajst-11953	30	12	the	the	DET
ajst-11953	30	13	radial	radial	ADJ
ajst-11953	30	14	basis	basis	NOUN
ajst-11953	30	15	kernel	kernel	NOUN
ajst-11953	30	16	function	function	NOUN
ajst-11953	30	17	is	be	AUX
ajst-11953	30	18	selected	select	VERB
ajst-11953	30	19	as	as	SCONJ
ajst-11953	30	20	the	the	DET
ajst-11953	30	21	kernel	kernel	PROPN
ajst-11953	30	22	function	function	NOUN
ajst-11953	30	23	of	of	ADP
ajst-11953	30	24	support	support	NOUN
ajst-11953	30	25	vector	vector	NOUN
ajst-11953	30	26	machine.the	machine.the	PRON
ajst-11953	30	27	radial	radial	ADJ
ajst-11953	30	28	basis	basis	NOUN
ajst-11953	30	29	kernel	kernel	NOUN
ajst-11953	30	30	function	function	NOUN
ajst-11953	30	31	has	have	VERB
ajst-11953	30	32	two	two	NUM
ajst-11953	30	33	parameters	parameter	NOUN
ajst-11953	30	34	.	.	PUNCT
ajst-11953	31	1	one	one	NUM
ajst-11953	31	2	is	be	AUX
ajst-11953	31	3	the	the	DET
ajst-11953	31	4	parameter	parameter	NOUN
ajst-11953	31	5	in	in	ADP
ajst-11953	31	6	the	the	DET
ajst-11953	31	7	kernel	kernel	PROPN
ajst-11953	31	8	function	function	NOUN
ajst-11953	31	9	,	,	PUNCT
ajst-11953	31	10	i.e.	i.e.	X
ajst-11953	31	11	,	,	PUNCT
ajst-11953	31	12	in	in	ADP
ajst-11953	31	13	equation	equation	NOUN
ajst-11953	31	14	(	(	PUNCT
ajst-11953	31	15	23	23	NUM
ajst-11953	31	16	)	)	PUNCT
ajst-11953	31	17	,	,	PUNCT
ajst-11953	31	18	which	which	PRON
ajst-11953	31	19	can	can	AUX
ajst-11953	31	20	be	be	AUX
ajst-11953	31	21	regarded	regard	VERB
ajst-11953	31	22	as	as	ADP
ajst-11953	31	23	a	a	DET
ajst-11953	31	24	parameter	parameter	NOUN
ajst-11953	31	25	and	and	CCONJ
ajst-11953	31	26	denoted	denote	VERB
ajst-11953	31	27	as;the	as;the	DET
ajst-11953	31	28	other	other	ADJ
ajst-11953	31	29	is	be	AUX
ajst-11953	31	30	the	the	DET
ajst-11953	31	31	penalty	penalty	NOUN
ajst-11953	31	32	factor	factor	NOUN
ajst-11953	31	33	,	,	PUNCT
ajst-11953	31	34	which	which	PRON
ajst-11953	31	35	is	be	AUX
ajst-11953	31	36	in	in	ADP
ajst-11953	31	37	equation	equation	NOUN
ajst-11953	31	38	(	(	PUNCT
ajst-11953	31	39	20).for	20).for	NUM
ajst-11953	31	40	these	these	DET
ajst-11953	31	41	two	two	NUM
ajst-11953	31	42	parameters	parameter	NOUN
ajst-11953	31	43	,	,	PUNCT
ajst-11953	31	44	the	the	DET
ajst-11953	31	45	parameter	parameter	NOUN
ajst-11953	31	46	optimization	optimization	NOUN
ajst-11953	31	47	method	method	NOUN
ajst-11953	31	48	of	of	ADP
ajst-11953	31	49	particle	particle	NOUN
ajst-11953	31	50	swarm	swarm	NOUN
ajst-11953	31	51	optimization	optimization	NOUN
ajst-11953	31	52	(	(	PUNCT
ajst-11953	31	53	pso	pso	NOUN
ajst-11953	31	54	)	)	PUNCT
ajst-11953	31	55	was	be	AUX
ajst-11953	31	56	used	use	VERB
ajst-11953	31	57	in	in	ADP
ajst-11953	31	58	this	this	DET
ajst-11953	31	59	paper	paper	NOUN
ajst-11953	31	60	to	to	PART
ajst-11953	31	61	optimize	optimize	VERB
ajst-11953	31	62	,	,	PUNCT
ajst-11953	31	63	and	and	CCONJ
ajst-11953	31	64	the	the	DET
ajst-11953	31	65	optimal	optimal	ADJ
ajst-11953	31	66	parameters	parameter	NOUN
ajst-11953	31	67	obtained	obtain	VERB
ajst-11953	31	68	were	be	AUX
ajst-11953	31	69	shown	show	VERB
ajst-11953	31	70	in	in	ADP
ajst-11953	31	71	the	the	DET
ajst-11953	31	72	table	table	NOUN
ajst-11953	31	73	below	below	ADV
ajst-11953	31	74	.	.	PUNCT
ajst-11953	32	1	table	table	NOUN
ajst-11953	32	2	2	2	NUM
ajst-11953	32	3	.	.	PUNCT
ajst-11953	32	4	classification	classification	NOUN
ajst-11953	32	5	accuracy	accuracy	NOUN
ajst-11953	32	6	table	table	NOUN
ajst-11953	32	7	category	category	NOUN
ajst-11953	32	8	building	build	VERB
ajst-11953	32	9	road	road	NOUN
ajst-11953	32	10	vegetation	vegetation	NOUN
ajst-11953	32	11	shadow	shadow	NOUN
ajst-11953	32	12	water	water	PROPN
ajst-11953	32	13	building	building	PROPN
ajst-11953	32	14	nan	nan	PROPN
ajst-11953	32	15	c=1.046	c=1.046	PUNCT
ajst-11953	32	16	g=49.613	g=49.613	NUM
ajst-11953	32	17	c=6.674	c=6.674	ADV
ajst-11953	32	18	g=50.677	g=50.677	PROPN
ajst-11953	32	19	c=4.174	c=4.174	ADP
ajst-11953	32	20	g=7.190	g=7.190	X
ajst-11953	32	21	c=1.040	c=1.040	NOUN
ajst-11953	32	22	g=20.846	g=20.846	PROPN
ajst-11953	32	23	road	road	NOUN
ajst-11953	32	24	c=1.046	c=1.046	PUNCT
ajst-11953	32	25	g=49.613	g=49.613	PROPN
ajst-11953	32	26	nan	nan	X
ajst-11953	32	27	c=0.771	c=0.771	X
ajst-11953	32	28	g=16.967	g=16.967	PROPN
ajst-11953	32	29	c=0.100	c=0.100	X
ajst-11953	32	30	g=64.749	g=64.749	PROPN
ajst-11953	32	31	c=7.472	c=7.472	X
ajst-11953	32	32	g=33.329	g=33.329	ADJ
ajst-11953	32	33	vegetation	vegetation	NOUN
ajst-11953	32	34	c=6.674	c=6.674	NOUN
ajst-11953	32	35	g=50.677	g=50.677	PROPN
ajst-11953	32	36	c=0.771	c=0.771	PROPN
ajst-11953	32	37	g=16.967	g=16.967	PROPN
ajst-11953	32	38	nan	nan	PROPN
ajst-11953	32	39	c=32.154	c=32.154	PROPN
ajst-11953	32	40	g=85.880	g=85.880	PROPN
ajst-11953	32	41	c=0.100	c=0.100	X
ajst-11953	32	42	g=87.161	g=87.161	ADJ
ajst-11953	32	43	shadow	shadow	PROPN
ajst-11953	32	44	c=4.174	c=4.174	X
ajst-11953	32	45	g=7.190	g=7.190	X
ajst-11953	32	46	c=0.100	c=0.100	X
ajst-11953	32	47	g=64.749	g=64.749	PRON
ajst-11953	32	48	c=32.154	c=32.154	X
ajst-11953	32	49	g=85.880	g=85.880	PROPN
ajst-11953	32	50	nan	nan	NOUN
ajst-11953	32	51	c=0.375	c=0.375	VERB
ajst-11953	32	52	g=49.235	g=49.235	PRON
ajst-11953	32	53	water	water	NOUN
ajst-11953	32	54	c=1.040	c=1.040	NOUN
ajst-11953	32	55	g=20.846	g=20.846	PROPN
ajst-11953	32	56	c=7.472	c=7.472	X
ajst-11953	32	57	g=33.329	g=33.329	X
ajst-11953	32	58	c=0.100	c=0.100	X
ajst-11953	32	59	g=87.161	g=87.161	X
ajst-11953	32	60	c=0.375	c=0.375	VERB
ajst-11953	32	61	g=49.235	g=49.235	NUM
ajst-11953	32	62	nan	nan	PROPN
ajst-11953	32	63	4	4	NUM
ajst-11953	32	64	.	.	PUNCT
ajst-11953	33	1	experimental	experimental	ADJ
ajst-11953	33	2	results	result	NOUN
ajst-11953	33	3	after	after	ADP
ajst-11953	33	4	the	the	DET
ajst-11953	33	5	determination	determination	NOUN
ajst-11953	33	6	of	of	ADP
ajst-11953	33	7	multiple	multiple	ADJ
ajst-11953	33	8	classification	classification	NOUN
ajst-11953	33	9	strategies	strategy	NOUN
ajst-11953	33	10	and	and	CCONJ
ajst-11953	33	11	the	the	DET
ajst-11953	33	12	optimization	optimization	NOUN
ajst-11953	33	13	of	of	ADP
ajst-11953	33	14	parameters	parameter	NOUN
ajst-11953	33	15	,	,	PUNCT
ajst-11953	33	16	the	the	DET
ajst-11953	33	17	images	image	NOUN
ajst-11953	33	18	were	be	AUX
ajst-11953	33	19	classified	classify	VERB
ajst-11953	33	20	by	by	ADP
ajst-11953	33	21	support	support	NOUN
ajst-11953	33	22	vector	vector	NOUN
ajst-11953	33	23	machine	machine	NOUN
ajst-11953	33	24	(	(	PUNCT
ajst-11953	33	25	svm	svm	PROPN
ajst-11953	33	26	)	)	PUNCT
ajst-11953	33	27	and	and	CCONJ
ajst-11953	33	28	the	the	DET
ajst-11953	33	29	results	result	NOUN
ajst-11953	33	30	in	in	ADP
ajst-11953	33	31	figure	figure	NOUN
ajst-11953	33	32	3	3	NUM
ajst-11953	33	33	were	be	AUX
ajst-11953	33	34	obtained	obtain	VERB
ajst-11953	33	35	classification	classification	NOUN
ajst-11953	33	36	accuracy	accuracy	NOUN
ajst-11953	33	37	=	=	NOUN
ajst-11953	33	38	70.97	70.97	NUM
ajst-11953	33	39	%	%	NOUN
ajst-11953	33	40	figure	figure	NOUN
ajst-11953	33	41	3	3	NUM
ajst-11953	33	42	.	.	PUNCT
ajst-11953	34	1	classification	classification	NOUN
ajst-11953	34	2	results	result	NOUN
ajst-11953	34	3	of	of	ADP
ajst-11953	34	4	spectral	spectral	ADJ
ajst-11953	34	5	features	feature	NOUN
ajst-11953	34	6	buildings	building	NOUN
ajst-11953	34	7	and	and	CCONJ
ajst-11953	34	8	cement	cement	NOUN
ajst-11953	34	9	pavements	pavement	NOUN
ajst-11953	34	10	in	in	ADP
ajst-11953	34	11	these	these	DET
ajst-11953	34	12	areas	area	NOUN
ajst-11953	34	13	have	have	VERB
ajst-11953	34	14	close	close	ADJ
ajst-11953	34	15	spectral	spectral	ADJ
ajst-11953	34	16	characteristics	characteristic	NOUN
ajst-11953	34	17	that	that	PRON
ajst-11953	34	18	are	be	AUX
ajst-11953	34	19	difficult	difficult	ADJ
ajst-11953	34	20	to	to	PART
ajst-11953	34	21	distinguish	distinguish	VERB
ajst-11953	34	22	by	by	ADP
ajst-11953	34	23	spectral	spectral	ADJ
ajst-11953	34	24	characteristics.similarly	characteristics.similarly	ADV
ajst-11953	34	25	,	,	PUNCT
ajst-11953	34	26	light	light	ADJ
ajst-11953	34	27	-	-	PUNCT
ajst-11953	34	28	colored	color	VERB
ajst-11953	34	29	vegetation	vegetation	NOUN
ajst-11953	34	30	is	be	AUX
ajst-11953	34	31	misclassified	misclassifie	VERB
ajst-11953	34	32	as	as	ADP
ajst-11953	34	33	a	a	DET
ajst-11953	34	34	body	body	NOUN
ajst-11953	34	35	of	of	ADP
ajst-11953	34	36	water	water	NOUN
ajst-11953	34	37	,	,	PUNCT
ajst-11953	34	38	and	and	CCONJ
ajst-11953	34	39	the	the	DET
ajst-11953	34	40	rippling	ripple	VERB
ajst-11953	34	41	locations	location	NOUN
ajst-11953	34	42	in	in	ADP
ajst-11953	34	43	the	the	DET
ajst-11953	34	44	water	water	NOUN
ajst-11953	34	45	are	be	AUX
ajst-11953	34	46	misclassified	misclassifie	VERB
ajst-11953	34	47	as	as	ADP
ajst-11953	34	48	concrete	concrete	ADJ
ajst-11953	34	49	pavements	pavement	NOUN
ajst-11953	34	50	and	and	CCONJ
ajst-11953	34	51	buildings.these	buildings.these	ADJ
ajst-11953	34	52	misclassification	misclassification	NOUN
ajst-11953	34	53	and	and	CCONJ
ajst-11953	34	54	salt	salt	NOUN
ajst-11953	34	55	-	-	PUNCT
ajst-11953	34	56	and	and	CCONJ
ajst-11953	34	57	-	-	PUNCT
ajst-11953	34	58	pepper	pepper	NOUN
ajst-11953	34	59	noise	noise	NOUN
ajst-11953	34	60	phenomena	phenomenon	NOUN
ajst-11953	34	61	in	in	ADP
ajst-11953	34	62	the	the	DET
ajst-11953	34	63	classification	classification	NOUN
ajst-11953	34	64	results	result	NOUN
ajst-11953	34	65	indicate	indicate	VERB
ajst-11953	34	66	that	that	SCONJ
ajst-11953	34	67	the	the	DET
ajst-11953	34	68	classification	classification	NOUN
ajst-11953	34	69	results	result	NOUN
ajst-11953	34	70	only	only	ADV
ajst-11953	34	71	relying	rely	VERB
ajst-11953	34	72	on	on	ADP
ajst-11953	34	73	spectral	spectral	ADJ
ajst-11953	34	74	features	feature	NOUN
ajst-11953	34	75	are	be	AUX
ajst-11953	34	76	not	not	PART
ajst-11953	34	77	reliable	reliable	ADJ
ajst-11953	34	78	,	,	PUNCT
ajst-11953	34	79	and	and	CCONJ
ajst-11953	34	80	other	other	ADJ
ajst-11953	34	81	features	feature	NOUN
ajst-11953	34	82	are	be	AUX
ajst-11953	34	83	needed	need	VERB
ajst-11953	34	84	to	to	PART
ajst-11953	34	85	supplement	supplement	VERB
ajst-11953	34	86	the	the	DET
ajst-11953	34	87	spectral	spectral	ADJ
ajst-11953	34	88	features	feature	NOUN
ajst-11953	34	89	to	to	PART
ajst-11953	34	90	enhance	enhance	VERB
ajst-11953	34	91	the	the	DET
ajst-11953	34	92	classification	classification	NOUN
ajst-11953	34	93	accuracy	accuracy	NOUN
ajst-11953	34	94	.	.	PUNCT
ajst-11953	35	1	acknowledgement	acknowledgement	NOUN
ajst-11953	35	2	supported	support	VERB
ajst-11953	35	3	by	by	ADP
ajst-11953	35	4	funded	fund	VERB
ajst-11953	35	5	by	by	ADP
ajst-11953	35	6	study	study	NOUN
ajst-11953	35	7	on	on	ADP
ajst-11953	35	8	spatial	spatial	ADJ
ajst-11953	35	9	and	and	CCONJ
ajst-11953	35	10	temporal	temporal	ADJ
ajst-11953	35	11	changes	change	NOUN
ajst-11953	35	12	of	of	ADP
ajst-11953	35	13	carbon	carbon	NOUN
ajst-11953	35	14	stock	stock	NOUN
ajst-11953	35	15	in	in	ADP
ajst-11953	35	16	the	the	DET
ajst-11953	35	17	northwest	northwest	ADJ
ajst-11953	35	18	agricultural	agricultural	ADJ
ajst-11953	35	19	and	and	CCONJ
ajst-11953	35	20	pastoral	pastoral	ADJ
ajst-11953	35	21	intertwined	intertwine	VERB
ajst-11953	35	22	zone	zone	NOUN
ajst-11953	35	23	based	base	VERB
ajst-11953	35	24	on	on	ADP
ajst-11953	35	25	invest	invest	VERB
ajst-11953	35	26	and	and	CCONJ
ajst-11953	35	27	ca	ca	NOUN
ajst-11953	35	28	-	-	PUNCT
ajst-11953	35	29	markov	markov	NOUN
ajst-11953	35	30	modeling（djny2022	modeling（djny2022	PROPN
ajst-11953	35	31	-	-	PUNCT
ajst-11953	35	32	21）and	21）and	NUM
ajst-11953	35	33	soil	soil	NOUN
ajst-11953	35	34	moisture	moisture	NOUN
ajst-11953	35	35	inversion	inversion	NOUN
ajst-11953	35	36	study	study	NOUN
ajst-11953	35	37	of	of	ADP
ajst-11953	35	38	the	the	DET
ajst-11953	35	39	loess	loess	NOUN
ajst-11953	35	40	plateau	plateau	NOUN
ajst-11953	35	41	dry	dry	ADJ
ajst-11953	35	42	plateau	plateau	NOUN
ajst-11953	35	43	based	base	VERB
ajst-11953	35	44	on	on	ADP
ajst-11953	35	45	sar	sar	PROPN
ajst-11953	35	46	radar	radar	PROPN
ajst-11953	35	47	data(djny2022	data(djny2022	PROPN
ajst-11953	35	48	-	-	PUNCT
ajst-11953	35	49	23).and	23).and	NUM
ajst-11953	35	50	key	key	ADJ
ajst-11953	35	51	research	research	NOUN
ajst-11953	35	52	and	and	CCONJ
ajst-11953	35	53	development	development	NOUN
ajst-11953	35	54	program	program	NOUN
ajst-11953	35	55	of	of	ADP
ajst-11953	35	56	shaanxi	shaanxi	PROPN
ajst-11953	35	57	under	under	ADP
ajst-11953	35	58	grant	grant	NOUN
ajst-11953	35	59	2022zdlny02	2022zdlny02	NUM
ajst-11953	35	60	-	-	SYM
ajst-11953	35	61	10	10	NUM
ajst-11953	35	62	.	.	PUNCT
ajst-11953	36	1	references	reference	NOUN
ajst-11953	36	2	[	[	X
ajst-11953	36	3	1	1	NUM
ajst-11953	36	4	]	]	X
ajst-11953	36	5	fan	fan	NOUN
ajst-11953	36	6	y	y	PROPN
ajst-11953	36	7	m	m	PROPN
ajst-11953	36	8	,	,	PUNCT
ajst-11953	36	9	zhao	zhao	PROPN
ajst-11953	36	10	l	l	PROPN
ajst-11953	36	11	l.	l.	PROPN
ajst-11953	36	12	research	research	PROPN
ajst-11953	36	13	on	on	ADP
ajst-11953	36	14	support	support	NOUN
ajst-11953	36	15	vector	vector	NOUN
ajst-11953	36	16	classification	classification	NOUN
ajst-11953	36	17	algorithm	algorithm	NOUN
ajst-11953	37	1	[	[	X
ajst-11953	37	2	j].journal	j].journal	NOUN
ajst-11953	37	3	of	of	ADP
ajst-11953	37	4	shijiazhuang	shijiazhuang	PROPN
ajst-11953	37	5	tiedao	tiedao	PROPN
ajst-11953	37	6	university	university	PROPN
ajst-11953	37	7	(	(	PUNCT
ajst-11953	37	8	natural	natural	ADJ
ajst-11953	37	9	science	science	NOUN
ajst-11953	37	10	edition	edition	NOUN
ajst-11953	37	11	)	)	PUNCT
ajst-11953	37	12	,	,	PUNCT
ajst-11953	37	13	2007	2007	NUM
ajst-11953	37	14	,	,	PUNCT
ajst-11953	37	15	20(3	20(3	NUM
ajst-11953	37	16	)	)	PUNCT
ajst-11953	37	17	:	:	PUNCT
ajst-11953	37	18	31	31	NUM
ajst-11953	37	19	-	-	SYM
ajst-11953	37	20	36	36	NUM
ajst-11953	37	21	.	.	PUNCT
ajst-11953	38	1	[	[	X
ajst-11953	38	2	2	2	NUM
ajst-11953	38	3	]	]	PUNCT
ajst-11953	38	4	du	du	PROPN
ajst-11953	38	5	shuxin	shuxin	PROPN
ajst-11953	38	6	,	,	PUNCT
ajst-11953	38	7	wu	wu	PROPN
ajst-11953	38	8	tiejun	tiejun	PROPN
ajst-11953	38	9	.	.	PUNCT
ajst-11953	39	1	support	support	NOUN
ajst-11953	39	2	vector	vector	NOUN
ajst-11953	39	3	machine	machine	NOUN
ajst-11953	39	4	method	method	NOUN
ajst-11953	39	5	for	for	ADP
ajst-11953	39	6	pattern	pattern	NOUN
ajst-11953	39	7	recognition	recognition	NOUN
ajst-11953	40	1	[	[	X
ajst-11953	40	2	j].journal	j].journal	NOUN
ajst-11953	40	3	of	of	ADP
ajst-11953	40	4	zhejiang	zhejiang	PROPN
ajst-11953	40	5	university	university	PROPN
ajst-11953	40	6	(	(	PUNCT
ajst-11953	40	7	engineering	engineering	NOUN
ajst-11953	40	8	science	science	NOUN
ajst-11953	40	9	)	)	PUNCT
ajst-11953	40	10	,	,	PUNCT
ajst-11953	40	11	2003	2003	NUM
ajst-11953	40	12	,	,	PUNCT
ajst-11953	40	13	37(5	37(5	NUM
ajst-11953	40	14	)	)	PUNCT
ajst-11953	40	15	:	:	PUNCT
ajst-11953	40	16	521	521	NUM
ajst-11953	40	17	-	-	SYM
ajst-11953	40	18	527	527	NUM
ajst-11953	40	19	.	.	PUNCT
ajst-11953	41	1	[	[	X
ajst-11953	41	2	3	3	X
ajst-11953	41	3	]	]	PUNCT
ajst-11953	41	4	ye	ye	PRON
ajst-11953	41	5	chenzhou	chenzhou	NOUN
ajst-11953	41	6	,	,	PUNCT
ajst-11953	41	7	yang	yang	PROPN
ajst-11953	41	8	jie	jie	PROPN
ajst-11953	41	9	,	,	PUNCT
ajst-11953	41	10	yao	yao	PROPN
ajst-11953	41	11	lixiu	lixiu	NOUN
ajst-11953	41	12	et	et	PROPN
ajst-11953	41	13	al	al	PROPN
ajst-11953	41	14	.	.	PROPN
ajst-11953	41	15	principle	principle	NOUN
ajst-11953	41	16	and	and	CCONJ
ajst-11953	41	17	application	application	NOUN
ajst-11953	41	18	of	of	ADP
ajst-11953	41	19	statistical	statistical	ADJ
ajst-11953	41	20	learning	learning	NOUN
ajst-11953	41	21	theory	theory	NOUN
ajst-11953	41	22	[	[	X
ajst-11953	41	23	j].computers	j].computer	NOUN
ajst-11953	41	24	and	and	CCONJ
ajst-11953	41	25	applied	apply	VERB
ajst-11953	41	26	chemistry	chemistry	NOUN
ajst-11953	41	27	,	,	PUNCT
ajst-11953	41	28	2002	2002	NUM
ajst-11953	41	29	,	,	PUNCT
ajst-11953	41	30	19(6	19(6	NUM
ajst-11953	41	31	)	)	PUNCT
ajst-11953	41	32	:	:	PUNCT
ajst-11953	41	33	712	712	NUM
ajst-11953	41	34	-	-	SYM
ajst-11953	41	35	716	716	NUM
ajst-11953	41	36	.	.	PUNCT
ajst-11953	42	1	[	[	X
ajst-11953	42	2	4	4	NUM
ajst-11953	42	3	]	]	X
ajst-11953	42	4	tan	tan	PROPN
ajst-11953	42	5	dongning	dongning	NOUN
ajst-11953	42	6	,	,	PUNCT
ajst-11953	42	7	tan	tan	PROPN
ajst-11953	42	8	donghan	donghan	ADV
ajst-11953	42	9	.	.	PUNCT
ajst-11953	43	1	small	small	ADJ
ajst-11953	43	2	sample	sample	NOUN
ajst-11953	43	3	machine	machine	NOUN
ajst-11953	43	4	learning	learn	VERB
ajst-11953	43	5	theory	theory	NOUN
ajst-11953	43	6	:	:	PUNCT
ajst-11953	43	7	statistical	statistical	ADJ
ajst-11953	43	8	learning	learning	NOUN
ajst-11953	43	9	theory	theory	NOUN
ajst-11953	43	10	[	[	X
ajst-11953	43	11	j].journal	j].journal	NOUN
ajst-11953	43	12	of	of	ADP
ajst-11953	43	13	nanjing	nanjing	PROPN
ajst-11953	43	14	university	university	PROPN
ajst-11953	43	15	of	of	ADP
ajst-11953	43	16	science	science	NOUN
ajst-11953	43	17	and	and	CCONJ
ajst-11953	43	18	technology	technology	NOUN
ajst-11953	43	19	,	,	PUNCT
ajst-11953	43	20	2001	2001	NUM
ajst-11953	43	21	,	,	PUNCT
ajst-11953	43	22	25(1	25(1	NUM
ajst-11953	43	23	)	)	PUNCT
ajst-11953	43	24	:	:	PUNCT
ajst-11953	43	25	108	108	NUM
ajst-11953	43	26	-	-	SYM
ajst-11953	43	27	112	112	NUM
ajst-11953	43	28	.	.	PUNCT
ajst-11953	44	1	[	[	X
ajst-11953	44	2	5	5	NUM
ajst-11953	44	3	]	]	PUNCT
ajst-11953	44	4	yu	yu	PROPN
ajst-11953	44	5	hui	hui	PROPN
ajst-11953	44	6	,	,	PUNCT
ajst-11953	44	7	zhao	zhao	PROPN
ajst-11953	44	8	hui	hui	PROPN
ajst-11953	44	9	.	.	PUNCT
ajst-11953	45	1	new	new	ADJ
ajst-11953	45	2	research	research	NOUN
ajst-11953	45	3	on	on	ADP
ajst-11953	45	4	multi	multi	ADJ
ajst-11953	45	5	-	-	ADJ
ajst-11953	45	6	class	class	ADJ
ajst-11953	45	7	classification	classification	NOUN
ajst-11953	45	8	algorithm	algorithm	NOUN
ajst-11953	45	9	of	of	ADP
ajst-11953	45	10	support	support	NOUN
ajst-11953	45	11	vector	vector	NOUN
ajst-11953	45	12	machines	machine	NOUN
ajst-11953	45	13	building	build	VERB
ajst-11953	45	14	roadt	roadt	ADJ
ajst-11953	45	15	vegetation	vegetation	NOUN
ajst-11953	45	16	shadow	shadow	NOUN
ajst-11953	45	17	water	water	NOUN
ajst-11953	45	18	114	114	NUM
ajst-11953	46	1	[	[	X
ajst-11953	46	2	j].computer	j].computer	NOUN
ajst-11953	46	3	engineering	engineering	NOUN
ajst-11953	46	4	and	and	CCONJ
ajst-11953	46	5	applications	application	NOUN
ajst-11953	46	6	,	,	PUNCT
ajst-11953	46	7	2008	2008	NUM
ajst-11953	46	8	,	,	PUNCT
ajst-11953	46	9	44(7	44(7	NOUN
ajst-11953	46	10	)	)	PUNCT
ajst-11953	46	11	:	:	PUNCT
ajst-11953	46	12	185189,212	185189,212	NUM
ajst-11953	46	13	.	.	PUNCT
ajst-11953	47	1	[	[	X
ajst-11953	47	2	6	6	NUM
ajst-11953	47	3	]	]	X
ajst-11953	47	4	burges	burge	NOUN
ajst-11953	47	5	c	c	PROPN
ajst-11953	47	6	j	j	PROPN
ajst-11953	47	7	c.	c.	PROPN
ajst-11953	47	8	a	a	DET
ajst-11953	47	9	tutorial	tutorial	NOUN
ajst-11953	47	10	on	on	ADP
ajst-11953	47	11	support	support	NOUN
ajst-11953	47	12	vector	vector	NOUN
ajst-11953	47	13	machines	machine	NOUN
ajst-11953	47	14	for	for	ADP
ajst-11953	47	15	pattern	pattern	NOUN
ajst-11953	47	16	recognition[j	recognition[j	NOUN
ajst-11953	47	17	]	]	PUNCT
ajst-11953	47	18	.	.	PUNCT
ajst-11953	48	1	data	datum	NOUN
ajst-11953	48	2	mining	mining	NOUN
ajst-11953	48	3	and	and	CCONJ
ajst-11953	48	4	knowledge	knowledge	NOUN
ajst-11953	48	5	discovery	discovery	NOUN
ajst-11953	48	6	,	,	PUNCT
ajst-11953	48	7	1998	1998	NUM
ajst-11953	48	8	,	,	PUNCT
ajst-11953	48	9	2(2	2(2	NUM
ajst-11953	48	10	)	)	PUNCT
ajst-11953	48	11	:	:	PUNCT
ajst-11953	48	12	121	121	NUM
ajst-11953	48	13	-	-	SYM
ajst-11953	48	14	167	167	NUM
ajst-11953	48	15	.	.	PUNCT
ajst-11953	49	1	[	[	X
ajst-11953	49	2	7	7	X
ajst-11953	49	3	]	]	X
ajst-11953	49	4	chapelle	chapelle	PROPN
ajst-11953	49	5	o	o	PROPN
ajst-11953	49	6	,	,	PUNCT
ajst-11953	49	7	vapnik	vapnik	X
ajst-11953	49	8	v.	v.	ADP
ajst-11953	49	9	choosing	choose	VERB
ajst-11953	49	10	multiple	multiple	ADJ
ajst-11953	49	11	parameters	parameter	NOUN
ajst-11953	49	12	for	for	ADP
ajst-11953	49	13	support	support	NOUN
ajst-11953	49	14	vector	vector	NOUN
ajst-11953	49	15	machines[j	machines[j	PROPN
ajst-11953	49	16	]	]	PUNCT
ajst-11953	49	17	.	.	PUNCT
ajst-11953	49	18	machine	machine	NOUN
ajst-11953	49	19	learning	learning	PROPN
ajst-11953	49	20	,	,	PUNCT
ajst-11953	49	21	2002	2002	NUM
ajst-11953	49	22	,	,	PUNCT
ajst-11953	49	23	46(13	46(13	NUM
ajst-11953	49	24	)	)	PUNCT
ajst-11953	49	25	:	:	PUNCT
ajst-11953	49	26	131	131	NUM
ajst-11953	49	27	-	-	SYM
ajst-11953	49	28	159	159	NUM
ajst-11953	49	29	.	.	PUNCT
ajst-11953	50	1	[	[	X
ajst-11953	50	2	8	8	NUM
ajst-11953	50	3	]	]	SYM
ajst-11953	50	4	ding	ding	NOUN
ajst-11953	50	5	shifei	shifei	NOUN
ajst-11953	50	6	,	,	PUNCT
ajst-11953	50	7	qi	qi	PROPN
ajst-11953	50	8	bingjuan	bingjuan	PROPN
ajst-11953	50	9	,	,	PUNCT
ajst-11953	50	10	tan	tan	PROPN
ajst-11953	50	11	hongyan	hongyan	PROPN
ajst-11953	50	12	.	.	PUNCT
ajst-11953	51	1	review	review	NOUN
ajst-11953	51	2	on	on	ADP
ajst-11953	51	3	theory	theory	NOUN
ajst-11953	51	4	and	and	CCONJ
ajst-11953	51	5	algorithm	algorithm	NOUN
ajst-11953	51	6	of	of	ADP
ajst-11953	51	7	support	support	NOUN
ajst-11953	51	8	vector	vector	NOUN
ajst-11953	51	9	machines	machine	NOUN
ajst-11953	52	1	[	[	X
ajst-11953	52	2	j].journal	j].journal	NOUN
ajst-11953	52	3	of	of	ADP
ajst-11953	52	4	university	university	NOUN
ajst-11953	52	5	of	of	ADP
ajst-11953	52	6	electronic	electronic	ADJ
ajst-11953	52	7	science	science	NOUN
ajst-11953	52	8	and	and	CCONJ
ajst-11953	52	9	technology	technology	NOUN
ajst-11953	52	10	of	of	ADP
ajst-11953	52	11	china	china	PROPN
ajst-11953	52	12	,	,	PUNCT
ajst-11953	52	13	2011	2011	NUM
ajst-11953	52	14	,	,	PUNCT
ajst-11953	52	15	40(1	40(1	NUM
ajst-11953	52	16	)	)	PUNCT
ajst-11953	52	17	:	:	PUNCT
ajst-11953	52	18	2	2	NUM
ajst-11953	52	19	-	-	SYM
ajst-11953	52	20	10	10	NUM
ajst-11953	52	21	.	.	PUNCT
ajst-11953	53	1	[	[	X
ajst-11953	53	2	9	9	NUM
ajst-11953	53	3	]	]	X
ajst-11953	53	4	zhang	zhang	PROPN
ajst-11953	53	5	rui	rui	PROPN
ajst-11953	53	6	,	,	PUNCT
ajst-11953	53	7	ma	ma	PROPN
ajst-11953	53	8	jianwen	jianwen	NOUN
ajst-11953	53	9	.	.	PUNCT
ajst-11953	54	1	new	new	ADJ
ajst-11953	54	2	progress	progress	NOUN
ajst-11953	54	3	of	of	ADP
ajst-11953	54	4	support	support	NOUN
ajst-11953	54	5	vector	vector	NOUN
ajst-11953	54	6	machine	machine	NOUN
ajst-11953	54	7	application	application	NOUN
ajst-11953	54	8	in	in	ADP
ajst-11953	54	9	remote	remote	ADJ
ajst-11953	54	10	sensing	sense	VERB
ajst-11953	54	11	data	datum	NOUN
ajst-11953	54	12	classification	classification	NOUN
ajst-11953	54	13	[	[	X
ajst-11953	54	14	j].advances	j].advance	NOUN
ajst-11953	54	15	in	in	ADP
ajst-11953	54	16	earth	earth	NOUN
ajst-11953	54	17	sciences	science	NOUN
ajst-11953	54	18	,	,	PUNCT
ajst-11953	54	19	2009	2009	NUM
ajst-11953	54	20	,	,	PUNCT
ajst-11953	54	21	24(5	24(5	NUM
ajst-11953	54	22	)	)	PUNCT
ajst-11953	54	23	:	:	PUNCT
ajst-11953	54	24	555	555	NUM
ajst-11953	54	25	-	-	SYM
ajst-11953	54	26	562	562	NUM
ajst-11953	54	27	.	.	PUNCT
ajst-11953	55	1	[	[	X
ajst-11953	55	2	10	10	NUM
ajst-11953	55	3	]	]	X
ajst-11953	55	4	dixon	dixon	PROPN
ajst-11953	55	5	b	b	PROPN
ajst-11953	55	6	,	,	PUNCT
ajst-11953	55	7	candade	candade	ADJ
ajst-11953	55	8	n.	n.	NOUN
ajst-11953	55	9	multispectral	multispectral	ADJ
ajst-11953	55	10	landuse	landuse	NOUN
ajst-11953	55	11	classification	classification	NOUN
ajst-11953	55	12	using	use	VERB
ajst-11953	55	13	neural	neural	ADJ
ajst-11953	55	14	networks	network	NOUN
ajst-11953	55	15	and	and	CCONJ
ajst-11953	55	16	support	support	VERB
ajst-11953	55	17	vector	vector	NOUN
ajst-11953	55	18	machines	machine	NOUN
ajst-11953	55	19	:	:	PUNCT
ajst-11953	55	20	one	one	NUM
ajst-11953	55	21	or	or	CCONJ
ajst-11953	55	22	the	the	DET
ajst-11953	55	23	other	other	ADJ
ajst-11953	55	24	or	or	CCONJ
ajst-11953	55	25	both?[j	both?[j	NUM
ajst-11953	55	26	]	]	PUNCT
ajst-11953	55	27	.	.	PUNCT
ajst-11953	56	1	international	international	ADJ
ajst-11953	56	2	journal	journal	PROPN
ajst-11953	56	3	of	of	ADP
ajst-11953	56	4	remote	remote	ADJ
ajst-11953	56	5	sensing	sensing	NOUN
ajst-11953	56	6	,	,	PUNCT
ajst-11953	56	7	2008	2008	NUM
ajst-11953	56	8	,	,	PUNCT
ajst-11953	56	9	29(4	29(4	NOUN
ajst-11953	56	10	)	)	PUNCT
ajst-11953	56	11	:	:	PUNCT
ajst-11953	56	12	1185	1185	NUM
ajst-11953	56	13	-	-	SYM
ajst-11953	56	14	1206	1206	NUM
ajst-11953	56	15	.	.	PUNCT
ajst-11953	57	1	[	[	X
ajst-11953	57	2	11	11	NUM
ajst-11953	57	3	]	]	X
ajst-11953	57	4	mathur	mathur	PROPN
ajst-11953	57	5	a	a	PROPN
ajst-11953	57	6	,	,	PUNCT
ajst-11953	57	7	foody	foody	NOUN
ajst-11953	57	8	g	g	PROPN
ajst-11953	57	9	m.	m.	NOUN
ajst-11953	57	10	multiclass	multiclass	ADJ
ajst-11953	57	11	and	and	CCONJ
ajst-11953	57	12	binary	binary	ADJ
ajst-11953	57	13	svm	svm	PROPN
ajst-11953	57	14	classification	classification	NOUN
ajst-11953	57	15	:	:	PUNCT
ajst-11953	57	16	implications	implication	NOUN
ajst-11953	57	17	for	for	ADP
ajst-11953	57	18	training	training	NOUN
ajst-11953	57	19	and	and	CCONJ
ajst-11953	57	20	classification	classification	NOUN
ajst-11953	57	21	users[j	users[j	NOUN
ajst-11953	57	22	]	]	X
ajst-11953	57	23	.	.	PUNCT
ajst-11953	58	1	ieee	ieee	PROPN
ajst-11953	58	2	geo	geo	PROPN
ajst-11953	58	3	-	-	PUNCT
ajst-11953	58	4	science	science	PROPN
ajst-11953	58	5	and	and	CCONJ
ajst-11953	58	6	remote	remote	ADJ
ajst-11953	58	7	sensing	sense	VERB
ajst-11953	58	8	letters	letter	NOUN
ajst-11953	58	9	,	,	PUNCT
ajst-11953	58	10	2008	2008	NUM
ajst-11953	58	11	5(2	5(2	NUM
ajst-11953	58	12	)	)	PUNCT
ajst-11953	58	13	:	:	PUNCT
ajst-11953	58	14	241	241	NUM
ajst-11953	58	15	-	-	SYM
ajst-11953	58	16	245	245	NUM
ajst-11953	58	17	.	.	PUNCT