id	sid	tid	token	lemma	pos
cana-2726	1	1	communications	communication	NOUN
cana-2726	1	2	on	on	ADP
cana-2726	1	3	applied	apply	VERB
cana-2726	1	4	nonlinear	nonlinear	ADJ
cana-2726	1	5	analysis	analysis	NOUN
cana-2726	1	6	issn	issn	NOUN
cana-2726	1	7	:	:	PUNCT
cana-2726	1	8	1074	1074	NUM
cana-2726	1	9	-	-	PUNCT
cana-2726	1	10	133x	133x	NUM
cana-2726	1	11	vol	vol	NOUN
cana-2726	1	12	32	32	NUM
cana-2726	1	13	no	no	NOUN
cana-2726	1	14	.	.	PUNCT
cana-2726	2	1	3s	3s	NUM
cana-2726	2	2	(	(	PUNCT
cana-2726	2	3	2025	2025	NUM
cana-2726	2	4	)	)	PUNCT
cana-2726	2	5	681	681	NUM
cana-2726	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	2	7	automatic	automatic	ADJ
cana-2726	2	8	urban	urban	ADJ
cana-2726	2	9	change	change	NOUN
cana-2726	2	10	detection	detection	NOUN
cana-2726	2	11	using	use	VERB
cana-2726	2	12	landsat-8	landsat-8	PROPN
cana-2726	2	13	satellite	satellite	NOUN
cana-2726	2	14	images	image	NOUN
cana-2726	2	15	and	and	CCONJ
cana-2726	2	16	deep	deep	ADJ
cana-2726	2	17	learning	learning	NOUN
cana-2726	2	18	techniques	technique	NOUN
cana-2726	2	19	in	in	ADP
cana-2726	2	20	australian	australian	ADJ
cana-2726	2	21	capital	capital	NOUN
cana-2726	2	22	territory	territory	NOUN
cana-2726	2	23	(	(	PUNCT
cana-2726	2	24	act	act	PROPN
cana-2726	2	25	)	)	PUNCT
cana-2726	2	26	,	,	PUNCT
cana-2726	2	27	australia	australia	PROPN
cana-2726	2	28	dr	dr	PROPN
cana-2726	2	29	.	.	PROPN
cana-2726	2	30	ninad	ninad	PROPN
cana-2726	2	31	more1	more1	PROPN
cana-2726	2	32	,	,	PUNCT
cana-2726	2	33	dr	dr	PROPN
cana-2726	2	34	.	.	PROPN
cana-2726	2	35	puja	puja	PROPN
cana-2726	2	36	padiya2	padiya2	PROPN
cana-2726	2	37	,	,	PUNCT
cana-2726	2	38	dr	dr	PROPN
cana-2726	2	39	.	.	PROPN
cana-2726	2	40	ashok	ashok	PROPN
cana-2726	2	41	kanthe3	kanthe3	PROPN
cana-2726	2	42	,	,	PUNCT
cana-2726	2	43	prof	prof	PROPN
cana-2726	2	44	.	.	PUNCT
cana-2726	3	1	prachi	prachi	PROPN
cana-2726	3	2	wagde4	wagde4	PROPN
cana-2726	3	3	,	,	PUNCT
cana-2726	3	4	dr	dr	PROPN
cana-2726	3	5	.	.	PROPN
cana-2726	3	6	nilesh	nilesh	PROPN
cana-2726	3	7	marathe5	marathe5	PROPN
cana-2726	3	8	dr	dr	PROPN
cana-2726	3	9	.	.	PROPN
cana-2726	3	10	kirti	kirti	PROPN
cana-2726	3	11	wanjale6	wanjale6	PROPN
cana-2726	4	1	1assistant	1assistant	NUM
cana-2726	4	2	professor	professor	NOUN
cana-2726	4	3	,	,	PUNCT
cana-2726	4	4	department	department	NOUN
cana-2726	4	5	of	of	ADP
cana-2726	4	6	computer	computer	NOUN
cana-2726	4	7	science	science	NOUN
cana-2726	4	8	and	and	CCONJ
cana-2726	4	9	engineering	engineering	NOUN
cana-2726	4	10	,	,	PUNCT
cana-2726	4	11	xavier	xavier	PROPN
cana-2726	4	12	institute	institute	PROPN
cana-2726	4	13	of	of	ADP
cana-2726	4	14	engineering	engineering	PROPN
cana-2726	4	15	,	,	PUNCT
cana-2726	4	16	mumbai	mumbai	PROPN
cana-2726	4	17	university	university	PROPN
cana-2726	4	18	,	,	PUNCT
cana-2726	4	19	mumbai	mumbai	PROPN
cana-2726	4	20	,	,	PUNCT
cana-2726	4	21	india	india	PROPN
cana-2726	4	22	.	.	PUNCT
cana-2726	5	1	ninad.m@xavier.ac.in	ninad.m@xavier.ac.in	PROPN
cana-2726	5	2	2assistant	2assistant	PROPN
cana-2726	5	3	professor	professor	NOUN
cana-2726	5	4	,	,	PUNCT
cana-2726	5	5	department	department	NOUN
cana-2726	5	6	of	of	ADP
cana-2726	5	7	computer	computer	NOUN
cana-2726	5	8	engineering	engineering	NOUN
cana-2726	5	9	,	,	PUNCT
cana-2726	5	10	ramrao	ramrao	VERB
cana-2726	5	11	adik	adik	PROPN
cana-2726	5	12	institute	institute	PROPN
cana-2726	5	13	of	of	ADP
cana-2726	5	14	technology	technology	PROPN
cana-2726	5	15	,	,	PUNCT
cana-2726	5	16	d	d	PROPN
cana-2726	5	17	y	y	PROPN
cana-2726	5	18	patil	patil	PROPN
cana-2726	5	19	deemed	deem	VERB
cana-2726	5	20	to	to	PART
cana-2726	5	21	be	be	AUX
cana-2726	5	22	university	university	NOUN
cana-2726	5	23	,	,	PUNCT
cana-2726	5	24	nerul	nerul	PROPN
cana-2726	5	25	,	,	PUNCT
cana-2726	5	26	navi	navi	PROPN
cana-2726	5	27	mumbai	mumbai	PROPN
cana-2726	5	28	,	,	PUNCT
cana-2726	5	29	india	india	PROPN
cana-2726	5	30	puja.padiya05@gmail.com	puja.padiya05@gmail.com	X
cana-2726	6	1	3associate	3associate	NUM
cana-2726	6	2	professor	professor	NOUN
cana-2726	6	3	,	,	PUNCT
cana-2726	6	4	department	department	NOUN
cana-2726	6	5	of	of	ADP
cana-2726	6	6	computer	computer	NOUN
cana-2726	6	7	engineering	engineering	NOUN
cana-2726	6	8	,	,	PUNCT
cana-2726	6	9	fr	fr	PROPN
cana-2726	6	10	.	.	PUNCT
cana-2726	7	1	conceicao	conceicao	PROPN
cana-2726	7	2	rodrigues	rodrigues	PROPN
cana-2726	7	3	college	college	PROPN
cana-2726	7	4	of	of	ADP
cana-2726	7	5	engineering	engineering	PROPN
cana-2726	7	6	,	,	PUNCT
cana-2726	7	7	mumbai	mumbai	PROPN
cana-2726	7	8	,	,	PUNCT
cana-2726	7	9	maharashtra	maharashtra	PROPN
cana-2726	7	10	,	,	PUNCT
cana-2726	7	11	india	india	PROPN
cana-2726	7	12	.	.	PUNCT
cana-2726	8	1	ashokkanthe@gmail.com	ashokkanthe@gmail.com	X
cana-2726	8	2	.	.	PUNCT
cana-2726	9	1	4assistant	4assistant	NUM
cana-2726	9	2	professor	professor	NOUN
cana-2726	9	3	,	,	PUNCT
cana-2726	9	4	department	department	NOUN
cana-2726	9	5	of	of	ADP
cana-2726	9	6	computer	computer	NOUN
cana-2726	9	7	engineering	engineering	NOUN
cana-2726	9	8	,	,	PUNCT
cana-2726	9	9	shah	shah	PROPN
cana-2726	9	10	&	&	CCONJ
cana-2726	9	11	anchor	anchor	PROPN
cana-2726	9	12	kutchhi	kutchhi	PROPN
cana-2726	9	13	engineering	engineering	PROPN
cana-2726	9	14	college	college	PROPN
cana-2726	9	15	,	,	PUNCT
cana-2726	9	16	mumbai	mumbai	PROPN
cana-2726	9	17	.	.	PUNCT
cana-2726	9	18	prachi.wagde@sakec.ac.in	prachi.wagde@sakec.ac.in	X
cana-2726	10	1	5associate	5associate	PROPN
cana-2726	10	2	professor	professor	NOUN
cana-2726	10	3	,	,	PUNCT
cana-2726	10	4	department	department	NOUN
cana-2726	10	5	of	of	ADP
cana-2726	10	6	computer	computer	NOUN
cana-2726	10	7	science	science	NOUN
cana-2726	10	8	and	and	CCONJ
cana-2726	10	9	engineering	engineering	NOUN
cana-2726	10	10	(	(	PUNCT
cana-2726	10	11	data	data	NOUN
cana-2726	10	12	science	science	NOUN
cana-2726	10	13	)	)	PUNCT
cana-2726	10	14	,	,	PUNCT
cana-2726	10	15	dwarkadas	dwarkadas	PROPN
cana-2726	10	16	j.	j.	PROPN
cana-2726	10	17	sanghvi	sanghvi	PROPN
cana-2726	10	18	college	college	PROPN
cana-2726	10	19	of	of	ADP
cana-2726	10	20	engineering	engineering	NOUN
cana-2726	10	21	,	,	PUNCT
cana-2726	10	22	vile	vile	NOUN
cana-2726	10	23	-	-	PUNCT
cana-2726	10	24	parle	parle	NOUN
cana-2726	10	25	,	,	PUNCT
cana-2726	10	26	mumbai	mumbai	PROPN
cana-2726	10	27	,	,	PUNCT
cana-2726	10	28	india	india	PROPN
cana-2726	10	29	nilmarathe2307@gmail.com	nilmarathe2307@gmail.com	NOUN
cana-2726	10	30	6professor	6professor	NUM
cana-2726	10	31	,	,	PUNCT
cana-2726	10	32	computer	computer	NOUN
cana-2726	10	33	engineering	engineering	NOUN
cana-2726	10	34	department	department	PROPN
cana-2726	10	35	,	,	PUNCT
cana-2726	10	36	vishwakarma	vishwakarma	PROPN
cana-2726	10	37	institute	institute	PROPN
cana-2726	10	38	of	of	ADP
cana-2726	10	39	technology	technology	PROPN
cana-2726	10	40	,	,	PUNCT
cana-2726	10	41	pune	pune	NOUN
cana-2726	10	42	,	,	PUNCT
cana-2726	10	43	kirti.wanjale@vit.edu	kirti.wanjale@vit.edu	PROPN
cana-2726	10	44	article	article	NOUN
cana-2726	10	45	history	history	NOUN
cana-2726	10	46	:	:	PUNCT
cana-2726	10	47	received	receive	VERB
cana-2726	10	48	:	:	PUNCT
cana-2726	10	49	27	27	NUM
cana-2726	10	50	-	-	SYM
cana-2726	10	51	09	09	NUM
cana-2726	10	52	-	-	PUNCT
cana-2726	10	53	2024	2024	NUM
cana-2726	10	54	revised	revise	VERB
cana-2726	10	55	:	:	PUNCT
cana-2726	10	56	16	16	NUM
cana-2726	10	57	-	-	SYM
cana-2726	10	58	11	11	NUM
cana-2726	10	59	-	-	PUNCT
cana-2726	10	60	2024	2024	NUM
cana-2726	10	61	accepted	accept	VERB
cana-2726	10	62	:	:	PUNCT
cana-2726	10	63	29	29	NUM
cana-2726	10	64	-	-	SYM
cana-2726	10	65	11	11	NUM
cana-2726	10	66	-	-	PUNCT
cana-2726	10	67	2024	2024	NUM
cana-2726	10	68	abstract	abstract	NOUN
cana-2726	10	69	:	:	PUNCT
cana-2726	10	70	the	the	DET
cana-2726	10	71	remote	remote	ADJ
cana-2726	10	72	sensing	sensing	NOUN
cana-2726	10	73	based	base	VERB
cana-2726	10	74	satellite	satellite	NOUN
cana-2726	10	75	data	datum	NOUN
cana-2726	10	76	is	be	AUX
cana-2726	10	77	useful	useful	ADJ
cana-2726	10	78	as	as	ADP
cana-2726	10	79	a	a	DET
cana-2726	10	80	very	very	ADV
cana-2726	10	81	powerful	powerful	ADJ
cana-2726	10	82	tools	tool	NOUN
cana-2726	10	83	for	for	ADP
cana-2726	10	84	providing	provide	VERB
cana-2726	10	85	a	a	DET
cana-2726	10	86	complete	complete	ADJ
cana-2726	10	87	information	information	NOUN
cana-2726	10	88	for	for	ADP
cana-2726	10	89	an	an	DET
cana-2726	10	90	accurate	accurate	ADJ
cana-2726	10	91	urban	urban	ADJ
cana-2726	10	92	area	area	NOUN
cana-2726	10	93	monitoring	monitoring	NOUN
cana-2726	10	94	.	.	PUNCT
cana-2726	11	1	identifying	identify	VERB
cana-2726	11	2	the	the	DET
cana-2726	11	3	urban	urban	ADJ
cana-2726	11	4	change	change	NOUN
cana-2726	11	5	detection	detection	NOUN
cana-2726	11	6	is	be	AUX
cana-2726	11	7	a	a	DET
cana-2726	11	8	main	main	ADJ
cana-2726	11	9	part	part	NOUN
cana-2726	11	10	of	of	ADP
cana-2726	11	11	professional	professional	ADJ
cana-2726	11	12	urban	urban	ADJ
cana-2726	11	13	drafting	drafting	NOUN
cana-2726	11	14	,	,	PUNCT
cana-2726	11	15	regional	regional	ADJ
cana-2726	11	16	based	base	VERB
cana-2726	11	17	urban	urban	ADJ
cana-2726	11	18	development	development	NOUN
cana-2726	11	19	in	in	ADP
cana-2726	11	20	fraction	fraction	NOUN
cana-2726	11	21	of	of	ADP
cana-2726	11	22	low	low	ADJ
cana-2726	11	23	cost	cost	NOUN
cana-2726	11	24	effective	effective	ADJ
cana-2726	11	25	along	along	ADP
cana-2726	11	26	with	with	ADP
cana-2726	11	27	less	less	ADJ
cana-2726	11	28	time	time	NOUN
cana-2726	11	29	duration	duration	NOUN
cana-2726	11	30	compared	compare	VERB
cana-2726	11	31	to	to	ADP
cana-2726	11	32	common	common	ADJ
cana-2726	11	33	methods	method	NOUN
cana-2726	11	34	(	(	PUNCT
cana-2726	11	35	e.g.	e.g.	ADV
cana-2726	11	36	manually	manually	ADV
cana-2726	11	37	field	field	NOUN
cana-2726	11	38	survey	survey	NOUN
cana-2726	11	39	report	report	NOUN
cana-2726	11	40	,	,	PUNCT
cana-2726	11	41	aerial	aerial	ADJ
cana-2726	11	42	imagery	imagery	NOUN
cana-2726	11	43	etc	etc	X
cana-2726	11	44	.	.	PUNCT
cana-2726	11	45	)	)	PUNCT
cana-2726	11	46	.	.	PUNCT
cana-2726	12	1	the	the	DET
cana-2726	12	2	main	main	ADJ
cana-2726	12	3	goal	goal	NOUN
cana-2726	12	4	of	of	ADP
cana-2726	12	5	the	the	DET
cana-2726	12	6	proposed	propose	VERB
cana-2726	12	7	work	work	NOUN
cana-2726	12	8	is	be	AUX
cana-2726	12	9	to	to	PART
cana-2726	12	10	monitoring	monitor	VERB
cana-2726	12	11	various	various	ADJ
cana-2726	12	12	changes	change	NOUN
cana-2726	12	13	in	in	ADP
cana-2726	12	14	features	feature	NOUN
cana-2726	12	15	on	on	ADP
cana-2726	12	16	the	the	DET
cana-2726	12	17	complete	complete	ADJ
cana-2726	12	18	surface	surface	NOUN
cana-2726	12	19	of	of	ADP
cana-2726	12	20	earth	earth	NOUN
cana-2726	12	21	of	of	ADP
cana-2726	12	22	various	various	ADJ
cana-2726	12	23	pixel	pixel	NOUN
cana-2726	12	24	resolution	resolution	NOUN
cana-2726	12	25	can	can	AUX
cana-2726	12	26	be	be	AUX
cana-2726	12	27	carried	carry	VERB
cana-2726	12	28	out	out	ADP
cana-2726	12	29	by	by	ADP
cana-2726	12	30	low	low	ADJ
cana-2726	12	31	-	-	PUNCT
cana-2726	12	32	cost	cost	NOUN
cana-2726	12	33	remote	remote	ADJ
cana-2726	12	34	sensing	sensing	NOUN
cana-2726	12	35	-	-	PUNCT
cana-2726	12	36	based	base	VERB
cana-2726	12	37	landsat-8	landsat-8	PROPN
cana-2726	12	38	satellite	satellite	NOUN
cana-2726	12	39	images	image	NOUN
cana-2726	12	40	.	.	PUNCT
cana-2726	13	1	the	the	DET
cana-2726	13	2	urban	urban	ADJ
cana-2726	13	3	change	change	NOUN
cana-2726	13	4	detection	detection	NOUN
cana-2726	13	5	is	be	AUX
cana-2726	13	6	examining	examine	VERB
cana-2726	13	7	the	the	DET
cana-2726	13	8	various	various	ADJ
cana-2726	13	9	changes	change	NOUN
cana-2726	13	10	in	in	ADP
cana-2726	13	11	urban	urban	ADJ
cana-2726	13	12	area	area	NOUN
cana-2726	13	13	between	between	ADP
cana-2726	13	14	two	two	NUM
cana-2726	13	15	periods	period	NOUN
cana-2726	13	16	:	:	PUNCT
cana-2726	13	17	1	1	NUM
cana-2726	13	18	)	)	PUNCT
cana-2726	13	19	baseline	baseline	NOUN
cana-2726	13	20	period	period	NOUN
cana-2726	13	21	2	2	NUM
cana-2726	13	22	)	)	PUNCT
cana-2726	13	23	more	more	ADV
cana-2726	13	24	recent	recent	ADJ
cana-2726	13	25	period	period	NOUN
cana-2726	13	26	.	.	PUNCT
cana-2726	14	1	in	in	ADP
cana-2726	14	2	the	the	DET
cana-2726	14	3	previously	previously	NOUN
cana-2726	14	4	,	,	PUNCT
cana-2726	14	5	the	the	DET
cana-2726	14	6	classical	classical	ADJ
cana-2726	14	7	change	change	NOUN
cana-2726	14	8	detection	detection	NOUN
cana-2726	14	9	(	(	PUNCT
cana-2726	14	10	cd	cd	NOUN
cana-2726	14	11	-	-	PUNCT
cana-2726	14	12	algorithm	algorithm	NOUN
cana-2726	14	13	)	)	PUNCT
cana-2726	14	14	is	be	AUX
cana-2726	14	15	inaccurately	inaccurately	ADV
cana-2726	14	16	identifying	identify	VERB
cana-2726	14	17	both	both	CCONJ
cana-2726	14	18	the	the	DET
cana-2726	14	19	spatial	spatial	ADJ
cana-2726	14	20	information	information	NOUN
cana-2726	14	21	and	and	CCONJ
cana-2726	14	22	various	various	ADJ
cana-2726	14	23	scale	scale	NOUN
cana-2726	14	24	variations	variation	NOUN
cana-2726	14	25	within	within	ADP
cana-2726	14	26	satellite	satellite	NOUN
cana-2726	14	27	images	image	NOUN
cana-2726	14	28	.	.	PUNCT
cana-2726	15	1	to	to	PART
cana-2726	15	2	overcome	overcome	VERB
cana-2726	15	3	the	the	DET
cana-2726	15	4	problem	problem	NOUN
cana-2726	15	5	,	,	PUNCT
cana-2726	15	6	the	the	DET
cana-2726	15	7	present	present	ADJ
cana-2726	15	8	research	research	NOUN
cana-2726	15	9	work	work	NOUN
cana-2726	15	10	introduces	introduce	VERB
cana-2726	15	11	an	an	DET
cana-2726	15	12	advanced	advanced	ADJ
cana-2726	15	13	deep	deep	ADJ
cana-2726	15	14	learning	learning	NOUN
cana-2726	15	15	based	base	VERB
cana-2726	15	16	novel	novel	NOUN
cana-2726	15	17	change	change	NOUN
cana-2726	15	18	detection	detection	NOUN
cana-2726	15	19	(	(	PUNCT
cana-2726	15	20	bitemporal_cd	bitemporal_cd	NOUN
cana-2726	15	21	)	)	PUNCT
cana-2726	15	22	technique	technique	NOUN
cana-2726	15	23	that	that	PRON
cana-2726	15	24	accurately	accurately	ADV
cana-2726	15	25	extracts	extract	VERB
cana-2726	15	26	complete	complete	ADJ
cana-2726	15	27	spatial	spatial	ADJ
cana-2726	15	28	information	information	NOUN
cana-2726	15	29	at	at	ADP
cana-2726	15	30	various	various	ADJ
cana-2726	15	31	level	level	NOUN
cana-2726	15	32	of	of	ADP
cana-2726	15	33	scales	scale	NOUN
cana-2726	15	34	variations	variation	NOUN
cana-2726	15	35	to	to	PART
cana-2726	15	36	simply	simply	ADV
cana-2726	15	37	address	address	VERB
cana-2726	15	38	both	both	DET
cana-2726	15	39	issues	issue	NOUN
cana-2726	15	40	.	.	PUNCT
cana-2726	16	1	the	the	DET
cana-2726	16	2	new	new	ADJ
cana-2726	16	3	proposed	propose	VERB
cana-2726	16	4	model	model	NOUN
cana-2726	16	5	is	be	AUX
cana-2726	16	6	based	base	VERB
cana-2726	16	7	on	on	ADP
cana-2726	16	8	multi	multi	ADJ
cana-2726	16	9	scale	scale	NOUN
cana-2726	16	10	and	and	CCONJ
cana-2726	16	11	multi	multi	ADJ
cana-2726	16	12	depth	depth	NOUN
cana-2726	16	13	(	(	PUNCT
cana-2726	16	14	msmd	msmd	NOUN
cana-2726	16	15	)	)	PUNCT
cana-2726	16	16	approach	approach	NOUN
cana-2726	16	17	deep	deep	ADJ
cana-2726	16	18	neural	neural	ADJ
cana-2726	16	19	network	network	NOUN
cana-2726	16	20	that	that	PRON
cana-2726	16	21	generates	generate	VERB
cana-2726	16	22	all	all	DET
cana-2726	16	23	binary	binary	ADJ
cana-2726	16	24	information	information	NOUN
cana-2726	16	25	change	change	NOUN
cana-2726	16	26	based	base	VERB
cana-2726	16	27	map	map	NOUN
cana-2726	16	28	that	that	PRON
cana-2726	16	29	simply	simply	ADV
cana-2726	16	30	integrates	integrate	VERB
cana-2726	16	31	with	with	ADP
cana-2726	16	32	complete	complete	ADJ
cana-2726	16	33	information	information	NOUN
cana-2726	16	34	of	of	ADP
cana-2726	16	35	different	different	ADJ
cana-2726	16	36	sizes	size	NOUN
cana-2726	16	37	of	of	ADP
cana-2726	16	38	patches	patch	NOUN
cana-2726	16	39	at	at	ADP
cana-2726	16	40	various	various	ADJ
cana-2726	16	41	decision	decision	NOUN
cana-2726	16	42	parameter	parameter	NOUN
cana-2726	16	43	.	.	PUNCT
cana-2726	17	1	it	it	PRON
cana-2726	17	2	is	be	AUX
cana-2726	17	3	used	use	VERB
cana-2726	17	4	landsat-8	landsat-8	PROPN
cana-2726	17	5	satellites	satellite	NOUN
cana-2726	17	6	images	image	NOUN
cana-2726	17	7	originally	originally	ADV
cana-2726	17	8	from	from	ADP
cana-2726	17	9	australian	australian	ADJ
cana-2726	17	10	capital	capital	NOUN
cana-2726	17	11	territory	territory	NOUN
cana-2726	17	12	(	(	PUNCT
cana-2726	17	13	act	act	PROPN
cana-2726	17	14	)	)	PUNCT
cana-2726	17	15	,	,	PUNCT
cana-2726	17	16	suburban	suburban	ADJ
cana-2726	17	17	nicholls	nicholl	NOUN
cana-2726	17	18	,	,	PUNCT
cana-2726	17	19	and	and	CCONJ
cana-2726	17	20	district	district	NOUN
cana-2726	17	21	:	:	PUNCT
cana-2726	17	22	gungahlinaustralia	gungahlinaustralia	NOUN
cana-2726	17	23	,	,	PUNCT
cana-2726	17	24	because	because	SCONJ
cana-2726	17	25	total	total	ADJ
cana-2726	17	26	area	area	NOUN
cana-2726	17	27	of	of	ADP
cana-2726	17	28	the	the	DET
cana-2726	17	29	act	act	NOUN
cana-2726	17	30	is	be	AUX
cana-2726	17	31	2,351.7	2,351.7	NUM
cana-2726	17	32	km2	km2	NOUN
cana-2726	17	33	of	of	ADP
cana-2726	17	34	which	which	PRON
cana-2726	17	35	61	61	NUM
cana-2726	17	36	%	%	NOUN
cana-2726	17	37	area	area	NOUN
cana-2726	17	38	is	be	AUX
cana-2726	17	39	hilly	hilly	ADV
cana-2726	17	40	or	or	CCONJ
cana-2726	17	41	complete	complete	ADJ
cana-2726	17	42	mountainous	mountainous	ADJ
cana-2726	17	43	.	.	PUNCT
cana-2726	18	1	the	the	DET
cana-2726	18	2	proposed	propose	VERB
cana-2726	18	3	advanced	advanced	ADJ
cana-2726	18	4	deep	deep	ADJ
cana-2726	18	5	learning	learning	NOUN
cana-2726	18	6	model	model	NOUN
cana-2726	18	7	is	be	AUX
cana-2726	18	8	estimated	estimate	VERB
cana-2726	18	9	in	in	ADP
cana-2726	18	10	comparison	comparison	NOUN
cana-2726	18	11	with	with	ADP
cana-2726	18	12	both	both	CCONJ
cana-2726	18	13	bi_temporal	bi_temporal	DET
cana-2726	18	14	change	change	NOUN
cana-2726	18	15	vector	vector	NOUN
cana-2726	18	16	analysis	analysis	NOUN
cana-2726	18	17	(	(	PUNCT
cana-2726	18	18	bi_temporal	bi_temporal	PROPN
cana-2726	18	19	cva	cva	PROPN
cana-2726	18	20	)	)	PUNCT
cana-2726	18	21	and	and	CCONJ
cana-2726	18	22	support	support	NOUN
cana-2726	18	23	-	-	PUNCT
cana-2726	18	24	based	base	VERB
cana-2726	18	25	vector	vector	NOUN
cana-2726	18	26	machine	machine	NOUN
cana-2726	18	27	(	(	PUNCT
cana-2726	18	28	svm	svm	PROPN
cana-2726	18	29	)	)	PUNCT
cana-2726	18	30	.	.	PUNCT
cana-2726	19	1	on	on	ADP
cana-2726	19	2	the	the	DET
cana-2726	19	3	basis	basis	NOUN
cana-2726	19	4	of	of	ADP
cana-2726	19	5	deep	deep	ADJ
cana-2726	19	6	learning	learning	NOUN
cana-2726	19	7	change	change	NOUN
cana-2726	19	8	detection	detection	NOUN
cana-2726	19	9	results	result	NOUN
cana-2726	19	10	,	,	PUNCT
cana-2726	19	11	our	our	PRON
cana-2726	19	12	proposed	propose	VERB
cana-2726	19	13	model	model	NOUN
cana-2726	19	14	shows	show	VERB
cana-2726	19	15	a	a	DET
cana-2726	19	16	notable	notable	ADJ
cana-2726	19	17	advancement	advancement	NOUN
cana-2726	19	18	in	in	ADP
cana-2726	19	19	the	the	DET
cana-2726	19	20	performance	performance	NOUN
cana-2726	19	21	of	of	ADP
cana-2726	19	22	cohen’s_kappa	cohen’s_kappa	ADJ
cana-2726	19	23	coefficient	coefficient	NOUN
cana-2726	19	24	(	(	PUNCT
cana-2726	19	25	kc	kc	PROPN
cana-2726	19	26	)	)	PUNCT
cana-2726	19	27	compared	compare	VERB
cana-2726	19	28	to	to	ADP
cana-2726	19	29	both	both	PRON
cana-2726	19	30	svm	svm	PROPN
cana-2726	19	31	as	as	ADV
cana-2726	19	32	well	well	ADV
cana-2726	19	33	as	as	ADP
cana-2726	19	34	bi_temporal	bi_temporal	PROPN
cana-2726	19	35	cva	cva	PROPN
cana-2726	19	36	,	,	PUNCT
cana-2726	19	37	with	with	ADP
cana-2726	19	38	high	high	ADJ
cana-2726	19	39	increases	increase	NOUN
cana-2726	19	40	of	of	ADP
cana-2726	19	41	approximately	approximately	ADV
cana-2726	19	42	12.87	12.87	NUM
cana-2726	19	43	%	%	NOUN
cana-2726	19	44	and	and	CCONJ
cana-2726	19	45	30.37	30.37	NUM
cana-2726	19	46	%	%	NOUN
cana-2726	19	47	individually	individually	ADV
cana-2726	19	48	.	.	PUNCT
cana-2726	20	1	finally	finally	ADV
cana-2726	20	2	,	,	PUNCT
cana-2726	20	3	the	the	DET
cana-2726	20	4	proposed	propose	VERB
cana-2726	20	5	multi	multi	ADJ
cana-2726	20	6	scale	scale	NOUN
cana-2726	20	7	and	and	CCONJ
cana-2726	20	8	multi	multi	ADJ
cana-2726	20	9	depth	depth	NOUN
cana-2726	20	10	approach	approach	NOUN
cana-2726	20	11	deep	deep	ADJ
cana-2726	20	12	neural	neural	ADJ
cana-2726	20	13	network	network	NOUN
cana-2726	20	14	model	model	NOUN
cana-2726	20	15	performs	perform	VERB
cana-2726	20	16	superior	superior	ADJ
cana-2726	20	17	in	in	ADP
cana-2726	20	18	detecting	detect	VERB
cana-2726	20	19	various	various	ADJ
cana-2726	20	20	changes	change	NOUN
cana-2726	20	21	including	include	VERB
cana-2726	20	22	across	across	ADP
cana-2726	20	23	all	all	DET
cana-2726	20	24	level	level	NOUN
cana-2726	20	25	of	of	ADP
cana-2726	20	26	metrics	metric	NOUN
cana-2726	20	27	with	with	ADP
cana-2726	20	28	high	high	ADJ
cana-2726	20	29	accuracy	accuracy	NOUN
cana-2726	20	30	.	.	PUNCT
cana-2726	21	1	mailto:ninad.m@xavier.ac.in	mailto:ninad.m@xavier.ac.in	ADV
cana-2726	21	2	mailto:puja.padiya05@gmail.com	mailto:puja.padiya05@gmail.com	X
cana-2726	21	3	mailto:ashokkanthe@gmail.com	mailto:ashokkanthe@gmail.com	PROPN
cana-2726	21	4	mailto:prachi.wagde@sakec.ac.in	mailto:prachi.wagde@sakec.ac.in	PROPN
cana-2726	21	5	mailto:nilmarathe2307@gmail.com	mailto:nilmarathe2307@gmail.com	PROPN
cana-2726	21	6	mailto:kirti.wanjale@vit.edu	mailto:kirti.wanjale@vit.edu	NOUN
cana-2726	21	7	communications	communication	NOUN
cana-2726	21	8	on	on	ADP
cana-2726	21	9	applied	apply	VERB
cana-2726	21	10	nonlinear	nonlinear	ADJ
cana-2726	21	11	analysis	analysis	NOUN
cana-2726	21	12	issn	issn	NOUN
cana-2726	21	13	:	:	PUNCT
cana-2726	21	14	1074	1074	NUM
cana-2726	21	15	-	-	PUNCT
cana-2726	21	16	133x	133x	NUM
cana-2726	21	17	vol	vol	NOUN
cana-2726	21	18	32	32	NUM
cana-2726	21	19	no	no	NOUN
cana-2726	21	20	.	.	PUNCT
cana-2726	22	1	3s	3s	NUM
cana-2726	22	2	(	(	PUNCT
cana-2726	22	3	2025	2025	NUM
cana-2726	22	4	)	)	PUNCT
cana-2726	22	5	682	682	NUM
cana-2726	22	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	22	7	keywords	keyword	NOUN
cana-2726	22	8	:	:	PUNCT
cana-2726	22	9	multi	multi	ADJ
cana-2726	22	10	scale	scale	NOUN
cana-2726	22	11	and	and	CCONJ
cana-2726	22	12	multi	multi	ADJ
cana-2726	22	13	depth	depth	NOUN
cana-2726	22	14	network	network	NOUN
cana-2726	22	15	,	,	PUNCT
cana-2726	22	16	bitemporal_change	bitemporal_change	NOUN
cana-2726	22	17	vector	vector	NOUN
cana-2726	22	18	analysis	analysis	NOUN
cana-2726	22	19	,	,	PUNCT
cana-2726	22	20	support	support	NOUN
cana-2726	22	21	vector	vector	NOUN
cana-2726	22	22	analysis	analysis	NOUN
cana-2726	22	23	,	,	PUNCT
cana-2726	22	24	remote	remote	ADJ
cana-2726	22	25	sensing	sense	VERB
cana-2726	22	26	satellite	satellite	NOUN
cana-2726	22	27	images	image	NOUN
cana-2726	22	28	.	.	PUNCT
cana-2726	23	1	1	1	X
cana-2726	23	2	.	.	X
cana-2726	23	3	introduction	introduction	NOUN
cana-2726	23	4	:	:	PUNCT
cana-2726	23	5	in	in	ADP
cana-2726	23	6	remote	remote	ADJ
cana-2726	23	7	sensing	sense	VERB
cana-2726	23	8	technology	technology	NOUN
cana-2726	23	9	,	,	PUNCT
cana-2726	23	10	the	the	DET
cana-2726	23	11	change	change	NOUN
cana-2726	23	12	detection	detection	NOUN
cana-2726	23	13	method	method	NOUN
cana-2726	23	14	(	(	PUNCT
cana-2726	23	15	cd	cd	PROPN
cana-2726	23	16	)	)	PUNCT
cana-2726	23	17	is	be	AUX
cana-2726	23	18	an	an	DET
cana-2726	23	19	important	important	ADJ
cana-2726	23	20	process	process	NOUN
cana-2726	23	21	of	of	ADP
cana-2726	23	22	effectively	effectively	ADV
cana-2726	23	23	identifying	identify	VERB
cana-2726	23	24	changes	change	NOUN
cana-2726	23	25	from	from	ADP
cana-2726	23	26	a	a	DET
cana-2726	23	27	pair	pair	NOUN
cana-2726	23	28	of	of	ADP
cana-2726	23	29	satellite	satellite	NOUN
cana-2726	23	30	images	image	NOUN
cana-2726	23	31	of	of	ADP
cana-2726	23	32	geographical	geographical	ADJ
cana-2726	23	33	coverage	coverage	NOUN
cana-2726	23	34	area	area	NOUN
cana-2726	23	35	at	at	ADP
cana-2726	23	36	different	different	ADJ
cana-2726	23	37	date	date	NOUN
cana-2726	23	38	and	and	CCONJ
cana-2726	23	39	time	time	NOUN
cana-2726	23	40	zones	zone	NOUN
cana-2726	23	41	.	.	PUNCT
cana-2726	24	1	accordingly	accordingly	ADV
cana-2726	24	2	,	,	PUNCT
cana-2726	24	3	the	the	DET
cana-2726	24	4	change	change	NOUN
cana-2726	24	5	detection	detection	NOUN
cana-2726	24	6	method	method	NOUN
cana-2726	24	7	is	be	AUX
cana-2726	24	8	arrived	arrive	VERB
cana-2726	24	9	as	as	ADP
cana-2726	24	10	very	very	ADV
cana-2726	24	11	powerful	powerful	ADJ
cana-2726	24	12	as	as	ADV
cana-2726	24	13	well	well	ADV
cana-2726	24	14	as	as	ADP
cana-2726	24	15	primary	primary	ADJ
cana-2726	24	16	task	task	NOUN
cana-2726	24	17	in	in	ADP
cana-2726	24	18	remote	remote	ADJ
cana-2726	24	19	sensing	sensing	NOUN
cana-2726	24	20	-	-	PUNCT
cana-2726	24	21	based	base	VERB
cana-2726	24	22	satellite	satellite	NOUN
cana-2726	24	23	images	image	NOUN
cana-2726	24	24	community	community	NOUN
cana-2726	24	25	with	with	ADP
cana-2726	24	26	present	present	ADJ
cana-2726	24	27	real	real	ADJ
cana-2726	24	28	time	time	NOUN
cana-2726	24	29	world	world	NOUN
cana-2726	24	30	applications	application	NOUN
cana-2726	24	31	includes	include	VERB
cana-2726	24	32	as	as	ADP
cana-2726	24	33	land	land	NOUN
cana-2726	24	34	usage	usage	NOUN
cana-2726	24	35	and	and	CCONJ
cana-2726	24	36	land	land	NOUN
cana-2726	24	37	covering	cover	VERB
cana-2726	24	38	monitoring	monitoring	NOUN
cana-2726	24	39	(	(	PUNCT
cana-2726	24	40	lulc	lulc	PROPN
cana-2726	24	41	)	)	PUNCT
cana-2726	24	42	,	,	PUNCT
cana-2726	24	43	remote	remote	ADJ
cana-2726	24	44	sensing	sensing	NOUN
cana-2726	24	45	for	for	ADP
cana-2726	24	46	agricultural	agricultural	ADJ
cana-2726	24	47	,	,	PUNCT
cana-2726	24	48	disaster	disaster	NOUN
cana-2726	24	49	assessment	assessment	NOUN
cana-2726	24	50	and	and	CCONJ
cana-2726	24	51	managementflooding	managementflooding	NOUN
cana-2726	24	52	,	,	PUNCT
cana-2726	24	53	wildfire	wildfire	NOUN
cana-2726	24	54	,	,	PUNCT
cana-2726	24	55	earthquake	earthquake	NOUN
cana-2726	24	56	etc	etc	X
cana-2726	25	1	[	[	X
cana-2726	25	2	1	1	NUM
cana-2726	25	3	]	]	PUNCT
cana-2726	25	4	.	.	PUNCT
cana-2726	26	1	the	the	DET
cana-2726	26	2	vision	vision	NOUN
cana-2726	26	3	based	base	VERB
cana-2726	26	4	transformer	transformer	NOUN
cana-2726	26	5	(	(	PUNCT
cana-2726	26	6	vt	vt	NOUN
cana-2726	26	7	)	)	PUNCT
cana-2726	26	8	is	be	AUX
cana-2726	26	9	significant	significant	ADJ
cana-2726	26	10	component	component	NOUN
cana-2726	26	11	that	that	PRON
cana-2726	26	12	simply	simply	ADV
cana-2726	26	13	learning	learn	VERB
cana-2726	26	14	of	of	ADP
cana-2726	26	15	spatio_temporal	spatio_temporal	PROPN
cana-2726	26	16	based	base	VERB
cana-2726	26	17	representation	representation	NOUN
cana-2726	26	18	but	but	CCONJ
cana-2726	26	19	that	that	PRON
cana-2726	26	20	includes	include	VERB
cana-2726	26	21	huge	huge	ADJ
cana-2726	26	22	computation	computation	NOUN
cana-2726	26	23	issue	issue	NOUN
cana-2726	26	24	,	,	PUNCT
cana-2726	26	25	mainly	mainly	ADV
cana-2726	26	26	for	for	ADP
cana-2726	26	27	high	high	ADJ
cana-2726	26	28	quality	quality	NOUN
cana-2726	26	29	of	of	ADP
cana-2726	26	30	resolution	resolution	NOUN
cana-2726	26	31	satellite	satellite	NOUN
cana-2726	26	32	images	image	NOUN
cana-2726	26	33	.	.	PUNCT
cana-2726	27	1	the	the	DET
cana-2726	27	2	designing	designing	NOUN
cana-2726	27	3	of	of	ADP
cana-2726	27	4	macro	macro	ADJ
cana-2726	27	5	architectures	architecture	NOUN
cana-2726	27	6	is	be	AUX
cana-2726	27	7	still	still	ADV
cana-2726	27	8	lacking	lack	VERB
cana-2726	27	9	integrating	integrate	VERB
cana-2726	27	10	with	with	ADP
cana-2726	27	11	these	these	DET
cana-2726	27	12	vision	vision	NOUN
cana-2726	27	13	transformer	transformer	NOUN
cana-2726	27	14	components	component	NOUN
cana-2726	27	15	specially	specially	ADV
cana-2726	27	16	for	for	ADP
cana-2726	27	17	urban	urban	ADJ
cana-2726	27	18	change	change	NOUN
cana-2726	27	19	detection	detection	NOUN
cana-2726	27	20	related	relate	VERB
cana-2726	27	21	tasks	task	NOUN
cana-2726	27	22	[	[	X
cana-2726	27	23	2	2	NUM
cana-2726	27	24	]	]	PUNCT
cana-2726	27	25	.	.	PUNCT
cana-2726	28	1	the	the	DET
cana-2726	28	2	field	field	NOUN
cana-2726	28	3	-	-	PUNCT
cana-2726	28	4	based	base	VERB
cana-2726	28	5	manually	manually	ADJ
cana-2726	28	6	surveys	survey	NOUN
cana-2726	28	7	are	be	AUX
cana-2726	28	8	primally	primally	PROPN
cana-2726	28	9	method	method	NOUN
cana-2726	28	10	of	of	ADP
cana-2726	28	11	change	change	NOUN
cana-2726	28	12	detection	detection	NOUN
cana-2726	28	13	but	but	CCONJ
cana-2726	28	14	they	they	PRON
cana-2726	28	15	are	be	AUX
cana-2726	28	16	loaded	load	VERB
cana-2726	28	17	with	with	ADP
cana-2726	28	18	various	various	ADJ
cana-2726	28	19	serious	serious	ADJ
cana-2726	28	20	drawbacks	drawback	NOUN
cana-2726	28	21	such	such	ADJ
cana-2726	28	22	as	as	ADP
cana-2726	28	23	time	time	NOUN
cana-2726	28	24	-	-	PUNCT
cana-2726	28	25	consuming	consume	VERB
cana-2726	28	26	process	process	NOUN
cana-2726	28	27	,	,	PUNCT
cana-2726	28	28	require	require	VERB
cana-2726	28	29	technical	technical	ADJ
cana-2726	28	30	ability	ability	NOUN
cana-2726	28	31	of	of	ADP
cana-2726	28	32	human	human	ADJ
cana-2726	28	33	power	power	NOUN
cana-2726	28	34	for	for	ADP
cana-2726	28	35	fieldwork	fieldwork	NOUN
cana-2726	28	36	,	,	PUNCT
cana-2726	28	37	limitations	limitation	NOUN
cana-2726	28	38	of	of	ADP
cana-2726	28	39	geographics	geographic	NOUN
cana-2726	28	40	area	area	NOUN
cana-2726	28	41	coverage	coverage	NOUN
cana-2726	28	42	as	as	ADV
cana-2726	28	43	well	well	ADV
cana-2726	28	44	as	as	ADP
cana-2726	28	45	multi	multi	ADJ
cana-2726	28	46	temporal	temporal	ADJ
cana-2726	28	47	based	base	VERB
cana-2726	28	48	satellite	satellite	NOUN
cana-2726	28	49	images	image	NOUN
cana-2726	28	50	that	that	PRON
cana-2726	28	51	provide	provide	VERB
cana-2726	28	52	high	high	ADJ
cana-2726	28	53	cost	cost	NOUN
cana-2726	28	54	effective	effective	ADJ
cana-2726	28	55	and	and	CCONJ
cana-2726	28	56	effective	effective	ADJ
cana-2726	28	57	approach	approach	NOUN
cana-2726	28	58	to	to	ADP
cana-2726	28	59	accurately	accurately	ADV
cana-2726	28	60	monitoring	monitor	VERB
cana-2726	28	61	various	various	ADJ
cana-2726	28	62	changes	change	NOUN
cana-2726	28	63	in	in	ADP
cana-2726	28	64	the	the	DET
cana-2726	28	65	earth	earth	NOUN
cana-2726	28	66	’s	’s	PART
cana-2726	28	67	area	area	NOUN
cana-2726	29	1	[	[	X
cana-2726	29	2	3	3	NUM
cana-2726	29	3	]	]	PUNCT
cana-2726	29	4	.	.	PUNCT
cana-2726	30	1	l.	l.	PROPN
cana-2726	30	2	castellana	castellana	PROPN
cana-2726	30	3	et	et	PROPN
cana-2726	30	4	al	al	PROPN
cana-2726	30	5	.	.	PUNCT
cana-2726	31	1	[	[	X
cana-2726	31	2	4	4	X
cana-2726	31	3	]	]	PUNCT
cana-2726	31	4	studied	study	VERB
cana-2726	31	5	a	a	DET
cana-2726	31	6	novel	novel	ADJ
cana-2726	31	7	approach	approach	NOUN
cana-2726	31	8	of	of	ADP
cana-2726	31	9	change	change	NOUN
cana-2726	31	10	detection	detection	NOUN
cana-2726	31	11	,	,	PUNCT
cana-2726	31	12	named	name	VERB
cana-2726	31	13	transition	transition	NOUN
cana-2726	31	14	based	base	VERB
cana-2726	31	15	driven	drive	VERB
cana-2726	31	16	(	(	PUNCT
cana-2726	31	17	td	td	NOUN
cana-2726	31	18	)	)	PUNCT
cana-2726	31	19	–	–	PUNCT
cana-2726	31	20	post	post	VERB
cana-2726	31	21	classification	classification	NOUN
cana-2726	31	22	level	level	NOUN
cana-2726	31	23	of	of	ADP
cana-2726	31	24	comparison	comparison	NOUN
cana-2726	31	25	(	(	PUNCT
cana-2726	31	26	pcc	pcc	NOUN
cana-2726	31	27	)	)	PUNCT
cana-2726	31	28	based	base	VERB
cana-2726	31	29	on	on	ADP
cana-2726	31	30	combination	combination	NOUN
cana-2726	31	31	of	of	ADP
cana-2726	31	32	both	both	CCONJ
cana-2726	31	33	the	the	DET
cana-2726	31	34	supervised	supervised	ADJ
cana-2726	31	35	algorithms	algorithm	NOUN
cana-2726	31	36	along	along	ADP
cana-2726	31	37	with	with	ADP
cana-2726	31	38	and	and	CCONJ
cana-2726	31	39	unsupervised	unsupervised	ADJ
cana-2726	31	40	algorithms	algorithm	NOUN
cana-2726	31	41	.	.	PUNCT
cana-2726	32	1	the	the	DET
cana-2726	32	2	advanced	advanced	ADJ
cana-2726	32	3	td	td	NOUN
cana-2726	32	4	-	-	PUNCT
cana-2726	32	5	pcc	pcc	NOUN
cana-2726	32	6	method	method	NOUN
cana-2726	32	7	is	be	AUX
cana-2726	32	8	based	base	VERB
cana-2726	32	9	on	on	ADP
cana-2726	32	10	the	the	DET
cana-2726	32	11	class	class	NOUN
cana-2726	32	12	transition	transition	NOUN
cana-2726	32	13	support	support	NOUN
cana-2726	32	14	matrix	matrix	NOUN
cana-2726	32	15	to	to	ADP
cana-2726	32	16	accurate	accurate	ADJ
cana-2726	32	17	correction	correction	NOUN
cana-2726	32	18	of	of	ADP
cana-2726	32	19	change	change	NOUN
cana-2726	32	20	produced	produce	VERB
cana-2726	32	21	by	by	ADP
cana-2726	32	22	an	an	DET
cana-2726	32	23	advanced	advance	VERB
cana-2726	32	24	supervised	supervise	VERB
cana-2726	32	25	based	base	VERB
cana-2726	32	26	pcc	pcc	NOUN
cana-2726	32	27	method	method	NOUN
cana-2726	32	28	as	as	ADV
cana-2726	32	29	well	well	ADV
cana-2726	32	30	as	as	ADP
cana-2726	32	31	a	a	DET
cana-2726	32	32	class	class	NOUN
cana-2726	32	33	transition	transition	NOUN
cana-2726	32	34	matrix	matrix	NOUN
cana-2726	32	35	both	both	PRON
cana-2726	32	36	are	be	AUX
cana-2726	32	37	automatically	automatically	ADV
cana-2726	32	38	obtained	obtain	VERB
cana-2726	32	39	data	datum	NOUN
cana-2726	32	40	from	from	ADP
cana-2726	32	41	simply	simply	ADV
cana-2726	32	42	an	an	DET
cana-2726	32	43	unsupervised	unsupervised	ADJ
cana-2726	32	44	based	base	VERB
cana-2726	32	45	effective	effective	ADJ
cana-2726	32	46	change	change	NOUN
cana-2726	32	47	detection	detection	NOUN
cana-2726	32	48	technique	technique	NOUN
cana-2726	32	49	.	.	PUNCT
cana-2726	33	1	prabuddh	prabuddh	PROPN
cana-2726	33	2	kumar	kumar	PROPN
cana-2726	33	3	mishra	mishra	PROPN
cana-2726	33	4	et	et	PROPN
cana-2726	33	5	al	al	PROPN
cana-2726	33	6	.	.	PUNCT
cana-2726	34	1	[	[	X
cana-2726	34	2	5	5	NUM
cana-2726	34	3	]	]	PUNCT
cana-2726	34	4	studied	study	VERB
cana-2726	34	5	the	the	DET
cana-2726	34	6	change	change	NOUN
cana-2726	34	7	detection	detection	NOUN
cana-2726	34	8	of	of	ADP
cana-2726	34	9	land	land	NOUN
cana-2726	34	10	usage	usage	NOUN
cana-2726	34	11	and	and	CCONJ
cana-2726	34	12	land	land	NOUN
cana-2726	34	13	coverage	coverage	NOUN
cana-2726	34	14	in	in	ADP
cana-2726	34	15	rani	rani	PROPN
cana-2726	34	16	khola	khola	PROPN
cana-2726	34	17	watershed	watershed	PROPN
cana-2726	34	18	of	of	ADP
cana-2726	34	19	state	state	NOUN
cana-2726	34	20	of	of	ADP
cana-2726	34	21	sikkim	sikkim	PROPN
cana-2726	34	22	eastern	eastern	PROPN
cana-2726	34	23	himalaya	himalaya	PROPN
cana-2726	34	24	,	,	PUNCT
cana-2726	34	25	using	use	VERB
cana-2726	34	26	supervised	supervised	ADJ
cana-2726	34	27	classification	classification	NOUN
cana-2726	34	28	based	base	VERB
cana-2726	34	29	on	on	ADP
cana-2726	34	30	advanced	advanced	ADJ
cana-2726	34	31	maximum	maximum	ADJ
cana-2726	34	32	likelihood	likelihood	NOUN
cana-2726	34	33	classifier	classifier	NOUN
cana-2726	34	34	from	from	ADP
cana-2726	34	35	landsat-5	landsat-5	PROPN
cana-2726	34	36	satellite	satellite	NOUN
cana-2726	34	37	images	image	NOUN
cana-2726	34	38	with	with	ADP
cana-2726	34	39	an	an	DET
cana-2726	34	40	advanced	advanced	ADJ
cana-2726	34	41	thematic	thematic	ADJ
cana-2726	34	42	based	base	VERB
cana-2726	34	43	mapper	mapper	NOUN
cana-2726	34	44	(	(	PUNCT
cana-2726	34	45	tm	tm	NOUN
cana-2726	34	46	)	)	PUNCT
cana-2726	34	47	and	and	CCONJ
cana-2726	35	1	remote	remote	ADJ
cana-2726	35	2	sensing	sense	VERB
cana-2726	35	3	sentinel	sentinel	NOUN
cana-2726	35	4	type_2a	type_2a	PROPN
cana-2726	35	5	(	(	PUNCT
cana-2726	35	6	13	13	NUM
cana-2726	35	7	spectral	spectral	ADJ
cana-2726	35	8	band	band	NOUN
cana-2726	35	9	)	)	PUNCT
cana-2726	35	10	multispectral	multispectral	ADJ
cana-2726	35	11	instrument	instrument	NOUN
cana-2726	35	12	(	(	PUNCT
cana-2726	35	13	msi	msi	PROPN
cana-2726	35	14	)	)	PUNCT
cana-2726	35	15	for	for	ADP
cana-2726	35	16	the	the	DET
cana-2726	35	17	periods	period	NOUN
cana-2726	35	18	1988	1988	NUM
cana-2726	35	19	to	to	ADP
cana-2726	35	20	2017	2017	NUM
cana-2726	35	21	.	.	PUNCT
cana-2726	36	1	nishant	nishant	PROPN
cana-2726	36	2	mehra	mehra	PROPN
cana-2726	36	3	et	et	PROPN
cana-2726	36	4	al	al	PROPN
cana-2726	36	5	.	.	PUNCT
cana-2726	37	1	[	[	X
cana-2726	37	2	6	6	NUM
cana-2726	37	3	]	]	PUNCT
cana-2726	37	4	integrated	integrate	VERB
cana-2726	37	5	artificial	artificial	ADJ
cana-2726	37	6	neural	neural	ADJ
cana-2726	37	7	network	network	NOUN
cana-2726	37	8	(	(	PUNCT
cana-2726	37	9	ann	ann	PROPN
cana-2726	37	10	)	)	PUNCT
cana-2726	37	11	with	with	ADP
cana-2726	37	12	a	a	DET
cana-2726	37	13	cellular	cellular	ADJ
cana-2726	37	14	automata	automata	NOUN
cana-2726	37	15	(	(	PUNCT
cana-2726	37	16	ca	ca	NOUN
cana-2726	37	17	)	)	PUNCT
cana-2726	37	18	for	for	ADP
cana-2726	37	19	predicated	predicate	VERB
cana-2726	37	20	land	land	NOUN
cana-2726	37	21	usage	usage	NOUN
cana-2726	37	22	and	and	CCONJ
cana-2726	37	23	land	land	NOUN
cana-2726	37	24	coverage	coverage	NOUN
cana-2726	37	25	maps	map	NOUN
cana-2726	37	26	for	for	ADP
cana-2726	37	27	periods	period	NOUN
cana-2726	37	28	of	of	ADP
cana-2726	37	29	2025	2025	NUM
cana-2726	37	30	and	and	CCONJ
cana-2726	37	31	2040	2040	NUM
cana-2726	37	32	.	.	PUNCT
cana-2726	38	1	the	the	DET
cana-2726	38	2	ann_ca	ann_ca	NOUN
cana-2726	38	3	model	model	NOUN
cana-2726	38	4	is	be	AUX
cana-2726	38	5	included	include	VERB
cana-2726	38	6	six	six	NUM
cana-2726	38	7	important	important	ADJ
cana-2726	38	8	factors	factor	NOUN
cana-2726	38	9	,	,	PUNCT
cana-2726	38	10	the	the	DET
cana-2726	38	11	four	four	NUM
cana-2726	38	12	factors	factor	NOUN
cana-2726	38	13	were	be	AUX
cana-2726	38	14	based	base	VERB
cana-2726	38	15	on	on	ADP
cana-2726	38	16	socio	socio	NOUN
cana-2726	38	17	economic	economic	ADJ
cana-2726	38	18	parameters	parameter	NOUN
cana-2726	38	19	such	such	ADJ
cana-2726	38	20	as	as	ADP
cana-2726	38	21	roads	road	NOUN
cana-2726	38	22	,	,	PUNCT
cana-2726	38	23	centre	centre	NOUN
cana-2726	38	24	of	of	ADP
cana-2726	38	25	city	city	NOUN
cana-2726	38	26	,	,	PUNCT
cana-2726	38	27	built	build	VERB
cana-2726	38	28	-	-	PUNCT
cana-2726	38	29	up	up	ADP
cana-2726	38	30	coverage	coverage	NOUN
cana-2726	38	31	areas	area	NOUN
cana-2726	38	32	and	and	CCONJ
cana-2726	38	33	streams	stream	NOUN
cana-2726	38	34	:	:	PUNCT
cana-2726	38	35	while	while	SCONJ
cana-2726	38	36	remaining	remain	VERB
cana-2726	38	37	two	two	NUM
cana-2726	38	38	factors	factor	NOUN
cana-2726	38	39	were	be	AUX
cana-2726	38	40	based	base	VERB
cana-2726	38	41	on	on	ADP
cana-2726	38	42	geospatial	geospatial	ADJ
cana-2726	38	43	data	datum	NOUN
cana-2726	38	44	parameters	parameter	NOUN
cana-2726	38	45	such	such	ADJ
cana-2726	38	46	as	as	ADP
cana-2726	38	47	slope	slope	NOUN
cana-2726	38	48	and	and	CCONJ
cana-2726	38	49	elevation	elevation	NOUN
cana-2726	38	50	.	.	PUNCT
cana-2726	39	1	there	there	ADV
cana-2726	39	2	all	all	DET
cana-2726	39	3	six	six	NUM
cana-2726	39	4	factors	factor	NOUN
cana-2726	39	5	’	'	PUNCT
cana-2726	39	6	combinations	combination	NOUN
cana-2726	39	7	performed	perform	VERB
cana-2726	39	8	the	the	DET
cana-2726	39	9	highest	high	ADJ
cana-2726	39	10	level	level	NOUN
cana-2726	39	11	of	of	ADP
cana-2726	39	12	accuracy	accuracy	NOUN
cana-2726	39	13	of	of	ADP
cana-2726	39	14	87.84	87.84	NUM
cana-2726	39	15	%	%	NOUN
cana-2726	39	16	in	in	ADP
cana-2726	39	17	ann_ca	ann_ca	PROPN
cana-2726	39	18	model	model	PROPN
cana-2726	39	19	.	.	PUNCT
cana-2726	40	1	bipin	bipin	NOUN
cana-2726	40	2	shah	shah	PROPN
cana-2726	40	3	et	et	PROPN
cana-2726	40	4	al	al	PROPN
cana-2726	40	5	.	.	PUNCT
cana-2726	41	1	[	[	X
cana-2726	41	2	7	7	NUM
cana-2726	41	3	]	]	PUNCT
cana-2726	41	4	developed	develop	VERB
cana-2726	41	5	a	a	DET
cana-2726	41	6	new	new	ADJ
cana-2726	41	7	framework	framework	NOUN
cana-2726	41	8	based	base	VERB
cana-2726	41	9	on	on	ADP
cana-2726	41	10	change	change	NOUN
cana-2726	41	11	detection	detection	NOUN
cana-2726	41	12	(	(	PUNCT
cana-2726	41	13	cd	cd	NOUN
cana-2726	41	14	)	)	PUNCT
cana-2726	41	15	algorithm	algorithm	NOUN
cana-2726	41	16	of	of	ADP
cana-2726	41	17	machine	machine	NOUN
cana-2726	41	18	learning	learn	VERB
cana-2726	41	19	with	with	ADP
cana-2726	41	20	combination	combination	NOUN
cana-2726	41	21	of	of	ADP
cana-2726	41	22	advanced	advanced	ADJ
cana-2726	41	23	particle	particle	NOUN
cana-2726	41	24	swarm	swarm	NOUN
cana-2726	41	25	optimization	optimization	NOUN
cana-2726	41	26	(	(	PUNCT
cana-2726	41	27	pso	pso	NOUN
cana-2726	41	28	)	)	PUNCT
cana-2726	41	29	and	and	CCONJ
cana-2726	41	30	new	new	ADJ
cana-2726	41	31	approach	approach	NOUN
cana-2726	41	32	of	of	ADP
cana-2726	41	33	support	support	NOUN
cana-2726	41	34	vector	vector	NOUN
cana-2726	41	35	machines	machine	NOUN
cana-2726	41	36	(	(	PUNCT
cana-2726	41	37	svm	svm	PROPN
cana-2726	41	38	)	)	PUNCT
cana-2726	41	39	which	which	PRON
cana-2726	41	40	provides	provide	VERB
cana-2726	41	41	expressive	expressive	ADJ
cana-2726	41	42	improvement	improvement	NOUN
cana-2726	41	43	in	in	ADP
cana-2726	41	44	overall	overall	ADJ
cana-2726	41	45	accuracy	accuracy	NOUN
cana-2726	41	46	.	.	PUNCT
cana-2726	42	1	sibo	sibo	PROPN
cana-2726	42	2	yu	yu	PROPN
cana-2726	42	3	et	et	PROPN
cana-2726	42	4	al	al	PROPN
cana-2726	42	5	.	.	PUNCT
cana-2726	43	1	[	[	X
cana-2726	43	2	8	8	NUM
cana-2726	43	3	]	]	PUNCT
cana-2726	43	4	devolved	devolve	VERB
cana-2726	43	5	a	a	DET
cana-2726	43	6	framework	framework	NOUN
cana-2726	43	7	based	base	VERB
cana-2726	43	8	on	on	ADP
cana-2726	43	9	multilevel	multilevel	ADJ
cana-2726	43	10	feature	feature	NOUN
cana-2726	43	11	based	base	VERB
cana-2726	43	12	on	on	ADP
cana-2726	43	13	cross	cross	NOUN
cana-2726	43	14	fusion	fusion	NOUN
cana-2726	43	15	technique	technique	NOUN
cana-2726	43	16	(	(	PUNCT
cana-2726	43	17	multilevel_fcf	multilevel_fcf	NUM
cana-2726	43	18	)	)	PUNCT
cana-2726	43	19	with	with	ADP
cana-2726	43	20	new	new	ADJ
cana-2726	43	21	approach	approach	NOUN
cana-2726	43	22	of	of	ADP
cana-2726	43	23	3d_cnns	3d_cnns	NUM
cana-2726	43	24	technique	technique	NOUN
cana-2726	43	25	for	for	ADP
cana-2726	43	26	remote	remote	ADJ
cana-2726	43	27	sensing	sense	VERB
cana-2726	43	28	satellite	satellite	NOUN
cana-2726	43	29	images	image	NOUN
cana-2726	43	30	for	for	ADP
cana-2726	43	31	change	change	NOUN
cana-2726	43	32	detection	detection	NOUN
cana-2726	43	33	.	.	PUNCT
cana-2726	44	1	primally	primally	PROPN
cana-2726	44	2	,	,	PUNCT
cana-2726	44	3	the	the	DET
cana-2726	44	4	change	change	NOUN
cana-2726	44	5	detection	detection	NOUN
cana-2726	44	6	(	(	PUNCT
cana-2726	44	7	cd	cd	NOUN
cana-2726	44	8	)	)	PUNCT
cana-2726	44	9	method	method	NOUN
cana-2726	44	10	in	in	ADP
cana-2726	44	11	remote	remote	ADJ
cana-2726	44	12	sensing	sense	VERB
cana-2726	44	13	satellite	satellite	NOUN
cana-2726	44	14	imagery	imagery	NOUN
cana-2726	44	15	challenges	challenge	NOUN
cana-2726	44	16	due	due	ADJ
cana-2726	44	17	to	to	ADP
cana-2726	44	18	various	various	ADJ
cana-2726	44	19	complex	complex	ADJ
cana-2726	44	20	structure	structure	NOUN
cana-2726	44	21	of	of	ADP
cana-2726	44	22	similar	similar	ADJ
cana-2726	44	23	objects	object	NOUN
cana-2726	44	24	as	as	ADV
cana-2726	44	25	well	well	ADV
cana-2726	44	26	as	as	ADP
cana-2726	44	27	different	different	ADJ
cana-2726	44	28	time	time	NOUN
cana-2726	44	29	zones	zone	NOUN
cana-2726	44	30	and	and	CCONJ
cana-2726	44	31	various	various	ADJ
cana-2726	44	32	locations	location	NOUN
cana-2726	44	33	.	.	PUNCT
cana-2726	45	1	the	the	DET
cana-2726	45	2	convolutional	convolutional	ADJ
cana-2726	45	3	based	base	VERB
cana-2726	45	4	neural	neural	ADJ
cana-2726	45	5	networks	network	NOUN
cana-2726	45	6	(	(	PUNCT
cana-2726	45	7	cnns	cnns	PROPN
cana-2726	45	8	)	)	PUNCT
cana-2726	45	9	have	have	AUX
cana-2726	45	10	presented	present	VERB
cana-2726	45	11	high	high	ADJ
cana-2726	45	12	performance	performance	NOUN
cana-2726	45	13	in	in	ADP
cana-2726	45	14	change	change	NOUN
cana-2726	45	15	detection	detection	NOUN
cana-2726	45	16	(	(	PUNCT
cana-2726	45	17	cd	cd	PROPN
cana-2726	45	18	)	)	PUNCT
cana-2726	45	19	by	by	ADP
cana-2726	45	20	effectively	effectively	ADV
cana-2726	45	21	extracted	extract	VERB
cana-2726	45	22	semantic	semantic	ADJ
cana-2726	45	23	level	level	NOUN
cana-2726	45	24	of	of	ADP
cana-2726	45	25	features	feature	NOUN
cana-2726	45	26	.	.	PUNCT
cana-2726	46	1	the	the	DET
cana-2726	46	2	traditional	traditional	ADJ
cana-2726	46	3	approach	approach	NOUN
cana-2726	46	4	of	of	ADP
cana-2726	46	5	2d	2d	NOUN
cana-2726	46	6	-	-	PUNCT
cana-2726	46	7	cnns	cnns	ADJ
cana-2726	46	8	method	method	NOUN
cana-2726	46	9	may	may	AUX
cana-2726	46	10	huge	huge	ADJ
cana-2726	46	11	struggle	struggle	NOUN
cana-2726	46	12	to	to	PART
cana-2726	46	13	extract	extract	VERB
cana-2726	46	14	the	the	DET
cana-2726	46	15	deep	deep	ADJ
cana-2726	46	16	features	feature	NOUN
cana-2726	46	17	from	from	ADP
cana-2726	46	18	specially	specially	ADV
cana-2726	46	19	multitemporal	multitemporal	ADJ
cana-2726	46	20	satellite	satellite	NOUN
cana-2726	46	21	images	image	NOUN
cana-2726	46	22	.	.	PUNCT
cana-2726	47	1	author	author	NOUN
cana-2726	47	2	gong	gong	PROPN
cana-2726	47	3	,	,	PUNCT
cana-2726	47	4	m.	m.	NOUN
cana-2726	47	5	et	et	PROPN
cana-2726	47	6	al	al	PROPN
cana-2726	47	7	.	.	PUNCT
cana-2726	48	1	[	[	X
cana-2726	48	2	9	9	NUM
cana-2726	48	3	]	]	PUNCT
cana-2726	48	4	introduced	introduce	VERB
cana-2726	48	5	the	the	DET
cana-2726	48	6	advanced	advanced	ADJ
cana-2726	48	7	remote	remote	ADJ
cana-2726	48	8	sensing	sensing	NOUN
cana-2726	48	9	-	-	PUNCT
cana-2726	48	10	based	base	VERB
cana-2726	48	11	satellite	satellite	NOUN
cana-2726	48	12	images	image	NOUN
cana-2726	48	13	change	change	NOUN
cana-2726	48	14	detection	detection	NOUN
cana-2726	48	15	technique	technique	NOUN
cana-2726	48	16	that	that	PRON
cana-2726	48	17	mainly	mainly	ADV
cana-2726	48	18	combines	combine	VERB
cana-2726	48	19	with	with	ADP
cana-2726	48	20	2d	2d	NOUN
cana-2726	48	21	-	-	PUNCT
cana-2726	48	22	cnns	cnns	ADJ
cana-2726	48	23	and	and	CCONJ
cana-2726	48	24	principal	principal	ADJ
cana-2726	48	25	components	component	NOUN
cana-2726	48	26	analysis	analysis	NOUN
cana-2726	48	27	(	(	PUNCT
cana-2726	48	28	pca	pca	NOUN
cana-2726	48	29	)	)	PUNCT
cana-2726	48	30	to	to	PART
cana-2726	48	31	accurately	accurately	ADV
cana-2726	48	32	enhance	enhance	VERB
cana-2726	48	33	remote	remote	ADJ
cana-2726	48	34	sensing	sense	VERB
cana-2726	48	35	satellite	satellite	NOUN
cana-2726	48	36	images	image	NOUN
cana-2726	48	37	change	change	NOUN
cana-2726	48	38	detection	detection	NOUN
cana-2726	48	39	performance	performance	NOUN
cana-2726	48	40	.	.	PUNCT
cana-2726	49	1	https://ieeexplore.ieee.org/author/168533137720687	https://ieeexplore.ieee.org/author/168533137720687	NOUN
cana-2726	49	2	communications	communication	NOUN
cana-2726	49	3	on	on	ADP
cana-2726	49	4	applied	apply	VERB
cana-2726	49	5	nonlinear	nonlinear	ADJ
cana-2726	49	6	analysis	analysis	NOUN
cana-2726	49	7	issn	issn	NOUN
cana-2726	49	8	:	:	PUNCT
cana-2726	49	9	1074	1074	NUM
cana-2726	49	10	-	-	PUNCT
cana-2726	49	11	133x	133x	NUM
cana-2726	49	12	vol	vol	NOUN
cana-2726	49	13	32	32	NUM
cana-2726	49	14	no	no	NOUN
cana-2726	49	15	.	.	PUNCT
cana-2726	50	1	3s	3s	NUM
cana-2726	50	2	(	(	PUNCT
cana-2726	50	3	2025	2025	NUM
cana-2726	50	4	)	)	PUNCT
cana-2726	50	5	683	683	NUM
cana-2726	50	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	50	7	the	the	DET
cana-2726	50	8	main	main	ADJ
cana-2726	50	9	aim	aim	NOUN
cana-2726	50	10	of	of	ADP
cana-2726	50	11	our	our	PRON
cana-2726	50	12	research	research	NOUN
cana-2726	50	13	study	study	NOUN
cana-2726	50	14	is	be	AUX
cana-2726	50	15	improved	improve	VERB
cana-2726	50	16	the	the	DET
cana-2726	50	17	high	high	ADJ
cana-2726	50	18	accuracy	accuracy	NOUN
cana-2726	50	19	along	along	ADP
cana-2726	50	20	with	with	ADP
cana-2726	50	21	exhaustiveness	exhaustiveness	NOUN
cana-2726	50	22	of	of	ADP
cana-2726	50	23	urban	urban	ADJ
cana-2726	50	24	change	change	NOUN
cana-2726	50	25	detection	detection	NOUN
cana-2726	50	26	by	by	ADP
cana-2726	50	27	effectively	effectively	ADV
cana-2726	50	28	the	the	DET
cana-2726	50	29	extraction	extraction	NOUN
cana-2726	50	30	of	of	ADP
cana-2726	50	31	spatial	spatial	ADJ
cana-2726	50	32	spectral	spectral	ADJ
cana-2726	50	33	information	information	NOUN
cana-2726	50	34	and	and	CCONJ
cana-2726	50	35	predominant	predominant	VERB
cana-2726	50	36	the	the	DET
cana-2726	50	37	limitations	limitation	NOUN
cana-2726	50	38	of	of	ADP
cana-2726	50	39	usual	usual	ADJ
cana-2726	50	40	change	change	NOUN
cana-2726	50	41	detection	detection	NOUN
cana-2726	50	42	(	(	PUNCT
cana-2726	50	43	cd	cd	NOUN
cana-2726	50	44	)	)	PUNCT
cana-2726	50	45	methods	method	NOUN
cana-2726	50	46	.	.	PUNCT
cana-2726	51	1	the	the	DET
cana-2726	51	2	research	research	NOUN
cana-2726	51	3	study	study	NOUN
cana-2726	51	4	is	be	AUX
cana-2726	51	5	introduced	introduce	VERB
cana-2726	51	6	a	a	DET
cana-2726	51	7	new	new	ADJ
cana-2726	51	8	msmd_cnn	msmd_cnn	NUM
cana-2726	51	9	model	model	NOUN
cana-2726	51	10	-	-	PUNCT
cana-2726	51	11	based	base	VERB
cana-2726	51	12	change	change	NOUN
cana-2726	51	13	detection	detection	NOUN
cana-2726	51	14	method	method	NOUN
cana-2726	51	15	that	that	PRON
cana-2726	51	16	considers	consider	VERB
cana-2726	51	17	the	the	DET
cana-2726	51	18	high	high	ADJ
cana-2726	51	19	level	level	NOUN
cana-2726	51	20	of	of	ADP
cana-2726	51	21	detailed	detailed	ADJ
cana-2726	51	22	information	information	NOUN
cana-2726	51	23	.	.	PUNCT
cana-2726	52	1	the	the	DET
cana-2726	52	2	overall	overall	ADJ
cana-2726	52	3	performance	performance	NOUN
cana-2726	52	4	of	of	ADP
cana-2726	52	5	the	the	DET
cana-2726	52	6	proposed	propose	VERB
cana-2726	52	7	msmd_cnns	msmd_cnns	NOUN
cana-2726	52	8	model	model	NOUN
cana-2726	52	9	is	be	AUX
cana-2726	52	10	accurately	accurately	ADV
cana-2726	52	11	evaluated	evaluate	VERB
cana-2726	52	12	against	against	ADP
cana-2726	52	13	both	both	DET
cana-2726	52	14	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	52	15	and	and	CCONJ
cana-2726	52	16	support	support	VERB
cana-2726	52	17	vector	vector	NOUN
cana-2726	52	18	analysis	analysis	NOUN
cana-2726	52	19	(	(	PUNCT
cana-2726	52	20	svm	svm	ADJ
cana-2726	52	21	)	)	PUNCT
cana-2726	52	22	algorithms	algorithm	NOUN
cana-2726	52	23	.	.	PUNCT
cana-2726	53	1	comparatively	comparatively	ADV
cana-2726	53	2	analysis	analysis	NOUN
cana-2726	53	3	with	with	ADP
cana-2726	53	4	cva	cva	PROPN
cana-2726	53	5	and	and	CCONJ
cana-2726	53	6	svm	svm	PROPN
cana-2726	53	7	,	,	PUNCT
cana-2726	53	8	the	the	DET
cana-2726	53	9	proposed	propose	VERB
cana-2726	53	10	method	method	NOUN
cana-2726	53	11	msmd_cnns	msmd_cnns	PROPN
cana-2726	53	12	is	be	AUX
cana-2726	53	13	excellence	excellence	NOUN
cana-2726	53	14	and	and	CCONJ
cana-2726	53	15	provide	provide	VERB
cana-2726	53	16	high	high	ADJ
cana-2726	53	17	reliability	reliability	NOUN
cana-2726	53	18	and	and	CCONJ
cana-2726	53	19	accuracy	accuracy	NOUN
cana-2726	53	20	.	.	PUNCT
cana-2726	54	1	2	2	X
cana-2726	54	2	.	.	X
cana-2726	54	3	methodology	methodology	NOUN
cana-2726	54	4	:	:	PUNCT
cana-2726	54	5	in	in	ADP
cana-2726	54	6	our	our	PRON
cana-2726	54	7	research	research	NOUN
cana-2726	54	8	study	study	NOUN
cana-2726	54	9	,	,	PUNCT
cana-2726	54	10	the	the	DET
cana-2726	54	11	proposed	propose	VERB
cana-2726	54	12	msmd_cnn	msmd_cnn	NUM
cana-2726	54	13	cd	cd	NOUN
cana-2726	54	14	method	method	NOUN
cana-2726	54	15	is	be	AUX
cana-2726	54	16	compared	compare	VERB
cana-2726	54	17	with	with	ADP
cana-2726	54	18	two	two	NUM
cana-2726	54	19	advanced	advanced	ADJ
cana-2726	54	20	cd	cd	NOUN
cana-2726	54	21	classical	classical	ADJ
cana-2726	54	22	methods	method	NOUN
cana-2726	54	23	:	:	PUNCT
cana-2726	54	24	1	1	X
cana-2726	54	25	)	)	PUNCT
cana-2726	54	26	the	the	DET
cana-2726	54	27	bi_temporal	bi_temporal	PROPN
cana-2726	54	28	change	change	NOUN
cana-2726	54	29	vector	vector	NOUN
cana-2726	54	30	analysis	analysis	NOUN
cana-2726	54	31	(	(	PUNCT
cana-2726	54	32	bi_temporal	bi_temporal	PROPN
cana-2726	54	33	cva	cva	PROPN
cana-2726	54	34	)	)	PUNCT
cana-2726	54	35	and	and	CCONJ
cana-2726	54	36	2	2	X
cana-2726	54	37	)	)	PUNCT
cana-2726	54	38	support	support	NOUN
cana-2726	54	39	vector	vector	NOUN
cana-2726	54	40	machine	machine	NOUN
cana-2726	54	41	(	(	PUNCT
cana-2726	54	42	svm	svm	PROPN
cana-2726	54	43	)	)	PUNCT
cana-2726	54	44	.	.	PUNCT
cana-2726	55	1	the	the	DET
cana-2726	55	2	working	work	VERB
cana-2726	55	3	flow	flow	NOUN
cana-2726	55	4	of	of	ADP
cana-2726	55	5	research	research	NOUN
cana-2726	55	6	study	study	NOUN
cana-2726	55	7	is	be	AUX
cana-2726	55	8	being	be	AUX
cana-2726	55	9	shown	show	VERB
cana-2726	55	10	in	in	ADP
cana-2726	55	11	figure:01	figure:01	PROPN
cana-2726	55	12	.	.	PUNCT
cana-2726	56	1	figure:01	figure:01	VERB
cana-2726	56	2	the	the	DET
cana-2726	56	3	working	work	VERB
cana-2726	56	4	flow	flow	NOUN
cana-2726	56	5	of	of	ADP
cana-2726	56	6	research	research	NOUN
cana-2726	56	7	study	study	NOUN
cana-2726	56	8	figure:01	figure:01	PROPN
cana-2726	56	9	illustrates	illustrate	VERB
cana-2726	56	10	the	the	DET
cana-2726	56	11	primary	primary	ADJ
cana-2726	56	12	steps	step	NOUN
cana-2726	56	13	of	of	ADP
cana-2726	56	14	urban	urban	ADJ
cana-2726	56	15	change	change	NOUN
cana-2726	56	16	detection	detection	NOUN
cana-2726	56	17	from	from	ADP
cana-2726	56	18	remote	remote	ADJ
cana-2726	56	19	remote	remote	ADJ
cana-2726	56	20	sensing	sense	VERB
cana-2726	56	21	satellite	satellite	NOUN
cana-2726	56	22	images	image	NOUN
cana-2726	56	23	.	.	PUNCT
cana-2726	57	1	the	the	DET
cana-2726	57	2	research	research	NOUN
cana-2726	57	3	work	work	NOUN
cana-2726	57	4	is	be	AUX
cana-2726	57	5	conducted	conduct	VERB
cana-2726	57	6	following	follow	VERB
cana-2726	57	7	analysis	analysis	NOUN
cana-2726	57	8	:	:	PUNCT
cana-2726	57	9	1	1	NUM
cana-2726	57	10	)	)	PUNCT
cana-2726	57	11	first	first	ADJ
cana-2726	57	12	step	step	NOUN
cana-2726	57	13	to	to	PART
cana-2726	57	14	load	load	VERB
cana-2726	57	15	the	the	DET
cana-2726	57	16	landsat-8	landsat-8	PROPN
cana-2726	57	17	satellite	satellite	NOUN
cana-2726	57	18	data	datum	NOUN
cana-2726	57	19	over	over	ADP
cana-2726	57	20	the	the	DET
cana-2726	57	21	area	area	NOUN
cana-2726	57	22	of	of	ADP
cana-2726	57	23	city	city	NOUN
cana-2726	57	24	/	/	SYM
cana-2726	57	25	region	region	NOUN
cana-2726	57	26	of	of	ADP
cana-2726	57	27	interest	interest	NOUN
cana-2726	57	28	(	(	PUNCT
cana-2726	57	29	roi	roi	NOUN
cana-2726	57	30	)	)	PUNCT
cana-2726	57	31	2	2	NUM
cana-2726	57	32	)	)	PUNCT
cana-2726	57	33	collected	collect	VERB
cana-2726	57	34	of	of	ADP
cana-2726	57	35	testing	testing	NOUN
cana-2726	57	36	and	and	CCONJ
cana-2726	57	37	training	training	NOUN
cana-2726	57	38	samples	sample	NOUN
cana-2726	57	39	3	3	NUM
cana-2726	57	40	)	)	PUNCT
cana-2726	57	41	apply	apply	VERB
cana-2726	57	42	pre	pre	ADJ
cana-2726	57	43	-	-	ADJ
cana-2726	57	44	processing	processing	ADJ
cana-2726	57	45	method	method	NOUN
cana-2726	57	46	4	4	NUM
cana-2726	57	47	)	)	PUNCT
cana-2726	57	48	apply	apply	VERB
cana-2726	57	49	proposed	propose	VERB
cana-2726	57	50	msmd_cnn	msmd_cnn	NUM
cana-2726	57	51	with	with	ADP
cana-2726	57	52	bi_temporal	bi_temporal	PROPN
cana-2726	57	53	cva	cva	PROPN
cana-2726	57	54	and	and	CCONJ
cana-2726	57	55	svm	svm	ADJ
cana-2726	57	56	cd	cd	PROPN
cana-2726	57	57	methods	method	NOUN
cana-2726	57	58	5	5	NUM
cana-2726	57	59	)	)	PUNCT
cana-2726	57	60	change	change	NOUN
cana-2726	57	61	maps	map	NOUN
cana-2726	57	62	are	be	AUX
cana-2726	57	63	generated	generate	VERB
cana-2726	57	64	by	by	ADP
cana-2726	57	65	using	use	VERB
cana-2726	57	66	msms_cnn	msms_cnn	NUM
cana-2726	57	67	,	,	PUNCT
cana-2726	57	68	bi_temporal	bi_temporal	PROPN
cana-2726	57	69	cvm	cvm	PROPN
cana-2726	57	70	and	and	CCONJ
cana-2726	57	71	svm	svm	PROPN
cana-2726	57	72	6	6	NUM
cana-2726	57	73	)	)	PUNCT
cana-2726	57	74	finally	finally	ADV
cana-2726	57	75	,	,	PUNCT
cana-2726	57	76	binary	binary	PROPN
cana-2726	57	77	generated	generate	VERB
cana-2726	57	78	change	change	NOUN
cana-2726	57	79	maps	map	NOUN
cana-2726	57	80	are	be	AUX
cana-2726	57	81	accurately	accurately	ADV
cana-2726	57	82	evaluated	evaluate	VERB
cana-2726	57	83	and	and	CCONJ
cana-2726	57	84	compared	compare	VERB
cana-2726	57	85	.	.	PUNCT
cana-2726	57	86	2.1	2.1	NUM
cana-2726	57	87	)	)	PUNCT
cana-2726	57	88	bitemporal	bitemporal	NOUN
cana-2726	57	89	_	_	PUNCT
cana-2726	57	90	change	change	NOUN
cana-2726	57	91	vector	vector	NOUN
cana-2726	57	92	analysis	analysis	NOUN
cana-2726	57	93	(	(	PUNCT
cana-2726	57	94	cva	cva	PROPN
cana-2726	57	95	):	):	PUNCT
cana-2726	57	96	the	the	DET
cana-2726	57	97	advanced	advanced	ADJ
cana-2726	57	98	change	change	NOUN
cana-2726	57	99	vector	vector	NOUN
cana-2726	57	100	analysis	analysis	NOUN
cana-2726	57	101	(	(	PUNCT
cana-2726	57	102	cva	cva	NOUN
cana-2726	57	103	)	)	PUNCT
cana-2726	57	104	was	be	AUX
cana-2726	57	105	firstly	firstly	ADV
cana-2726	57	106	introduced	introduce	VERB
cana-2726	57	107	by	by	ADP
cana-2726	57	108	malila	malila	NOUN
cana-2726	57	109	in	in	ADP
cana-2726	57	110	1980	1980	NUM
cana-2726	57	111	and	and	CCONJ
cana-2726	57	112	implemented	implement	VERB
cana-2726	57	113	for	for	ADP
cana-2726	57	114	forest	forest	NOUN
cana-2726	57	115	change	change	NOUN
cana-2726	57	116	detection	detection	NOUN
cana-2726	57	117	with	with	ADP
cana-2726	57	118	landsat	landsat	PROPN
cana-2726	57	119	satellite	satellite	NOUN
cana-2726	57	120	images	image	NOUN
cana-2726	57	121	.	.	PUNCT
cana-2726	58	1	the	the	DET
cana-2726	58	2	necessarily	necessarily	ADV
cana-2726	58	3	to	to	PART
cana-2726	58	4	monitor	monitor	VERB
cana-2726	58	5	a	a	DET
cana-2726	58	6	complete	complete	ADJ
cana-2726	58	7	earth	earth	NOUN
cana-2726	58	8	’s	’s	PART
cana-2726	58	9	surface	surface	NOUN
cana-2726	58	10	over	over	ADP
cana-2726	58	11	a	a	DET
cana-2726	58	12	range	range	NOUN
cana-2726	58	13	of	of	ADP
cana-2726	58	14	both	both	CCONJ
cana-2726	58	15	spatial	spatial	ADJ
cana-2726	58	16	scale	scale	NOUN
cana-2726	58	17	and	and	CCONJ
cana-2726	58	18	temporal	temporal	ADJ
cana-2726	58	19	scale	scale	NOUN
cana-2726	58	20	are	be	AUX
cana-2726	58	21	fundamental	fundamental	ADJ
cana-2726	58	22	in	in	ADP
cana-2726	58	23	ecosystems	ecosystem	NOUN
cana-2726	58	24	management	management	NOUN
cana-2726	58	25	,	,	PUNCT
cana-2726	58	26	planning	planning	NOUN
cana-2726	58	27	,	,	PUNCT
cana-2726	58	28	effective	effective	ADJ
cana-2726	58	29	action	action	NOUN
cana-2726	58	30	plan	plan	NOUN
cana-2726	58	31	with	with	ADP
cana-2726	58	32	implementation	implementation	NOUN
cana-2726	58	33	of	of	ADP
cana-2726	58	34	various	various	ADJ
cana-2726	58	35	strategies	strategy	NOUN
cana-2726	58	36	.	.	PUNCT
cana-2726	59	1	the	the	DET
cana-2726	59	2	change	change	NOUN
cana-2726	59	3	vector	vector	NOUN
cana-2726	59	4	analysis	analysis	NOUN
cana-2726	59	5	(	(	PUNCT
cana-2726	59	6	cva	cva	NOUN
cana-2726	59	7	)	)	PUNCT
cana-2726	59	8	is	be	AUX
cana-2726	59	9	a	a	DET
cana-2726	59	10	method	method	NOUN
cana-2726	59	11	of	of	ADP
cana-2726	59	12	change	change	NOUN
cana-2726	59	13	detection	detection	NOUN
cana-2726	59	14	(	(	PUNCT
cana-2726	59	15	cd	cd	PROPN
cana-2726	59	16	)	)	PUNCT
cana-2726	59	17	that	that	PRON
cana-2726	59	18	primary	primary	NOUN
cana-2726	59	19	based	base	VERB
cana-2726	59	20	on	on	ADP
cana-2726	59	21	bi_temporal	bi_temporal	PROPN
cana-2726	59	22	method	method	NOUN
cana-2726	59	23	that	that	PRON
cana-2726	59	24	used	use	VERB
cana-2726	59	25	change	change	NOUN
cana-2726	59	26	of	of	ADP
cana-2726	59	27	magnitude	magnitude	NOUN
cana-2726	59	28	and	and	CCONJ
cana-2726	59	29	determine	determine	VERB
cana-2726	59	30	both	both	DET
cana-2726	59	31	length	length	NOUN
cana-2726	59	32	with	with	ADP
cana-2726	59	33	change	change	NOUN
cana-2726	59	34	of	of	ADP
cana-2726	59	35	direction	direction	NOUN
cana-2726	59	36	between	between	ADP
cana-2726	59	37	two	two	NUM
cana-2726	59	38	input	input	NOUN
cana-2726	59	39	(	(	PUNCT
cana-2726	59	40	spectral	spectral	ADJ
cana-2726	59	41	)	)	PUNCT
cana-2726	59	42	images	image	NOUN
cana-2726	59	43	at	at	ADP
cana-2726	59	44	different	different	ADJ
cana-2726	59	45	times	time	NOUN
cana-2726	59	46	in	in	ADP
cana-2726	59	47	figure	figure	NOUN
cana-2726	59	48	02	02	NUM
cana-2726	59	49	.	.	PUNCT
cana-2726	60	1	https://www.thesaurus.com/browse/predominant	https://www.thesaurus.com/browse/predominant	ADJ
cana-2726	60	2	communications	communication	NOUN
cana-2726	60	3	on	on	ADP
cana-2726	60	4	applied	apply	VERB
cana-2726	60	5	nonlinear	nonlinear	ADJ
cana-2726	60	6	analysis	analysis	NOUN
cana-2726	60	7	issn	issn	NOUN
cana-2726	60	8	:	:	PUNCT
cana-2726	60	9	1074	1074	NUM
cana-2726	60	10	-	-	PUNCT
cana-2726	60	11	133x	133x	NUM
cana-2726	60	12	vol	vol	NOUN
cana-2726	60	13	32	32	NUM
cana-2726	60	14	no	no	NOUN
cana-2726	60	15	.	.	PUNCT
cana-2726	61	1	3s	3s	NUM
cana-2726	61	2	(	(	PUNCT
cana-2726	61	3	2025	2025	NUM
cana-2726	61	4	)	)	PUNCT
cana-2726	61	5	684	684	NUM
cana-2726	61	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	61	7	figure	figure	NOUN
cana-2726	61	8	:	:	PUNCT
cana-2726	61	9	02	02	NUM
cana-2726	61	10	basic	basic	ADJ
cana-2726	61	11	workflow	workflow	NOUN
cana-2726	61	12	of	of	ADP
cana-2726	61	13	the	the	DET
cana-2726	61	14	bitemporal_change	bitemporal_change	PROPN
cana-2726	61	15	vector	vector	NOUN
cana-2726	61	16	analysis	analysis	NOUN
cana-2726	61	17	(	(	PUNCT
cana-2726	61	18	bi_cva	bi_cva	NOUN
cana-2726	61	19	)	)	PUNCT
cana-2726	61	20	the	the	DET
cana-2726	61	21	following	follow	VERB
cana-2726	61	22	equation	equation	NOUN
cana-2726	61	23	(	(	PUNCT
cana-2726	61	24	1	1	X
cana-2726	61	25	)	)	PUNCT
cana-2726	61	26	is	be	AUX
cana-2726	61	27	applied	apply	VERB
cana-2726	61	28	to	to	PART
cana-2726	61	29	calculated	calculate	VERB
cana-2726	61	30	the	the	DET
cana-2726	61	31	magnitude	magnitude	NOUN
cana-2726	61	32	of	of	ADP
cana-2726	61	33	change	change	NOUN
cana-2726	61	34	vector	vector	NOUN
cana-2726	61	35	in	in	ADP
cana-2726	61	36	images	image	NOUN
cana-2726	61	37	of	of	ADP
cana-2726	61	38	various	various	ADJ
cana-2726	61	39	regions	region	NOUN
cana-2726	61	40	in	in	ADP
cana-2726	61	41	which	which	PRON
cana-2726	61	42	transformed	transform	VERB
cana-2726	61	43	data	datum	NOUN
cana-2726	61	44	is	be	AUX
cana-2726	61	45	represented	represent	VERB
cana-2726	61	46	by	by	ADP
cana-2726	61	47	“	"	PUNCT
cana-2726	61	48	𝞓	𝞓	PROPN
cana-2726	61	49	h	h	NOUN
cana-2726	61	50	”	"	PUNCT
cana-2726	61	51	that	that	PRON
cana-2726	61	52	simply	simply	ADV
cana-2726	61	53	lies	lie	VERB
cana-2726	61	54	between	between	ADP
cana-2726	61	55	two	two	NUM
cana-2726	61	56	different	different	ADJ
cana-2726	61	57	multitemporal	multitemporal	ADJ
cana-2726	61	58	approach	approach	NOUN
cana-2726	61	59	image	image	NOUN
cana-2726	61	60	t1	t1	NOUN
cana-2726	61	61	and	and	CCONJ
cana-2726	61	62	image	image	NOUN
cana-2726	61	63	t2	t2	NOUN
cana-2726	61	64	(	(	PUNCT
cana-2726	61	65	t1	t1	NOUN
cana-2726	61	66	:	:	PUNCT
cana-2726	61	67	2014	2014	NUM
cana-2726	61	68	and	and	CCONJ
cana-2726	61	69	t2:2020	t2:2020	NOUN
cana-2726	61	70	)	)	PUNCT
cana-2726	61	71	captured	capture	VERB
cana-2726	61	72	for	for	ADP
cana-2726	61	73	given	give	VERB
cana-2726	61	74	pixel	pixel	NOUN
cana-2726	61	75	by	by	ADP
cana-2726	61	76	y=	y=	PROPN
cana-2726	61	77	(	(	PUNCT
cana-2726	61	78	y1	y1	PROPN
cana-2726	61	79	,	,	PUNCT
cana-2726	61	80	y2	y2	PROPN
cana-2726	61	81	,	,	PUNCT
cana-2726	61	82	y3,	y3,	NOUN
cana-2726	61	83	…	…	SYM
cana-2726	61	84	..	..	PUNCT
cana-2726	61	85	yi	yi	NUM
cana-2726	61	86	)	)	PUNCT
cana-2726	61	87	t1	t1	NOUN
cana-2726	61	88	and	and	CCONJ
cana-2726	61	89	x=(x1,x2,x3,	x=(x1,x2,x3,	PROPN
cana-2726	61	90	…	…	SYM
cana-2726	61	91	xi	xi	X
cana-2726	61	92	)	)	PUNCT
cana-2726	61	93	t2	t2	NOUN
cana-2726	61	94	respectively	respectively	ADV
cana-2726	61	95	[	[	X
cana-2726	61	96	10	10	NUM
cana-2726	61	97	]	]	PUNCT
cana-2726	61	98	.	.	PUNCT
cana-2726	62	1	where	where	SCONJ
cana-2726	62	2	“	"	PUNCT
cana-2726	62	3	i	i	PRON
cana-2726	62	4	”	"	PUNCT
cana-2726	62	5	indicates	indicate	VERB
cana-2726	62	6	the	the	DET
cana-2726	62	7	number	number	NOUN
cana-2726	62	8	of	of	ADP
cana-2726	62	9	bands	band	NOUN
cana-2726	62	10	in	in	ADP
cana-2726	62	11	data	datum	NOUN
cana-2726	62	12	/imagery	/imagery	PUNCT
cana-2726	62	13	.	.	PUNCT
cana-2726	63	1	2.2	2.2	NUM
cana-2726	63	2	)	)	PUNCT
cana-2726	63	3	support	support	NOUN
cana-2726	63	4	vector	vector	NOUN
cana-2726	63	5	machine	machine	NOUN
cana-2726	63	6	(	(	PUNCT
cana-2726	63	7	svm	svm	PROPN
cana-2726	63	8	):	):	PUNCT
cana-2726	63	9	the	the	DET
cana-2726	63	10	support	support	NOUN
cana-2726	63	11	vector	vector	NOUN
cana-2726	63	12	machine	machine	NOUN
cana-2726	63	13	(	(	PUNCT
cana-2726	63	14	svm	svm	PROPN
cana-2726	63	15	)	)	PUNCT
cana-2726	63	16	is	be	AUX
cana-2726	63	17	fully	fully	ADV
cana-2726	63	18	based	base	VERB
cana-2726	63	19	on	on	ADP
cana-2726	63	20	theory	theory	NOUN
cana-2726	63	21	of	of	ADP
cana-2726	63	22	“	"	PUNCT
cana-2726	63	23	statistical	statistical	ADJ
cana-2726	63	24	learning	learning	NOUN
cana-2726	63	25	”	"	PUNCT
cana-2726	63	26	that	that	PRON
cana-2726	63	27	used	use	VERB
cana-2726	63	28	supervised	supervise	VERB
cana-2726	63	29	based	base	VERB
cana-2726	63	30	machine	machine	NOUN
cana-2726	63	31	learning	learning	NOUN
cana-2726	63	32	algorithm	algorithm	NOUN
cana-2726	63	33	.	.	PUNCT
cana-2726	64	1	nowadays	nowadays	ADV
cana-2726	64	2	,	,	PUNCT
cana-2726	64	3	the	the	DET
cana-2726	64	4	advanced	advanced	ADJ
cana-2726	64	5	support	support	NOUN
cana-2726	64	6	vector	vector	NOUN
cana-2726	64	7	machine	machine	NOUN
cana-2726	64	8	(	(	PUNCT
cana-2726	64	9	svm	svm	PROPN
cana-2726	64	10	)	)	PUNCT
cana-2726	64	11	is	be	AUX
cana-2726	64	12	very	very	ADV
cana-2726	64	13	popular	popular	ADJ
cana-2726	64	14	algorithm	algorithm	NOUN
cana-2726	64	15	of	of	ADP
cana-2726	64	16	machine	machine	NOUN
cana-2726	64	17	-	-	PUNCT
cana-2726	64	18	based	base	VERB
cana-2726	64	19	learning	learning	NOUN
cana-2726	64	20	and	and	CCONJ
cana-2726	64	21	most	most	ADV
cana-2726	64	22	commonly	commonly	ADV
cana-2726	64	23	used	use	VERB
cana-2726	64	24	in	in	ADP
cana-2726	64	25	advanced	advanced	ADJ
cana-2726	64	26	remote	remote	ADJ
cana-2726	64	27	sensing	sensing	NOUN
cana-2726	64	28	based	base	VERB
cana-2726	64	29	multi	multi	ADJ
cana-2726	64	30	temporal	temporal	ADJ
cana-2726	64	31	satellite	satellite	NOUN
cana-2726	64	32	image	image	NOUN
cana-2726	64	33	classification	classification	NOUN
cana-2726	64	34	with	with	ADP
cana-2726	64	35	a	a	DET
cana-2726	64	36	higher	high	ADJ
cana-2726	64	37	accuracy	accuracy	NOUN
cana-2726	64	38	.	.	PUNCT
cana-2726	65	1	in	in	ADP
cana-2726	65	2	the	the	DET
cana-2726	65	3	supervised	supervised	ADJ
cana-2726	65	4	learning	learning	NOUN
cana-2726	65	5	algorithms	algorithm	NOUN
cana-2726	65	6	,	,	PUNCT
cana-2726	65	7	a	a	DET
cana-2726	65	8	machine	machine	NOUN
cana-2726	65	9	is	be	AUX
cana-2726	65	10	simply	simply	ADV
cana-2726	65	11	trained	train	VERB
cana-2726	65	12	rather	rather	ADV
cana-2726	65	13	of	of	ADP
cana-2726	65	14	programmed	programmed	ADJ
cana-2726	65	15	using	use	VERB
cana-2726	65	16	a	a	DET
cana-2726	65	17	number	number	NOUN
cana-2726	65	18	of	of	ADP
cana-2726	65	19	training	training	NOUN
cana-2726	65	20	set	set	VERB
cana-2726	65	21	as	as	ADP
cana-2726	65	22	an	an	DET
cana-2726	65	23	example	example	NOUN
cana-2726	65	24	of	of	ADP
cana-2726	65	25	both	both	PRON
cana-2726	65	26	input	input	NOUN
cana-2726	65	27	and	and	CCONJ
cana-2726	65	28	output	output	NOUN
cana-2726	65	29	pairs	pair	NOUN
cana-2726	65	30	.	.	PUNCT
cana-2726	66	1	the	the	DET
cana-2726	66	2	primary	primary	ADJ
cana-2726	66	3	aim	aim	NOUN
cana-2726	66	4	of	of	ADP
cana-2726	66	5	training	training	NOUN
cana-2726	66	6	is	be	AUX
cana-2726	66	7	to	to	PART
cana-2726	66	8	simply	simply	ADV
cana-2726	66	9	determine	determine	VERB
cana-2726	66	10	a	a	DET
cana-2726	66	11	function	function	NOUN
cana-2726	66	12	which	which	PRON
cana-2726	66	13	best	good	ADJ
cana-2726	66	14	result	result	VERB
cana-2726	66	15	that	that	SCONJ
cana-2726	66	16	simply	simply	ADV
cana-2726	66	17	describes	describe	VERB
cana-2726	66	18	the	the	DET
cana-2726	66	19	good	good	ADJ
cana-2726	66	20	relation	relation	NOUN
cana-2726	66	21	between	between	ADP
cana-2726	66	22	the	the	DET
cana-2726	66	23	inputs	input	NOUN
cana-2726	66	24	as	as	ADV
cana-2726	66	25	well	well	ADV
cana-2726	66	26	as	as	ADP
cana-2726	66	27	outputs	output	NOUN
cana-2726	66	28	.	.	PUNCT
cana-2726	67	1	in	in	ADP
cana-2726	67	2	generally	generally	ADV
cana-2726	67	3	,	,	PUNCT
cana-2726	67	4	any	any	DET
cana-2726	67	5	type	type	NOUN
cana-2726	67	6	of	of	ADP
cana-2726	67	7	learning	learn	VERB
cana-2726	67	8	problem	problem	NOUN
cana-2726	67	9	in	in	ADP
cana-2726	67	10	most	most	ADJ
cana-2726	67	11	of	of	ADP
cana-2726	67	12	statistical	statistical	ADJ
cana-2726	67	13	learning	learning	NOUN
cana-2726	67	14	theory	theory	NOUN
cana-2726	67	15	always	always	ADV
cana-2726	67	16	will	will	AUX
cana-2726	67	17	lead	lead	VERB
cana-2726	67	18	to	to	ADP
cana-2726	67	19	a	a	DET
cana-2726	67	20	proper	proper	ADJ
cana-2726	67	21	solution	solution	NOUN
cana-2726	67	22	of	of	ADP
cana-2726	67	23	the	the	DET
cana-2726	67	24	type	type	NOUN
cana-2726	67	25	:	:	PUNCT
cana-2726	67	26	in	in	ADP
cana-2726	67	27	the	the	DET
cana-2726	67	28	above	above	ADJ
cana-2726	67	29	equation	equation	NOUN
cana-2726	67	30	(	(	PUNCT
cana-2726	67	31	1	1	NUM
cana-2726	67	32	)	)	PUNCT
cana-2726	67	33	,	,	PUNCT
cana-2726	67	34	where	where	SCONJ
cana-2726	67	35	xi	xi	X
cana-2726	67	36	,	,	PUNCT
cana-2726	67	37	“	"	PUNCT
cana-2726	67	38	i	i	PRON
cana-2726	67	39	”	"	PUNCT
cana-2726	67	40	represents	represent	VERB
cana-2726	67	41	the	the	DET
cana-2726	67	42	i=1,2,3	i=1,2,3	NUM
cana-2726	67	43	……	……	NOUN
cana-2726	67	44	,	,	PUNCT
cana-2726	67	45	l	l	NOUN
cana-2726	67	46	are	be	AUX
cana-2726	67	47	the	the	DET
cana-2726	67	48	inputs	input	NOUN
cana-2726	67	49	,	,	PUNCT
cana-2726	67	50	“	"	PUNCT
cana-2726	67	51	k	k	X
cana-2726	67	52	”	"	PUNCT
cana-2726	67	53	is	be	AUX
cana-2726	67	54	a	a	DET
cana-2726	67	55	kernal	kernal	NOUN
cana-2726	67	56	that	that	PRON
cana-2726	67	57	represent	represent	VERB
cana-2726	67	58	a	a	DET
cana-2726	67	59	symmetric	symmetric	ADJ
cana-2726	67	60	definite	definite	ADJ
cana-2726	67	61	function	function	NOUN
cana-2726	67	62	and	and	CCONJ
cana-2726	67	63	“	"	PUNCT
cana-2726	67	64	ci	ci	NOUN
cana-2726	67	65	”	"	PUNCT
cana-2726	67	66	is	be	AUX
cana-2726	67	67	represent	represent	VERB
cana-2726	67	68	set	set	NOUN
cana-2726	67	69	of	of	ADP
cana-2726	67	70	parameters	parameter	NOUN
cana-2726	67	71	to	to	PART
cana-2726	67	72	be	be	AUX
cana-2726	67	73	simply	simply	ADV
cana-2726	67	74	determined	determine	VERB
cana-2726	67	75	from	from	ADP
cana-2726	67	76	given	give	VERB
cana-2726	67	77	samples	sample	NOUN
cana-2726	67	78	.	.	PUNCT
cana-2726	68	1	advanced	advanced	ADJ
cana-2726	68	2	support	support	NOUN
cana-2726	68	3	vector	vector	NOUN
cana-2726	68	4	machine	machine	NOUN
cana-2726	68	5	(	(	PUNCT
cana-2726	68	6	svm	svm	PROPN
cana-2726	68	7	)	)	PUNCT
cana-2726	68	8	uses	use	VERB
cana-2726	68	9	both	both	DET
cana-2726	68	10	classification	classification	NOUN
cana-2726	68	11	and	and	CCONJ
cana-2726	68	12	regression	regression	NOUN
cana-2726	68	13	to	to	PART
cana-2726	68	14	map	map	VERB
cana-2726	68	15	points	point	NOUN
cana-2726	68	16	in	in	ADP
cana-2726	68	17	higher	high	ADJ
cana-2726	68	18	dimensional	dimensional	ADJ
cana-2726	68	19	space	space	NOUN
cana-2726	68	20	that	that	PRON
cana-2726	68	21	simply	simply	ADV
cana-2726	68	22	separate	separate	VERB
cana-2726	68	23	the	the	DET
cana-2726	68	24	two	two	NUM
cana-2726	68	25	different	different	ADJ
cana-2726	68	26	categories	category	NOUN
cana-2726	68	27	of	of	ADP
cana-2726	68	28	points	point	NOUN
cana-2726	68	29	.	.	PUNCT
cana-2726	69	1	figure:03	figure:03	X
cana-2726	69	2	hyperplane	hyperplane	NOUN
cana-2726	69	3	with	with	ADP
cana-2726	69	4	separated	separate	VERB
cana-2726	69	5	points	point	NOUN
cana-2726	69	6	.	.	PUNCT
cana-2726	70	1	communications	communication	NOUN
cana-2726	70	2	on	on	ADP
cana-2726	70	3	applied	apply	VERB
cana-2726	70	4	nonlinear	nonlinear	ADJ
cana-2726	70	5	analysis	analysis	NOUN
cana-2726	70	6	issn	issn	NOUN
cana-2726	70	7	:	:	PUNCT
cana-2726	70	8	1074	1074	NUM
cana-2726	70	9	-	-	PUNCT
cana-2726	70	10	133x	133x	NUM
cana-2726	70	11	vol	vol	NOUN
cana-2726	70	12	32	32	NUM
cana-2726	70	13	no	no	NOUN
cana-2726	70	14	.	.	PUNCT
cana-2726	71	1	3s	3s	NUM
cana-2726	71	2	(	(	PUNCT
cana-2726	71	3	2025	2025	NUM
cana-2726	71	4	)	)	PUNCT
cana-2726	71	5	685	685	NUM
cana-2726	71	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	71	7	in	in	ADP
cana-2726	71	8	the	the	DET
cana-2726	71	9	figure:03	figure:03	PUNCT
cana-2726	71	10	shows	show	VERB
cana-2726	71	11	an	an	DET
cana-2726	71	12	example	example	NOUN
cana-2726	71	13	of	of	ADP
cana-2726	71	14	two	two	NUM
cana-2726	71	15	different	different	ADJ
cana-2726	71	16	categories	category	NOUN
cana-2726	71	17	of	of	ADP
cana-2726	71	18	points	point	NOUN
cana-2726	71	19	(	(	PUNCT
cana-2726	71	20	red	red	ADJ
cana-2726	71	21	and	and	CCONJ
cana-2726	71	22	green	green	ADJ
cana-2726	71	23	)	)	PUNCT
cana-2726	71	24	are	be	AUX
cana-2726	71	25	separated	separate	VERB
cana-2726	71	26	by	by	ADP
cana-2726	71	27	an	an	DET
cana-2726	71	28	optimal	optimal	ADJ
cana-2726	71	29	hyperplane	hyperplane	NOUN
cana-2726	71	30	.	.	PUNCT
cana-2726	72	1	the	the	DET
cana-2726	72	2	two	two	NUM
cana-2726	72	3	categories	category	NOUN
cana-2726	72	4	of	of	ADP
cana-2726	72	5	points	point	NOUN
cana-2726	72	6	(	(	PUNCT
cana-2726	72	7	red	red	ADJ
cana-2726	72	8	and	and	CCONJ
cana-2726	72	9	green	green	ADJ
cana-2726	72	10	)	)	PUNCT
cana-2726	72	11	are	be	AUX
cana-2726	72	12	located	locate	VERB
cana-2726	72	13	closed	close	VERB
cana-2726	72	14	to	to	ADP
cana-2726	72	15	the	the	DET
cana-2726	72	16	hyperplane	hyperplane	NOUN
cana-2726	72	17	which	which	PRON
cana-2726	72	18	are	be	AUX
cana-2726	72	19	called	call	VERB
cana-2726	72	20	as	as	ADP
cana-2726	72	21	“	"	PUNCT
cana-2726	72	22	support	support	NOUN
cana-2726	72	23	vectors	vector	NOUN
cana-2726	72	24	”	"	PUNCT
cana-2726	72	25	(	(	PUNCT
cana-2726	72	26	sv	sv	NOUN
cana-2726	72	27	)	)	PUNCT
cana-2726	72	28	machine	machine	NOUN
cana-2726	72	29	.	.	PUNCT
cana-2726	73	1	each	each	DET
cana-2726	73	2	side	side	NOUN
cana-2726	73	3	of	of	ADP
cana-2726	73	4	plane	plane	NOUN
cana-2726	73	5	can	can	AUX
cana-2726	73	6	be	be	AUX
cana-2726	73	7	more	more	ADJ
cana-2726	73	8	than	than	ADP
cana-2726	73	9	one	one	NUM
cana-2726	73	10	support	support	NOUN
cana-2726	73	11	vector	vector	NOUN
cana-2726	73	12	(	(	PUNCT
cana-2726	73	13	sv	sv	NOUN
cana-2726	73	14	)	)	PUNCT
cana-2726	73	15	.	.	PUNCT
cana-2726	74	1	in	in	ADP
cana-2726	74	2	the	the	DET
cana-2726	74	3	remote	remote	ADJ
cana-2726	74	4	sensing	sensing	NOUN
cana-2726	74	5	,	,	PUNCT
cana-2726	74	6	the	the	DET
cana-2726	74	7	svm	svm	NOUN
cana-2726	74	8	has	have	AUX
cana-2726	74	9	best	well	ADV
cana-2726	74	10	proven	prove	VERB
cana-2726	74	11	to	to	PART
cana-2726	74	12	be	be	AUX
cana-2726	74	13	advanced	advance	VERB
cana-2726	74	14	in	in	ADP
cana-2726	74	15	both	both	CCONJ
cana-2726	74	16	heterogeneous	heterogeneous	ADJ
cana-2726	74	17	and	and	CCONJ
cana-2726	74	18	homogeneous	homogeneous	ADJ
cana-2726	74	19	land	land	NOUN
cana-2726	74	20	use	use	NOUN
cana-2726	74	21	and	and	CCONJ
cana-2726	74	22	land	land	NOUN
cana-2726	74	23	cover	cover	NOUN
cana-2726	74	24	features	feature	NOUN
cana-2726	74	25	[	[	X
cana-2726	74	26	12	12	NUM
cana-2726	74	27	]	]	PUNCT
cana-2726	74	28	.	.	PUNCT
cana-2726	75	1	2.3	2.3	NUM
cana-2726	75	2	)	)	PUNCT
cana-2726	75	3	multi	multi	ADJ
cana-2726	75	4	scale	scale	NOUN
cana-2726	75	5	and	and	CCONJ
cana-2726	75	6	multi	multi	ADJ
cana-2726	75	7	depth	depth	NOUN
cana-2726	75	8	(	(	PUNCT
cana-2726	75	9	msmd	msmd	NOUN
cana-2726	75	10	)	)	PUNCT
cana-2726	75	11	cnn	cnn	NOUN
cana-2726	75	12	:	:	PUNCT
cana-2726	75	13	recently	recently	ADV
cana-2726	75	14	,	,	PUNCT
cana-2726	75	15	convolutional	convolutional	ADJ
cana-2726	75	16	neural	neural	ADJ
cana-2726	75	17	networks	network	NOUN
cana-2726	75	18	(	(	PUNCT
cana-2726	75	19	cnns	cnns	PROPN
cana-2726	75	20	)	)	PUNCT
cana-2726	75	21	are	be	AUX
cana-2726	75	22	most	most	ADV
cana-2726	75	23	widely	widely	ADV
cana-2726	75	24	used	use	VERB
cana-2726	75	25	in	in	ADP
cana-2726	75	26	new	new	ADJ
cana-2726	75	27	approach	approach	NOUN
cana-2726	75	28	of	of	ADP
cana-2726	75	29	remote	remote	ADJ
cana-2726	75	30	sensing	sensing	NOUN
cana-2726	75	31	-	-	PUNCT
cana-2726	75	32	based	base	VERB
cana-2726	75	33	satellite	satellite	NOUN
cana-2726	75	34	imagery	imagery	NOUN
cana-2726	75	35	applications	application	NOUN
cana-2726	75	36	.	.	PUNCT
cana-2726	76	1	sometimes	sometimes	ADV
cana-2726	76	2	,	,	PUNCT
cana-2726	76	3	the	the	DET
cana-2726	76	4	remote	remote	ADJ
cana-2726	76	5	sensing	sense	VERB
cana-2726	76	6	satellite	satellite	NOUN
cana-2726	76	7	images	image	NOUN
cana-2726	76	8	are	be	AUX
cana-2726	76	9	more	more	ADV
cana-2726	76	10	complex	complex	ADJ
cana-2726	76	11	,	,	PUNCT
cana-2726	76	12	the	the	DET
cana-2726	76	13	huge	huge	ADJ
cana-2726	76	14	different	different	ADJ
cana-2726	76	15	variation	variation	NOUN
cana-2726	76	16	of	of	ADP
cana-2726	76	17	scales	scale	NOUN
cana-2726	76	18	and	and	CCONJ
cana-2726	76	19	complex	complex	ADJ
cana-2726	76	20	surrounding	surrounding	NOUN
cana-2726	76	21	will	will	AUX
cana-2726	76	22	effectively	effectively	ADV
cana-2726	76	23	affect	affect	VERB
cana-2726	76	24	the	the	DET
cana-2726	76	25	performance	performance	NOUN
cana-2726	76	26	of	of	ADP
cana-2726	76	27	the	the	DET
cana-2726	76	28	detection	detection	NOUN
cana-2726	76	29	.	.	PUNCT
cana-2726	77	1	as	as	ADV
cana-2726	77	2	previously	previously	ADV
cana-2726	77	3	,	,	PUNCT
cana-2726	77	4	some	some	DET
cana-2726	77	5	deep	deep	ADJ
cana-2726	77	6	learning	learn	VERB
cana-2726	77	7	classification	classification	NOUN
cana-2726	77	8	algorithms	algorithm	NOUN
cana-2726	77	9	are	be	AUX
cana-2726	77	10	completely	completely	ADV
cana-2726	77	11	depended	depend	VERB
cana-2726	77	12	on	on	ADP
cana-2726	77	13	spatial	spatial	ADJ
cana-2726	77	14	based	base	VERB
cana-2726	77	15	spectral	spectral	ADJ
cana-2726	77	16	information	information	NOUN
cana-2726	77	17	and	and	CCONJ
cana-2726	77	18	feature	feature	NOUN
cana-2726	77	19	extraction	extraction	NOUN
cana-2726	77	20	.	.	PUNCT
cana-2726	78	1	the	the	DET
cana-2726	78	2	single	single	ADJ
cana-2726	78	3	scale	scale	NOUN
cana-2726	78	4	cnns	cnn	NOUN
cana-2726	78	5	ignore	ignore	VERB
cana-2726	78	6	both	both	CCONJ
cana-2726	78	7	spatial	spatial	ADJ
cana-2726	78	8	based	base	VERB
cana-2726	78	9	spectral	spectral	ADJ
cana-2726	78	10	information	information	NOUN
cana-2726	78	11	and	and	CCONJ
cana-2726	78	12	some	some	DET
cana-2726	78	13	detailed	detailed	ADJ
cana-2726	78	14	features	feature	NOUN
cana-2726	78	15	during	during	ADP
cana-2726	78	16	features	feature	NOUN
cana-2726	78	17	extraction	extraction	NOUN
cana-2726	78	18	and	and	CCONJ
cana-2726	78	19	resulting	result	VERB
cana-2726	78	20	the	the	DET
cana-2726	78	21	overall	overall	ADJ
cana-2726	78	22	performance	performance	NOUN
cana-2726	78	23	of	of	ADP
cana-2726	78	24	the	the	DET
cana-2726	78	25	detection	detection	NOUN
cana-2726	78	26	methods	method	NOUN
cana-2726	78	27	are	be	AUX
cana-2726	78	28	poor	poor	ADJ
cana-2726	78	29	.	.	PUNCT
cana-2726	79	1	to	to	PART
cana-2726	79	2	overcome	overcome	VERB
cana-2726	79	3	,	,	PUNCT
cana-2726	79	4	this	this	DET
cana-2726	79	5	problem	problem	NOUN
cana-2726	79	6	,	,	PUNCT
cana-2726	79	7	the	the	DET
cana-2726	79	8	proposed	propose	VERB
cana-2726	79	9	method	method	NOUN
cana-2726	79	10	is	be	AUX
cana-2726	79	11	based	base	VERB
cana-2726	79	12	on	on	ADP
cana-2726	79	13	multi	multi	ADJ
cana-2726	79	14	scale	scale	NOUN
cana-2726	79	15	and	and	CCONJ
cana-2726	79	16	multi	multi	ADJ
cana-2726	79	17	depth	depth	NOUN
cana-2726	79	18	convolutional	convolutional	ADJ
cana-2726	79	19	neural	neural	ADJ
cana-2726	79	20	networks	network	NOUN
cana-2726	79	21	(	(	PUNCT
cana-2726	79	22	msmd_cnn	msmd_cnn	NUM
cana-2726	79	23	)	)	PUNCT
cana-2726	79	24	.	.	PUNCT
cana-2726	80	1	the	the	DET
cana-2726	80	2	multi	multi	ADJ
cana-2726	80	3	scale	scale	NOUN
cana-2726	80	4	and	and	CCONJ
cana-2726	80	5	multi	multi	ADJ
cana-2726	80	6	depth	depth	NOUN
cana-2726	80	7	cnns	cnn	NOUN
cana-2726	80	8	is	be	AUX
cana-2726	80	9	an	an	DET
cana-2726	80	10	effectively	effectively	ADV
cana-2726	80	11	work	work	NOUN
cana-2726	80	12	with	with	ADP
cana-2726	80	13	a	a	DET
cana-2726	80	14	largescale	largescale	NOUN
cana-2726	80	15	variation	variation	NOUN
cana-2726	80	16	.	.	PUNCT
cana-2726	81	1	firstly	firstly	ADV
cana-2726	81	2	,	,	PUNCT
cana-2726	81	3	the	the	DET
cana-2726	81	4	dataset	dataset	NOUN
cana-2726	81	5	is	be	AUX
cana-2726	81	6	divided	divide	VERB
cana-2726	81	7	into	into	ADP
cana-2726	81	8	two	two	NUM
cana-2726	81	9	type	type	NOUN
cana-2726	81	10	of	of	ADP
cana-2726	81	11	pixel	pixel	NOUN
cana-2726	81	12	module	module	NOUN
cana-2726	81	13	,	,	PUNCT
cana-2726	81	14	and	and	CCONJ
cana-2726	81	15	then	then	ADV
cana-2726	81	16	two	two	NUM
cana-2726	81	17	or	or	CCONJ
cana-2726	81	18	more	more	ADV
cana-2726	81	19	different	different	ADJ
cana-2726	81	20	channel	channel	NOUN
cana-2726	81	21	are	be	AUX
cana-2726	81	22	used	use	VERB
cana-2726	81	23	for	for	ADP
cana-2726	81	24	various	various	ADJ
cana-2726	81	25	feature	feature	NOUN
cana-2726	81	26	extraction	extraction	NOUN
cana-2726	81	27	.	.	PUNCT
cana-2726	82	1	in	in	ADP
cana-2726	82	2	multi	multi	ADJ
cana-2726	82	3	scale	scale	NOUN
cana-2726	82	4	and	and	CCONJ
cana-2726	82	5	multi	multi	ADJ
cana-2726	82	6	depth	depth	NOUN
cana-2726	82	7	cnns	cnn	NOUN
cana-2726	82	8	,	,	PUNCT
cana-2726	82	9	utilize	utilize	VERB
cana-2726	82	10	different	different	ADJ
cana-2726	82	11	sizes	size	NOUN
cana-2726	82	12	of	of	ADP
cana-2726	82	13	convolution	convolution	NOUN
cana-2726	82	14	kernels	kernel	NOUN
cana-2726	82	15	to	to	PART
cana-2726	82	16	better	well	ADV
cana-2726	82	17	extract	extract	VERB
cana-2726	82	18	the	the	DET
cana-2726	82	19	spatial	spatial	ADJ
cana-2726	82	20	spectral	spectral	ADJ
cana-2726	82	21	detailed	detailed	ADJ
cana-2726	82	22	information	information	NOUN
cana-2726	82	23	and	and	CCONJ
cana-2726	82	24	then	then	ADV
cana-2726	82	25	combined	combine	VERB
cana-2726	82	26	together	together	ADV
cana-2726	82	27	for	for	ADP
cana-2726	82	28	final	final	ADJ
cana-2726	82	29	classification	classification	NOUN
cana-2726	83	1	[	[	X
cana-2726	83	2	13][14	13][14	PROPN
cana-2726	83	3	]	]	PUNCT
cana-2726	83	4	.	.	PUNCT
cana-2726	84	1	figure:04	figure:04	PROPN
cana-2726	84	2	the	the	DET
cana-2726	84	3	proposed	propose	VERB
cana-2726	84	4	msmd	msmd	PROPN
cana-2726	84	5	cnn	cnn	PROPN
cana-2726	84	6	architecture	architecture	NOUN
cana-2726	84	7	figure	figure	NOUN
cana-2726	84	8	:	:	PUNCT
cana-2726	84	9	04	04	NUM
cana-2726	84	10	,	,	PUNCT
cana-2726	84	11	shows	show	VERB
cana-2726	84	12	the	the	DET
cana-2726	84	13	msmd_cnns	msmd_cnn	NOUN
cana-2726	84	14	include	include	VERB
cana-2726	84	15	multiple	multiple	ADJ
cana-2726	84	16	layers	layer	NOUN
cana-2726	84	17	along	along	ADP
cana-2726	84	18	with	with	ADP
cana-2726	84	19	convolutional	convolutional	ADJ
cana-2726	84	20	,	,	PUNCT
cana-2726	84	21	relu	relu	NOUN
cana-2726	84	22	,	,	PUNCT
cana-2726	84	23	max_pool	max_pool	NOUN
cana-2726	84	24	,	,	PUNCT
cana-2726	84	25	fusion	fusion	NOUN
cana-2726	84	26	and	and	CCONJ
cana-2726	84	27	fully	fully	ADV
cana-2726	84	28	connected	connected	ADJ
cana-2726	84	29	layers	layer	NOUN
cana-2726	84	30	.	.	PUNCT
cana-2726	85	1	the	the	DET
cana-2726	85	2	proposed	propose	VERB
cana-2726	85	3	system	system	NOUN
cana-2726	85	4	involves	involve	VERB
cana-2726	85	5	the	the	DET
cana-2726	85	6	2d	2d	NUM
cana-2726	85	7	cnn	cnn	PROPN
cana-2726	85	8	are	be	AUX
cana-2726	85	9	used	use	VERB
cana-2726	85	10	to	to	PART
cana-2726	85	11	extract	extract	VERB
cana-2726	85	12	spatial	spatial	ADJ
cana-2726	85	13	spectral	spectral	ADJ
cana-2726	85	14	information	information	NOUN
cana-2726	85	15	,	,	PUNCT
cana-2726	85	16	respectively	respectively	ADV
cana-2726	85	17	with	with	ADP
cana-2726	85	18	various	various	ADJ
cana-2726	85	19	inputs	input	NOUN
cana-2726	85	20	to	to	PART
cana-2726	85	21	simply	simply	ADV
cana-2726	85	22	classify	classify	VERB
cana-2726	85	23	the	the	DET
cana-2726	85	24	bitemporal	bitemporal	NOUN
cana-2726	85	25	based	base	VERB
cana-2726	85	26	landsat-8	landsat-8	PROPN
cana-2726	85	27	satellite	satellite	NOUN
cana-2726	85	28	images	image	NOUN
cana-2726	85	29	along	along	ADP
cana-2726	85	30	with	with	ADP
cana-2726	85	31	region	region	NOUN
cana-2726	85	32	of	of	ADP
cana-2726	85	33	weighted	weight	VERB
cana-2726	85	34	based	base	VERB
cana-2726	85	35	majority	majority	NOUN
cana-2726	85	36	voting	vote	VERB
cana-2726	85	37	cnn	cnn	PROPN
cana-2726	85	38	algorithm	algorithm	NOUN
cana-2726	85	39	is	be	AUX
cana-2726	85	40	integrated	integrate	VERB
cana-2726	85	41	with	with	ADP
cana-2726	85	42	final	final	ADJ
cana-2726	85	43	results	result	NOUN
cana-2726	85	44	.	.	PUNCT
cana-2726	86	1	the	the	DET
cana-2726	86	2	patch	patch	ADJ
cana-2726	86	3	sizes	size	NOUN
cana-2726	86	4	[	[	X
cana-2726	86	5	3×3	3×3	NUM
cana-2726	86	6	,	,	PUNCT
cana-2726	86	7	7×7	7×7	NOUN
cana-2726	86	8	,	,	PUNCT
cana-2726	86	9	and	and	CCONJ
cana-2726	86	10	10×10	10×10	NUM
cana-2726	86	11	]	]	PUNCT
cana-2726	86	12	are	be	AUX
cana-2726	86	13	used	use	VERB
cana-2726	86	14	as	as	ADP
cana-2726	86	15	inputs	input	NOUN
cana-2726	86	16	,	,	PUNCT
cana-2726	86	17	the	the	DET
cana-2726	86	18	kernel	kernel	NOUN
cana-2726	86	19	size	size	NOUN
cana-2726	86	20	is	be	AUX
cana-2726	86	21	3×3	3×3	NUM
cana-2726	86	22	for	for	ADP
cana-2726	86	23	sequence	sequence	NOUN
cana-2726	86	24	of	of	ADP
cana-2726	86	25	the	the	DET
cana-2726	86	26	filters	filter	NOUN
cana-2726	86	27	is	be	AUX
cana-2726	86	28	presented	present	VERB
cana-2726	86	29	in	in	ADP
cana-2726	86	30	[	[	X
cana-2726	86	31	64,128,256	64,128,256	NUM
cana-2726	86	32	]	]	PUNCT
cana-2726	86	33	order	order	NOUN
cana-2726	86	34	.	.	PUNCT
cana-2726	87	1	3	3	X
cana-2726	87	2	)	)	PUNCT
cana-2726	87	3	experimental	experimental	ADJ
cana-2726	87	4	result	result	NOUN
cana-2726	87	5	:	:	PUNCT
cana-2726	87	6	3.1	3.1	NUM
cana-2726	87	7	)	)	PUNCT
cana-2726	87	8	research	research	NOUN
cana-2726	87	9	study	study	NOUN
cana-2726	87	10	area	area	NOUN
cana-2726	87	11	and	and	CCONJ
cana-2726	87	12	datasets	dataset	NOUN
cana-2726	87	13	:	:	PUNCT
cana-2726	87	14	in	in	ADP
cana-2726	87	15	research	research	NOUN
cana-2726	87	16	study	study	NOUN
cana-2726	87	17	,	,	PUNCT
cana-2726	87	18	the	the	DET
cana-2726	87	19	landsat-8	landsat-8	NUM
cana-2726	87	20	remote	remote	ADJ
cana-2726	87	21	sensing	sense	VERB
cana-2726	87	22	satellite	satellite	NOUN
cana-2726	87	23	-	-	PUNCT
cana-2726	87	24	based	base	VERB
cana-2726	87	25	images	image	NOUN
cana-2726	87	26	are	be	AUX
cana-2726	87	27	used	use	VERB
cana-2726	87	28	for	for	ADP
cana-2726	87	29	effectively	effectively	ADV
cana-2726	87	30	evaluated	evaluate	VERB
cana-2726	87	31	of	of	ADP
cana-2726	87	32	the	the	DET
cana-2726	87	33	proposed	propose	VERB
cana-2726	87	34	method	method	NOUN
cana-2726	87	35	in	in	ADP
cana-2726	87	36	various	various	ADJ
cana-2726	87	37	changes	change	NOUN
cana-2726	87	38	in	in	ADP
cana-2726	87	39	region	region	NOUN
cana-2726	87	40	of	of	ADP
cana-2726	87	41	australian	australian	ADJ
cana-2726	87	42	capital	capital	NOUN
cana-2726	87	43	territory	territory	NOUN
cana-2726	87	44	(	(	PUNCT
cana-2726	87	45	act	act	PROPN
cana-2726	87	46	)	)	PUNCT
cana-2726	87	47	area	area	NOUN
cana-2726	87	48	.	.	PUNCT
cana-2726	88	1	australian	australian	ADJ
cana-2726	88	2	capital	capital	NOUN
cana-2726	88	3	territory	territory	NOUN
cana-2726	88	4	is	be	AUX
cana-2726	88	5	mainly	mainly	ADV
cana-2726	88	6	situated	situate	VERB
cana-2726	88	7	in	in	ADP
cana-2726	88	8	the	the	DET
cana-2726	88	9	province	province	NOUN
cana-2726	88	10	of	of	ADP
cana-2726	88	11	australia	australia	PROPN
cana-2726	88	12	,	,	PUNCT
cana-2726	88	13	with	with	SCONJ
cana-2726	88	14	a	a	DET
cana-2726	88	15	longitude	longitude	NOUN
cana-2726	88	16	of	of	ADP
cana-2726	88	17	communications	communication	NOUN
cana-2726	88	18	on	on	ADP
cana-2726	88	19	applied	apply	VERB
cana-2726	88	20	nonlinear	nonlinear	ADJ
cana-2726	88	21	analysis	analysis	NOUN
cana-2726	88	22	issn	issn	NOUN
cana-2726	88	23	:	:	PUNCT
cana-2726	88	24	1074	1074	NUM
cana-2726	88	25	-	-	PUNCT
cana-2726	88	26	133x	133x	NUM
cana-2726	88	27	vol	vol	NOUN
cana-2726	88	28	32	32	NUM
cana-2726	89	1	no	no	NOUN
cana-2726	89	2	.	.	PUNCT
cana-2726	90	1	3s	3s	NUM
cana-2726	90	2	(	(	PUNCT
cana-2726	90	3	2025	2025	NUM
cana-2726	90	4	)	)	PUNCT
cana-2726	90	5	686	686	NUM
cana-2726	90	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	90	7	149.1210	149.1210	NUM
cana-2726	90	8	and	and	CCONJ
cana-2726	90	9	a	a	DET
cana-2726	90	10	latitude	latitude	NOUN
cana-2726	90	11	of	of	ADP
cana-2726	90	12	-35.1836	-35.1836	PUNCT
cana-2726	90	13	.	.	PUNCT
cana-2726	91	1	the	the	DET
cana-2726	91	2	complete	complete	ADJ
cana-2726	91	3	area	area	NOUN
cana-2726	91	4	of	of	ADP
cana-2726	91	5	the	the	DET
cana-2726	91	6	australian	australian	ADJ
cana-2726	91	7	capital	capital	NOUN
cana-2726	91	8	territory	territory	NOUN
cana-2726	91	9	is	be	AUX
cana-2726	91	10	over	over	ADP
cana-2726	91	11	2,400	2,400	NUM
cana-2726	91	12	km2	km2	NOUN
cana-2726	91	13	.	.	PUNCT
cana-2726	92	1	the	the	DET
cana-2726	92	2	australian	australian	ADJ
cana-2726	92	3	capital	capital	NOUN
cana-2726	92	4	territory	territory	NOUN
cana-2726	92	5	is	be	AUX
cana-2726	92	6	surrounded	surround	VERB
cana-2726	92	7	by	by	ADP
cana-2726	92	8	ngunnawal	ngunnawal	NOUN
cana-2726	92	9	,	,	PUNCT
cana-2726	92	10	palmerston	palmerston	PROPN
cana-2726	92	11	and	and	CCONJ
cana-2726	92	12	new	new	ADJ
cana-2726	92	13	south	south	PROPN
cana-2726	92	14	wales	wales	PROPN
cana-2726	92	15	.	.	PUNCT
cana-2726	93	1	the	the	DET
cana-2726	93	2	australian	australian	ADJ
cana-2726	93	3	capital	capital	NOUN
cana-2726	93	4	territory	territory	NOUN
cana-2726	93	5	extend	extend	VERB
cana-2726	93	6	89	89	NUM
cana-2726	93	7	km	km	NOUN
cana-2726	93	8	from	from	ADP
cana-2726	93	9	north	north	NOUN
cana-2726	93	10	to	to	ADP
cana-2726	93	11	south	south	NOUN
cana-2726	93	12	zone	zone	NOUN
cana-2726	93	13	along	along	ADP
cana-2726	93	14	with	with	ADP
cana-2726	93	15	only	only	ADV
cana-2726	93	16	31	31	NUM
cana-2726	93	17	km	km	NOUN
cana-2726	93	18	from	from	ADP
cana-2726	93	19	west	west	NOUN
cana-2726	93	20	to	to	ADP
cana-2726	93	21	east	east	PROPN
cana-2726	93	22	zone	zone	NOUN
cana-2726	93	23	.	.	PUNCT
cana-2726	94	1	the	the	DET
cana-2726	94	2	landscape	landscape	NOUN
cana-2726	94	3	around	around	ADP
cana-2726	94	4	ngunnawal	ngunnawal	PROPN
cana-2726	94	5	,	,	PUNCT
cana-2726	94	6	palmerston	palmerston	PROPN
cana-2726	94	7	are	be	AUX
cana-2726	94	8	made	make	VERB
cana-2726	94	9	up	up	ADP
cana-2726	94	10	of	of	ADP
cana-2726	94	11	hill	hill	NOUN
cana-2726	94	12	areas	area	NOUN
cana-2726	94	13	,	,	PUNCT
cana-2726	94	14	huge	huge	ADJ
cana-2726	94	15	mountains	mountain	NOUN
cana-2726	94	16	and	and	CCONJ
cana-2726	94	17	rugged	rugged	ADJ
cana-2726	94	18	plains	plain	NOUN
cana-2726	94	19	,	,	PUNCT
cana-2726	94	20	as	as	ADV
cana-2726	94	21	well	well	ADV
cana-2726	94	22	as	as	ADP
cana-2726	94	23	lot	lot	NOUN
cana-2726	94	24	of	of	ADP
cana-2726	94	25	trees	tree	NOUN
cana-2726	94	26	.	.	PUNCT
cana-2726	95	1	figure:05	figure:05	ADV
cana-2726	95	2	the	the	DET
cana-2726	95	3	location	location	NOUN
cana-2726	95	4	of	of	ADP
cana-2726	95	5	the	the	DET
cana-2726	95	6	australian	australian	ADJ
cana-2726	95	7	capital	capital	NOUN
cana-2726	95	8	territory	territory	NOUN
cana-2726	95	9	(	(	PUNCT
cana-2726	95	10	act	act	PROPN
cana-2726	95	11	)	)	PUNCT
cana-2726	95	12	(	(	PUNCT
cana-2726	95	13	image	image	NOUN
cana-2726	95	14	is	be	AUX
cana-2726	95	15	acquired	acquire	VERB
cana-2726	95	16	from	from	ADP
cana-2726	95	17	google	google	PROPN
cana-2726	95	18	satellite	satellite	NOUN
cana-2726	95	19	earth	earth	NOUN
cana-2726	95	20	engine	engine	NOUN
cana-2726	95	21	)	)	PUNCT
cana-2726	95	22	.	.	PUNCT
cana-2726	96	1	3.2	3.2	NUM
cana-2726	96	2	)	)	PUNCT
cana-2726	96	3	result	result	VERB
cana-2726	96	4	analysis	analysis	NOUN
cana-2726	96	5	:	:	PUNCT
cana-2726	96	6	the	the	DET
cana-2726	96	7	landsat-8	landsat-8	PROPN
cana-2726	96	8	satellite	satellite	NOUN
cana-2726	96	9	images	image	NOUN
cana-2726	96	10	were	be	AUX
cana-2726	96	11	acquired	acquire	VERB
cana-2726	96	12	from	from	ADP
cana-2726	96	13	a	a	DET
cana-2726	96	14	powerful	powerful	ADJ
cana-2726	96	15	platform	platform	NOUN
cana-2726	96	16	of	of	ADP
cana-2726	96	17	the	the	DET
cana-2726	96	18	google	google	PROPN
cana-2726	96	19	earth	earth	NOUN
cana-2726	96	20	engine	engine	NOUN
cana-2726	96	21	on	on	ADP
cana-2726	96	22	year	year	NOUN
cana-2726	96	23	of	of	ADP
cana-2726	96	24	2014	2014	NUM
cana-2726	96	25	and	and	CCONJ
cana-2726	96	26	year	year	NOUN
cana-2726	96	27	of	of	ADP
cana-2726	96	28	2020	2020	NUM
cana-2726	96	29	.	.	PUNCT
cana-2726	97	1	the	the	DET
cana-2726	97	2	geographic	geographic	ADJ
cana-2726	97	3	region	region	NOUN
cana-2726	97	4	of	of	ADP
cana-2726	97	5	the	the	DET
cana-2726	97	6	australian	australian	ADJ
cana-2726	97	7	capital	capital	NOUN
cana-2726	97	8	territory	territory	NOUN
cana-2726	97	9	(	(	PUNCT
cana-2726	97	10	act	act	PROPN
cana-2726	97	11	)	)	PUNCT
cana-2726	97	12	studied	study	VERB
cana-2726	97	13	area	area	NOUN
cana-2726	97	14	is	be	AUX
cana-2726	97	15	detailed	detail	VERB
cana-2726	97	16	in	in	ADP
cana-2726	97	17	figure	figure	NOUN
cana-2726	97	18	06	06	NUM
cana-2726	97	19	.	.	PUNCT
cana-2726	98	1	figure	figure	NOUN
cana-2726	98	2	:	:	PUNCT
cana-2726	98	3	06	06	NUM
cana-2726	98	4	google	google	PROPN
cana-2726	98	5	earth	earth	NOUN
cana-2726	98	6	engine	engine	NOUN
cana-2726	98	7	year	year	NOUN
cana-2726	98	8	of	of	ADP
cana-2726	98	9	2024	2024	NUM
cana-2726	98	10	and	and	CCONJ
cana-2726	98	11	year	year	NOUN
cana-2726	98	12	of	of	ADP
cana-2726	98	13	2020	2020	NUM
cana-2726	98	14	3.2.1	3.2.1	NUM
cana-2726	98	15	)	)	PUNCT
cana-2726	98	16	calculate	calculate	VERB
cana-2726	98	17	impervious	impervious	ADJ
cana-2726	98	18	surfaces	surface	NOUN
cana-2726	98	19	(	(	PUNCT
cana-2726	98	20	iss	iss	NOUN
cana-2726	98	21	)	)	PUNCT
cana-2726	98	22	indices	indice	VERB
cana-2726	98	23	:	:	PUNCT
cana-2726	98	24	in	in	ADP
cana-2726	98	25	this	this	DET
cana-2726	98	26	research	research	NOUN
cana-2726	98	27	study	study	NOUN
cana-2726	98	28	,	,	PUNCT
cana-2726	98	29	the	the	DET
cana-2726	98	30	proposed	propose	VERB
cana-2726	98	31	method	method	NOUN
cana-2726	98	32	aims	aim	VERB
cana-2726	98	33	to	to	PART
cana-2726	98	34	mainly	mainly	ADV
cana-2726	98	35	analyse	analyse	VERB
cana-2726	98	36	the	the	DET
cana-2726	98	37	relevant	relevant	ADJ
cana-2726	98	38	as	as	ADV
cana-2726	98	39	well	well	ADV
cana-2726	98	40	as	as	ADP
cana-2726	98	41	performance	performance	NOUN
cana-2726	98	42	of	of	ADP
cana-2726	98	43	various	various	ADJ
cana-2726	98	44	impervious	impervious	ADJ
cana-2726	98	45	surface	surface	NOUN
cana-2726	98	46	(	(	PUNCT
cana-2726	98	47	is	be	AUX
cana-2726	98	48	)	)	PUNCT
cana-2726	98	49	four	four	NUM
cana-2726	98	50	indices	index	NOUN
cana-2726	98	51	methods	method	NOUN
cana-2726	98	52	such	such	ADJ
cana-2726	98	53	as	as	ADP
cana-2726	98	54	:	:	PUNCT
cana-2726	98	55	1	1	X
cana-2726	98	56	)	)	PUNCT
cana-2726	98	57	mndwi	mndwi	ADV
cana-2726	98	58	2	2	NUM
cana-2726	98	59	)	)	PUNCT
cana-2726	98	60	swir_diff	swir_diff	NOUN
cana-2726	98	61	3	3	NUM
cana-2726	98	62	)	)	PUNCT
cana-2726	98	63	alpha	alpha	NOUN
cana-2726	98	64	and	and	CCONJ
cana-2726	98	65	4	4	NUM
cana-2726	98	66	)	)	PUNCT
cana-2726	98	67	endisi	endisi	VERB
cana-2726	98	68	using	use	VERB
cana-2726	98	69	remote	remote	ADJ
cana-2726	98	70	sensing	sense	VERB
cana-2726	98	71	landsat-8	landsat-8	NUM
cana-2726	98	72	images	image	NOUN
cana-2726	98	73	in	in	ADP
cana-2726	98	74	different	different	ADJ
cana-2726	98	75	study	study	NOUN
cana-2726	98	76	regions	region	NOUN
cana-2726	98	77	.	.	PUNCT
cana-2726	99	1	1	1	X
cana-2726	99	2	)	)	PUNCT
cana-2726	99	3	modified_normalized	modified_normalize	VERB
cana-2726	99	4	difference	difference	NOUN
cana-2726	99	5	water	water	NOUN
cana-2726	99	6	index	index	NOUN
cana-2726	99	7	(	(	PUNCT
cana-2726	99	8	mndwi	mndwi	ADV
cana-2726	99	9	):	):	PUNCT
cana-2726	99	10	the	the	DET
cana-2726	99	11	modified_normalized	modified_normalize	VERB
cana-2726	99	12	difference	difference	NOUN
cana-2726	99	13	water	water	NOUN
cana-2726	99	14	index	index	NOUN
cana-2726	99	15	(	(	PUNCT
cana-2726	99	16	mndwi	mndwi	ADV
cana-2726	99	17	)	)	PUNCT
cana-2726	99	18	accurately	accurately	ADV
cana-2726	99	19	differentiates	differentiate	VERB
cana-2726	99	20	between	between	ADP
cana-2726	99	21	open	open	ADJ
cana-2726	99	22	water	water	NOUN
cana-2726	99	23	features	feature	NOUN
cana-2726	99	24	and	and	CCONJ
cana-2726	99	25	urban	urban	ADJ
cana-2726	99	26	area	area	NOUN
cana-2726	99	27	in	in	ADP
cana-2726	99	28	remote	remote	ADJ
cana-2726	99	29	sensing	sense	VERB
cana-2726	99	30	satellite	satellite	NOUN
cana-2726	99	31	images	image	NOUN
cana-2726	99	32	.	.	PUNCT
cana-2726	100	1	this	this	DET
cana-2726	100	2	mndwi	mndwi	ADJ
cana-2726	100	3	methods	method	NOUN
cana-2726	100	4	uses	use	VERB
cana-2726	100	5	the	the	DET
cana-2726	100	6	visible	visible	ADJ
cana-2726	100	7	green	green	NOUN
cana-2726	100	8	and	and	CCONJ
cana-2726	100	9	swir_1	swir_1	PROPN
cana-2726	100	10	spectral	spectral	ADJ
cana-2726	100	11	bands	band	NOUN
cana-2726	100	12	.	.	PUNCT
cana-2726	101	1	communications	communication	NOUN
cana-2726	101	2	on	on	ADP
cana-2726	101	3	applied	apply	VERB
cana-2726	101	4	nonlinear	nonlinear	ADJ
cana-2726	101	5	analysis	analysis	NOUN
cana-2726	101	6	issn	issn	NOUN
cana-2726	101	7	:	:	PUNCT
cana-2726	101	8	1074	1074	NUM
cana-2726	101	9	-	-	PUNCT
cana-2726	101	10	133x	133x	NUM
cana-2726	101	11	vol	vol	NOUN
cana-2726	101	12	32	32	NUM
cana-2726	101	13	no	no	NOUN
cana-2726	101	14	.	.	PUNCT
cana-2726	102	1	3s	3s	NUM
cana-2726	102	2	(	(	PUNCT
cana-2726	102	3	2025	2025	NUM
cana-2726	102	4	)	)	PUNCT
cana-2726	102	5	687	687	NUM
cana-2726	102	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	102	7	visible	visible	ADJ
cana-2726	102	8	green=	green=	NUM
cana-2726	102	9	green	green	ADJ
cana-2726	102	10	band	band	NOUN
cana-2726	102	11	of	of	ADP
cana-2726	102	12	pixel	pixel	PROPN
cana-2726	102	13	values	value	NOUN
cana-2726	102	14	swir_1=	swir_1=	PROPN
cana-2726	102	15	short	short	ADJ
cana-2726	102	16	-	-	PUNCT
cana-2726	102	17	wave	wave	NOUN
cana-2726	102	18	infrared	infrare	VERB
cana-2726	102	19	band_1	band_1	PROPN
cana-2726	102	20	of	of	ADP
cana-2726	102	21	pixel	pixel	PROPN
cana-2726	102	22	values	value	NOUN
cana-2726	102	23	2	2	NUM
cana-2726	102	24	)	)	PUNCT
cana-2726	102	25	short	short	ADJ
cana-2726	102	26	wave	wave	NOUN
cana-2726	102	27	infrared	infrare	VERB
cana-2726	102	28	bands	band	NOUN
cana-2726	103	1	_	_	DET
cana-2726	103	2	diff	diff	NOUN
cana-2726	103	3	(	(	PUNCT
cana-2726	103	4	swir_diff	swir_diff	PROPN
cana-2726	103	5	):	):	PUNCT
cana-2726	103	6	the	the	DET
cana-2726	103	7	short	short	ADJ
cana-2726	103	8	-	-	PUNCT
cana-2726	103	9	wave	wave	NOUN
cana-2726	103	10	infrared	infrare	VERB
cana-2726	103	11	bands	band	NOUN
cana-2726	104	1	_	_	PRON
cana-2726	104	2	diff	diff	NOUN
cana-2726	104	3	(	(	PUNCT
cana-2726	104	4	swir_diff	swir_diff	PROPN
cana-2726	104	5	)	)	PUNCT
cana-2726	104	6	are	be	AUX
cana-2726	104	7	effectively	effectively	ADV
cana-2726	104	8	distinguishing	distinguish	VERB
cana-2726	104	9	water	water	NOUN
cana-2726	104	10	cloud	cloud	NOUN
cana-2726	104	11	and	and	CCONJ
cana-2726	104	12	ice	ice	NOUN
cana-2726	104	13	could	could	AUX
cana-2726	104	14	as	as	ADV
cana-2726	104	15	well	well	ADV
cana-2726	104	16	as	as	ADP
cana-2726	104	17	snow	snow	NOUN
cana-2726	104	18	and	and	CCONJ
cana-2726	104	19	ice	ice	NOUN
cana-2726	104	20	which	which	PRON
cana-2726	104	21	most	most	ADV
cana-2726	104	22	appear	appear	VERB
cana-2726	104	23	white	white	ADJ
cana-2726	104	24	in	in	ADP
cana-2726	104	25	visible	visible	ADJ
cana-2726	104	26	light	light	NOUN
cana-2726	104	27	.	.	PUNCT
cana-2726	105	1	3	3	X
cana-2726	105	2	)	)	PUNCT
cana-2726	105	3	alpha	alpha	NOUN
cana-2726	105	4	:	:	PUNCT
cana-2726	105	5	4	4	NUM
cana-2726	105	6	)	)	PUNCT
cana-2726	105	7	enhanced	enhance	VERB
cana-2726	105	8	normalized	normalize	VERB
cana-2726	105	9	difference	difference	NOUN
cana-2726	105	10	impervious	impervious	ADJ
cana-2726	105	11	surfaces	surface	NOUN
cana-2726	105	12	index	index	NOUN
cana-2726	105	13	(	(	PUNCT
cana-2726	105	14	endisi	endisi	VERB
cana-2726	105	15	):	):	PUNCT
cana-2726	105	16	the	the	DET
cana-2726	105	17	enhanced	enhance	VERB
cana-2726	105	18	normalized	normalize	VERB
cana-2726	105	19	difference	difference	NOUN
cana-2726	105	20	impervious	impervious	ADJ
cana-2726	105	21	surfaces	surface	NOUN
cana-2726	105	22	index	index	NOUN
cana-2726	105	23	(	(	PUNCT
cana-2726	105	24	endisi	endisi	VERB
cana-2726	105	25	)	)	PUNCT
cana-2726	105	26	is	be	AUX
cana-2726	105	27	simply	simply	ADV
cana-2726	105	28	differentiated	differentiate	VERB
cana-2726	105	29	between	between	ADP
cana-2726	105	30	two	two	NUM
cana-2726	105	31	surfaces	surface	NOUN
cana-2726	105	32	such	such	ADJ
cana-2726	105	33	as	as	ADP
cana-2726	105	34	:	:	PUNCT
cana-2726	105	35	1	1	NUM
cana-2726	105	36	)	)	PUNCT
cana-2726	105	37	impervious	impervious	ADJ
cana-2726	105	38	surfaces	surface	NOUN
cana-2726	105	39	(	(	PUNCT
cana-2726	105	40	iss	iss	PROPN
cana-2726	105	41	)	)	PUNCT
cana-2726	105	42	and	and	CCONJ
cana-2726	105	43	natural	natural	ADJ
cana-2726	105	44	surfaces	surface	NOUN
cana-2726	105	45	(	(	PUNCT
cana-2726	105	46	nss	ns	NOUN
cana-2726	105	47	)	)	PUNCT
cana-2726	105	48	.	.	PUNCT
cana-2726	106	1	to	to	PART
cana-2726	106	2	find	find	VERB
cana-2726	106	3	a	a	DET
cana-2726	106	4	major	major	ADJ
cana-2726	106	5	differences	difference	NOUN
cana-2726	106	6	between	between	ADP
cana-2726	106	7	both	both	CCONJ
cana-2726	106	8	the	the	DET
cana-2726	106	9	impervious	impervious	ADJ
cana-2726	106	10	based	base	VERB
cana-2726	106	11	surfaces	surface	NOUN
cana-2726	106	12	(	(	PUNCT
cana-2726	106	13	iss	iss	PROPN
cana-2726	106	14	)	)	PUNCT
cana-2726	106	15	and	and	CCONJ
cana-2726	106	16	natural	natural	ADJ
cana-2726	106	17	surfaces	surface	NOUN
cana-2726	106	18	(	(	PUNCT
cana-2726	106	19	nss	nss	PROPN
cana-2726	106	20	)	)	PUNCT
cana-2726	106	21	,	,	PUNCT
cana-2726	106	22	the	the	DET
cana-2726	106	23	endisi	endisi	VERB
cana-2726	106	24	is	be	AUX
cana-2726	106	25	primary	primary	ADJ
cana-2726	106	26	selected	select	VERB
cana-2726	106	27	the	the	DET
cana-2726	106	28	blue	blue	ADJ
cana-2726	106	29	(	(	PUNCT
cana-2726	106	30	color	color	NOUN
cana-2726	106	31	)	)	PUNCT
cana-2726	106	32	band	band	NOUN
cana-2726	106	33	as	as	ADP
cana-2726	106	34	an	an	DET
cana-2726	106	35	impervious	impervious	ADJ
cana-2726	106	36	surfaces	surface	NOUN
cana-2726	106	37	(	(	PUNCT
cana-2726	106	38	iss	iss	NOUN
cana-2726	106	39	)	)	PUNCT
cana-2726	106	40	enhancement	enhancement	NOUN
cana-2726	106	41	factor	factor	NOUN
cana-2726	106	42	as	as	ADV
cana-2726	106	43	well	well	ADV
cana-2726	106	44	as	as	ADP
cana-2726	106	45	simply	simply	ADV
cana-2726	106	46	ratio	ratio	NOUN
cana-2726	106	47	of	of	ADP
cana-2726	106	48	band	band	NOUN
cana-2726	106	49	swir_1	swir_1	PROPN
cana-2726	106	50	to	to	PART
cana-2726	106	51	band	band	VERB
cana-2726	106	52	swir_2	swir_2	ADV
cana-2726	106	53	along	along	ADP
cana-2726	106	54	with	with	ADP
cana-2726	106	55	mndwi	mndwi	NOUN
cana-2726	106	56	as	as	ADP
cana-2726	106	57	obstruction	obstruction	NOUN
cana-2726	106	58	.	.	PUNCT
cana-2726	107	1	figure	figure	NOUN
cana-2726	107	2	:	:	PUNCT
cana-2726	107	3	07	07	NUM
cana-2726	107	4	endisi	endisi	VERB
cana-2726	107	5	calculation	calculation	NOUN
cana-2726	107	6	(	(	PUNCT
cana-2726	107	7	mndwi	mndwi	ADV
cana-2726	107	8	,	,	PUNCT
cana-2726	107	9	swir_diff	swir_diff	NOUN
cana-2726	107	10	and	and	CCONJ
cana-2726	107	11	alpha	alpha	NOUN
cana-2726	107	12	)	)	PUNCT
cana-2726	107	13	3.2.2	3.2.2	NUM
cana-2726	107	14	)	)	PUNCT
cana-2726	107	15	apply	apply	VERB
cana-2726	107	16	threshold	threshold	NOUN
cana-2726	107	17	:	:	PUNCT
cana-2726	107	18	the	the	DET
cana-2726	107	19	change	change	NOUN
cana-2726	107	20	detection	detection	NOUN
cana-2726	107	21	image	image	NOUN
cana-2726	107	22	analysis	analysis	NOUN
cana-2726	107	23	is	be	AUX
cana-2726	107	24	one	one	NUM
cana-2726	107	25	of	of	ADP
cana-2726	107	26	primary	primary	ADJ
cana-2726	107	27	step	step	NOUN
cana-2726	107	28	in	in	ADP
cana-2726	107	29	comparison	comparison	NOUN
cana-2726	107	30	of	of	ADP
cana-2726	107	31	remote	remote	ADJ
cana-2726	107	32	sensing	sense	VERB
cana-2726	107	33	multitemporal	multitemporal	ADJ
cana-2726	107	34	images	image	NOUN
cana-2726	107	35	.	.	PUNCT
cana-2726	108	1	the	the	DET
cana-2726	108	2	main	main	ADJ
cana-2726	108	3	aim	aim	NOUN
cana-2726	108	4	of	of	ADP
cana-2726	108	5	change	change	NOUN
cana-2726	108	6	detection	detection	NOUN
cana-2726	108	7	image	image	NOUN
cana-2726	108	8	analysis	analysis	NOUN
cana-2726	108	9	is	be	AUX
cana-2726	108	10	to	to	PART
cana-2726	108	11	simply	simply	ADV
cana-2726	108	12	generate	generate	VERB
cana-2726	108	13	a	a	DET
cana-2726	108	14	change_map	change_map	NUM
cana-2726	108	15	image	image	NOUN
cana-2726	108	16	that	that	PRON
cana-2726	108	17	mostly	mostly	ADV
cana-2726	108	18	increases	increase	VERB
cana-2726	108	19	the	the	DET
cana-2726	108	20	contrast	contrast	NOUN
cana-2726	108	21	level	level	NOUN
cana-2726	108	22	between	between	ADP
cana-2726	108	23	both	both	PRON
cana-2726	108	24	changed	change	VERB
cana-2726	108	25	area	area	NOUN
cana-2726	108	26	and	and	CCONJ
cana-2726	108	27	unchanged	unchanged	ADJ
cana-2726	108	28	area	area	NOUN
cana-2726	108	29	.	.	PUNCT
cana-2726	109	1	the	the	DET
cana-2726	109	2	change_map	change_map	NUM
cana-2726	109	3	has	have	AUX
cana-2726	109	4	been	be	AUX
cana-2726	109	5	generated	generate	VERB
cana-2726	109	6	by	by	ADP
cana-2726	109	7	thresholding	thresholde	VERB
cana-2726	109	8	with	with	ADP
cana-2726	109	9	the	the	DET
cana-2726	109	10	otsu	otsu	NOUN
cana-2726	109	11	’s	’s	PART
cana-2726	109	12	method	method	NOUN
cana-2726	109	13	(	(	PUNCT
cana-2726	109	14	threshold=	threshold=	NUM
cana-2726	109	15	-0.1	-0.1	NOUN
cana-2726	109	16	)	)	PUNCT
cana-2726	110	1	[	[	X
cana-2726	110	2	11	11	NUM
cana-2726	110	3	]	]	PUNCT
cana-2726	110	4	.	.	PUNCT
cana-2726	111	1	communications	communication	NOUN
cana-2726	111	2	on	on	ADP
cana-2726	111	3	applied	apply	VERB
cana-2726	111	4	nonlinear	nonlinear	ADJ
cana-2726	111	5	analysis	analysis	NOUN
cana-2726	111	6	issn	issn	NOUN
cana-2726	111	7	:	:	PUNCT
cana-2726	111	8	1074	1074	NUM
cana-2726	111	9	-	-	PUNCT
cana-2726	111	10	133x	133x	NUM
cana-2726	111	11	vol	vol	NOUN
cana-2726	111	12	32	32	NUM
cana-2726	111	13	no	no	NOUN
cana-2726	111	14	.	.	PUNCT
cana-2726	112	1	3s	3s	NUM
cana-2726	112	2	(	(	PUNCT
cana-2726	112	3	2025	2025	NUM
cana-2726	112	4	)	)	PUNCT
cana-2726	112	5	688	688	NUM
cana-2726	112	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	112	7	figure:08	figure:08	NOUN
cana-2726	112	8	calculated	calculate	VERB
cana-2726	112	9	urban	urban	ADJ
cana-2726	112	10	extent	extent	NOUN
cana-2726	112	11	with	with	ADP
cana-2726	112	12	threshold	threshold	NOUN
cana-2726	112	13	(	(	PUNCT
cana-2726	112	14	ostu	ostu	NOUN
cana-2726	112	15	method	method	NOUN
cana-2726	112	16	)	)	PUNCT
cana-2726	112	17	figure	figure	NOUN
cana-2726	112	18	09	09	NUM
cana-2726	112	19	:	:	PUNCT
cana-2726	112	20	binary	binary	ADJ
cana-2726	112	21	map	map	NOUN
cana-2726	112	22	is	be	AUX
cana-2726	112	23	generated	generate	VERB
cana-2726	112	24	a	a	DET
cana-2726	112	25	)	)	PUNCT
cana-2726	112	26	cva	cva	PROPN
cana-2726	112	27	b	b	PROPN
cana-2726	112	28	)	)	PUNCT
cana-2726	112	29	svm	svm	PROPN
cana-2726	112	30	c	c	NOUN
cana-2726	112	31	)	)	PUNCT
cana-2726	112	32	proposed	propose	VERB
cana-2726	112	33	msmd_cnn	msmd_cnn	NOUN
cana-2726	112	34	in	in	ADP
cana-2726	112	35	above	above	ADP
cana-2726	112	36	figure	figure	NOUN
cana-2726	112	37	09	09	NUM
cana-2726	112	38	:	:	PUNCT
cana-2726	112	39	shown	show	VERB
cana-2726	112	40	the	the	DET
cana-2726	112	41	binary	binary	NOUN
cana-2726	112	42	based	base	VERB
cana-2726	112	43	change	change	NOUN
cana-2726	112	44	maps	map	NOUN
cana-2726	112	45	are	be	AUX
cana-2726	112	46	generated	generate	VERB
cana-2726	112	47	by	by	ADP
cana-2726	112	48	the	the	DET
cana-2726	112	49	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	112	50	,	,	PUNCT
cana-2726	112	51	svm	svm	NOUN
cana-2726	112	52	and	and	CCONJ
cana-2726	112	53	proposed	propose	VERB
cana-2726	112	54	msmd_cnn	msmd_cnn	NUM
cana-2726	112	55	technique	technique	NOUN
cana-2726	112	56	.	.	PUNCT
cana-2726	113	1	the	the	DET
cana-2726	113	2	bitemporal	bitemporal	PROPN
cana-2726	113	3	cva	cva	PROPN
cana-2726	113	4	that	that	PRON
cana-2726	113	5	inaccurately	inaccurately	ADV
cana-2726	113	6	identified	identify	VERB
cana-2726	113	7	most	most	ADJ
cana-2726	113	8	areas	area	NOUN
cana-2726	113	9	as	as	ADP
cana-2726	113	10	changes	change	NOUN
cana-2726	113	11	.	.	PUNCT
cana-2726	114	1	the	the	DET
cana-2726	114	2	proposed	propose	VERB
cana-2726	114	3	msmd_cnn	msmd_cnn	NOUN
cana-2726	114	4	and	and	CCONJ
cana-2726	114	5	svm	svm	ADJ
cana-2726	114	6	techniques	technique	NOUN
cana-2726	114	7	have	have	AUX
cana-2726	114	8	been	be	AUX
cana-2726	114	9	superior	superior	ADJ
cana-2726	114	10	performance	performance	NOUN
cana-2726	114	11	compare	compare	VERB
cana-2726	114	12	to	to	ADP
cana-2726	114	13	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	114	14	in	in	ADP
cana-2726	114	15	detecting	detect	VERB
cana-2726	114	16	area	area	NOUN
cana-2726	114	17	change	change	NOUN
cana-2726	114	18	.	.	PUNCT
cana-2726	115	1	figure:10	figure:10	PROPN
cana-2726	115	2	plotted	plot	VERB
cana-2726	115	3	change	change	NOUN
cana-2726	115	4	in	in	ADP
cana-2726	115	5	urban	urban	ADJ
cana-2726	115	6	extent	extent	NOUN
cana-2726	115	7	in	in	ADP
cana-2726	115	8	figure	figure	NOUN
cana-2726	115	9	10	10	NUM
cana-2726	115	10	,	,	PUNCT
cana-2726	115	11	the	the	DET
cana-2726	115	12	area	area	NOUN
cana-2726	115	13	of	of	ADP
cana-2726	115	14	urban	urban	ADJ
cana-2726	115	15	extent	extent	NOUN
cana-2726	115	16	in	in	ADP
cana-2726	115	17	2014	2014	NUM
cana-2726	115	18	is	be	AUX
cana-2726	115	19	33.641999999999996	33.641999999999996	NUM
cana-2726	115	20	km2	km2	X
cana-2726	115	21	(	(	PUNCT
cana-2726	115	22	red	red	ADJ
cana-2726	115	23	color	color	NOUN
cana-2726	115	24	)	)	PUNCT
cana-2726	115	25	and	and	CCONJ
cana-2726	115	26	the	the	DET
cana-2726	115	27	total	total	ADJ
cana-2726	115	28	area	area	NOUN
cana-2726	115	29	of	of	ADP
cana-2726	115	30	urban	urban	ADJ
cana-2726	115	31	extent	extent	NOUN
cana-2726	115	32	in	in	ADP
cana-2726	115	33	2020	2020	NUM
cana-2726	115	34	is	be	AUX
cana-2726	115	35	39.7296	39.7296	NUM
cana-2726	115	36	km2	km2	NOUN
cana-2726	115	37	(	(	PUNCT
cana-2726	115	38	green	green	ADJ
cana-2726	115	39	color	color	NOUN
cana-2726	115	40	)	)	PUNCT
cana-2726	115	41	.	.	PUNCT
cana-2726	116	1	the	the	DET
cana-2726	116	2	figure	figure	NOUN
cana-2726	116	3	10	10	NUM
cana-2726	116	4	shows	show	NOUN
cana-2726	116	5	,	,	PUNCT
cana-2726	116	6	the	the	DET
cana-2726	116	7	confusion	confusion	NOUN
cana-2726	116	8	-	-	PUNCT
cana-2726	116	9	based	base	VERB
cana-2726	116	10	matrices	matrix	NOUN
cana-2726	116	11	of	of	ADP
cana-2726	116	12	binary	binary	ADJ
cana-2726	116	13	change_map	change_map	NUM
cana-2726	116	14	that	that	PRON
cana-2726	116	15	simply	simply	ADV
cana-2726	116	16	comparing	compare	VERB
cana-2726	116	17	with	with	ADP
cana-2726	116	18	the	the	DET
cana-2726	116	19	ground	ground	NOUN
cana-2726	116	20	truth	truth	NOUN
cana-2726	116	21	data	datum	NOUN
cana-2726	116	22	value	value	NOUN
cana-2726	116	23	.	.	PUNCT
cana-2726	117	1	the	the	DET
cana-2726	117	2	based	base	VERB
cana-2726	117	3	-	-	PUNCT
cana-2726	117	4	on	on	ADP
cana-2726	117	5	confusion	confusion	NOUN
cana-2726	117	6	-	-	PUNCT
cana-2726	117	7	based	base	VERB
cana-2726	117	8	matrices	matrix	NOUN
cana-2726	117	9	,	,	PUNCT
cana-2726	117	10	it	it	PRON
cana-2726	117	11	is	be	AUX
cana-2726	117	12	show	show	NOUN
cana-2726	117	13	that	that	SCONJ
cana-2726	117	14	the	the	DET
cana-2726	117	15	bitemporal_cva	bitemporal_cva	ADJ
cana-2726	117	16	algorithm	algorithm	NOUN
cana-2726	117	17	misidentified	misidentifie	VERB
cana-2726	117	18	191	191	NUM
cana-2726	117	19	pixels	pixel	NOUN
cana-2726	117	20	,	,	PUNCT
cana-2726	117	21	where	where	SCONJ
cana-2726	117	22	svm	svm	PROPN
cana-2726	117	23	and	and	CCONJ
cana-2726	117	24	proposed	propose	VERB
cana-2726	117	25	msmd_cnn	msmd_cnn	NUM
cana-2726	117	26	misidentified	misidentifie	VERB
cana-2726	117	27	133	133	NUM
cana-2726	117	28	and	and	CCONJ
cana-2726	117	29	51	51	NUM
cana-2726	117	30	pixels	pixel	NOUN
cana-2726	117	31	,	,	PUNCT
cana-2726	117	32	respectively	respectively	ADV
cana-2726	117	33	.	.	PUNCT
cana-2726	118	1	communications	communication	NOUN
cana-2726	118	2	on	on	ADP
cana-2726	118	3	applied	apply	VERB
cana-2726	118	4	nonlinear	nonlinear	ADJ
cana-2726	118	5	analysis	analysis	NOUN
cana-2726	118	6	issn	issn	NOUN
cana-2726	118	7	:	:	PUNCT
cana-2726	118	8	1074	1074	NUM
cana-2726	118	9	-	-	PUNCT
cana-2726	118	10	133x	133x	NUM
cana-2726	118	11	vol	vol	NOUN
cana-2726	118	12	32	32	NUM
cana-2726	118	13	no	no	NOUN
cana-2726	118	14	.	.	PUNCT
cana-2726	119	1	3s	3s	NUM
cana-2726	119	2	(	(	PUNCT
cana-2726	119	3	2025	2025	NUM
cana-2726	119	4	)	)	PUNCT
cana-2726	120	1	689	689	NUM
cana-2726	120	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	120	3	figure	figure	NOUN
cana-2726	120	4	11	11	NUM
cana-2726	120	5	:	:	PUNCT
cana-2726	120	6	a	a	X
cana-2726	120	7	)	)	PUNCT
cana-2726	120	8	confusion	confusion	NOUN
cana-2726	120	9	matrices_cva	matrices_cva	PROPN
cana-2726	120	10	b	b	NOUN
cana-2726	120	11	)	)	PUNCT
cana-2726	120	12	confusion	confusion	NOUN
cana-2726	120	13	matrices_svm	matrices_svm	X
cana-2726	120	14	c	c	NOUN
cana-2726	120	15	)	)	PUNCT
cana-2726	120	16	confusion	confusion	NOUN
cana-2726	120	17	matrices_msmd_cnn	matrices_msmd_cnn	VERB
cana-2726	120	18	these	these	DET
cana-2726	120	19	numbers	number	NOUN
cana-2726	120	20	in	in	ADP
cana-2726	120	21	the	the	DET
cana-2726	120	22	confusion	confusion	NOUN
cana-2726	120	23	matrices	matrix	NOUN
cana-2726	120	24	with	with	ADP
cana-2726	120	25	cva	cva	PROPN
cana-2726	120	26	,	,	PUNCT
cana-2726	120	27	svm	svm	PROPN
cana-2726	120	28	and	and	CCONJ
cana-2726	120	29	proposed	propose	VERB
cana-2726	120	30	msmd_cnn	msmd_cnn	NUM
cana-2726	120	31	shows	show	VERB
cana-2726	120	32	the	the	DET
cana-2726	120	33	overall	overall	ADJ
cana-2726	120	34	performance	performance	NOUN
cana-2726	120	35	of	of	ADP
cana-2726	120	36	cva	cva	PROPN
cana-2726	120	37	,	,	PUNCT
cana-2726	120	38	svm	svm	NOUN
cana-2726	120	39	and	and	CCONJ
cana-2726	120	40	msmd_cnn	msmd_cnn	NUM
cana-2726	120	41	algorithm	algorithm	NOUN
cana-2726	120	42	based	base	VERB
cana-2726	120	43	on	on	ADP
cana-2726	120	44	overall	overall	ADJ
cana-2726	120	45	classification	classification	NOUN
cana-2726	120	46	accuracy	accuracy	NOUN
cana-2726	120	47	.	.	PUNCT
cana-2726	121	1	additionally	additionally	ADV
cana-2726	121	2	,	,	PUNCT
cana-2726	121	3	all	all	DET
cana-2726	121	4	evaluation	evaluation	NOUN
cana-2726	121	5	criteria	criterion	NOUN
cana-2726	121	6	,	,	PUNCT
cana-2726	121	7	the	the	DET
cana-2726	121	8	precision	precision	NOUN
cana-2726	121	9	value_(p	value_(p	NUM
cana-2726	121	10	)	)	PUNCT
cana-2726	121	11	,	,	PUNCT
cana-2726	121	12	recall	recall	VERB
cana-2726	121	13	rate_(r	rate_(r	NOUN
cana-2726	121	14	)	)	PUNCT
cana-2726	121	15	,	,	PUNCT
cana-2726	121	16	f1	f1	PROPN
cana-2726	121	17	score_(f1	score_(f1	PROPN
cana-2726	121	18	)	)	PUNCT
cana-2726	121	19	,	,	PUNCT
cana-2726	121	20	overall	overall	ADV
cana-2726	121	21	accuracy_(oa	accuracy_(oa	ADV
cana-2726	121	22	)	)	PUNCT
cana-2726	121	23	and	and	CCONJ
cana-2726	121	24	kappa	kappa	NOUN
cana-2726	121	25	coefficient_(kc	coefficient_(kc	PROPN
cana-2726	121	26	)	)	PUNCT
cana-2726	121	27	,	,	PUNCT
cana-2726	121	28	are	be	AUX
cana-2726	121	29	used	use	VERB
cana-2726	121	30	to	to	PART
cana-2726	121	31	conducted	conduct	VERB
cana-2726	121	32	an	an	DET
cana-2726	121	33	extensive	extensive	ADJ
cana-2726	121	34	along	along	ADV
cana-2726	121	35	with	with	ADP
cana-2726	121	36	perceptible	perceptible	ADJ
cana-2726	121	37	assessment	assessment	NOUN
cana-2726	121	38	of	of	ADP
cana-2726	121	39	results	result	NOUN
cana-2726	121	40	.	.	PUNCT
cana-2726	122	1	table	table	NOUN
cana-2726	122	2	1	1	NUM
cana-2726	122	3	:	:	PUNCT
cana-2726	122	4	accuracy	accuracy	NOUN
cana-2726	122	5	based	base	VERB
cana-2726	122	6	assessment	assessment	NOUN
cana-2726	122	7	of	of	ADP
cana-2726	122	8	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	122	9	in	in	ADP
cana-2726	122	10	change	change	NOUN
cana-2726	122	11	detection	detection	NOUN
cana-2726	122	12	(	(	PUNCT
cana-2726	122	13	cd	cd	PROPN
cana-2726	122	14	)	)	PUNCT
cana-2726	122	15	.	.	PUNCT
cana-2726	123	1	table	table	NOUN
cana-2726	123	2	2	2	NUM
cana-2726	123	3	:	:	PUNCT
cana-2726	123	4	accuracy	accuracy	NOUN
cana-2726	123	5	based	base	VERB
cana-2726	123	6	assessment	assessment	NOUN
cana-2726	123	7	of	of	ADP
cana-2726	123	8	svm	svm	PROPN
cana-2726	123	9	in	in	ADP
cana-2726	123	10	change	change	NOUN
cana-2726	123	11	detection	detection	NOUN
cana-2726	123	12	(	(	PUNCT
cana-2726	123	13	cd	cd	PROPN
cana-2726	123	14	)	)	PUNCT
cana-2726	123	15	.	.	PUNCT
cana-2726	124	1	table	table	NOUN
cana-2726	124	2	3	3	NUM
cana-2726	124	3	:	:	PUNCT
cana-2726	124	4	accuracy	accuracy	NOUN
cana-2726	124	5	assessment	assessment	NOUN
cana-2726	124	6	of	of	ADP
cana-2726	124	7	proposed	propose	VERB
cana-2726	124	8	msmd_cnn	msmd_cnn	NOUN
cana-2726	124	9	in	in	ADP
cana-2726	124	10	change	change	NOUN
cana-2726	124	11	detection	detection	NOUN
cana-2726	124	12	(	(	PUNCT
cana-2726	124	13	cd	cd	PROPN
cana-2726	124	14	)	)	PUNCT
cana-2726	124	15	.	.	PUNCT
cana-2726	125	1	in	in	ADP
cana-2726	125	2	the	the	DET
cana-2726	125	3	table	table	NOUN
cana-2726	125	4	3	3	NUM
cana-2726	125	5	,	,	PUNCT
cana-2726	125	6	the	the	DET
cana-2726	125	7	proposed	propose	VERB
cana-2726	125	8	msmd_cnn	msmd_cnn	NOUN
cana-2726	125	9	in	in	ADP
cana-2726	125	10	change	change	NOUN
cana-2726	125	11	detection	detection	NOUN
cana-2726	125	12	(	(	PUNCT
cana-2726	125	13	cd	cd	NOUN
cana-2726	125	14	)	)	PUNCT
cana-2726	125	15	approach	approach	NOUN
cana-2726	125	16	determines	determine	VERB
cana-2726	125	17	a	a	DET
cana-2726	125	18	precison_(p	precison_(p	PROPN
cana-2726	125	19	)	)	PUNCT
cana-2726	125	20	of	of	ADP
cana-2726	125	21	0.9781	0.9781	NUM
cana-2726	125	22	,	,	PUNCT
cana-2726	125	23	recall	recall	VERB
cana-2726	125	24	rate_(r	rate_(r	NOUN
cana-2726	125	25	)	)	PUNCT
cana-2726	125	26	of	of	ADP
cana-2726	125	27	90.59	90.59	NUM
cana-2726	125	28	and	and	CCONJ
cana-2726	125	29	f1	f1	PROPN
cana-2726	125	30	score_(f1	score_(f1	PROPN
cana-2726	125	31	)	)	PUNCT
cana-2726	125	32	of	of	ADP
cana-2726	125	33	0.8635	0.8635	NUM
cana-2726	125	34	in	in	ADP
cana-2726	125	35	detecting	detect	VERB
cana-2726	125	36	changes	change	NOUN
cana-2726	125	37	that	that	PRON
cana-2726	125	38	representing	represent	VERB
cana-2726	125	39	the	the	DET
cana-2726	125	40	highest	high	ADJ
cana-2726	125	41	precision	precision	NOUN
cana-2726	125	42	value	value	NOUN
cana-2726	125	43	(	(	PUNCT
cana-2726	125	44	p	p	NOUN
cana-2726	125	45	)	)	PUNCT
cana-2726	125	46	,	,	PUNCT
cana-2726	125	47	recall	recall	VERB
cana-2726	125	48	score	score	NOUN
cana-2726	125	49	(	(	PUNCT
cana-2726	125	50	r	r	NOUN
cana-2726	125	51	)	)	PUNCT
cana-2726	125	52	and	and	CCONJ
cana-2726	125	53	f1	f1	PROPN
cana-2726	125	54	score	score	NOUN
cana-2726	125	55	(	(	PUNCT
cana-2726	125	56	f1	f1	NOUN
cana-2726	125	57	)	)	PUNCT
cana-2726	125	58	among	among	ADP
cana-2726	125	59	bitemporal_cva	bitemporal_cva	NUM
cana-2726	125	60	and	and	CCONJ
cana-2726	125	61	svm	svm	ADJ
cana-2726	125	62	methods	method	NOUN
cana-2726	125	63	.	.	PUNCT
cana-2726	126	1	the	the	DET
cana-2726	126	2	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	126	3	exhibits	exhibit	VERB
cana-2726	126	4	the	the	DET
cana-2726	126	5	poor	poor	ADJ
cana-2726	126	6	performance	performance	NOUN
cana-2726	126	7	with	with	ADP
cana-2726	126	8	precison_(p	precison_(p	PROPN
cana-2726	126	9	)	)	PUNCT
cana-2726	126	10	value	value	NOUN
cana-2726	126	11	of	of	ADP
cana-2726	126	12	0.4576	0.4576	NUM
cana-2726	126	13	,	,	PUNCT
cana-2726	126	14	recall	recall	VERB
cana-2726	126	15	rate_(r	rate_(r	NOUN
cana-2726	126	16	)	)	PUNCT
cana-2726	126	17	of	of	ADP
cana-2726	126	18	61.42	61.42	NUM
cana-2726	126	19	and	and	CCONJ
cana-2726	126	20	f1	f1	PROPN
cana-2726	126	21	score_(f1	score_(f1	PROPN
cana-2726	126	22	)	)	PUNCT
cana-2726	126	23	of	of	ADP
cana-2726	126	24	0.5179	0.5179	NUM
cana-2726	126	25	.	.	PUNCT
cana-2726	127	1	finally	finally	ADV
cana-2726	127	2	,	,	PUNCT
cana-2726	127	3	when	when	SCONJ
cana-2726	127	4	considering	consider	VERB
cana-2726	127	5	all	all	DET
cana-2726	127	6	criteria	criterion	NOUN
cana-2726	127	7	,	,	PUNCT
cana-2726	127	8	it	it	PRON
cana-2726	127	9	come	come	VERB
cana-2726	127	10	that	that	SCONJ
cana-2726	127	11	the	the	DET
cana-2726	127	12	proposed	propose	VERB
cana-2726	127	13	msmd_cnn	msmd_cnn	NUM
cana-2726	127	14	network	network	NOUN
cana-2726	127	15	model	model	NOUN
cana-2726	127	16	outperforms	outperform	VERB
cana-2726	127	17	the	the	DET
cana-2726	127	18	good	good	ADJ
cana-2726	127	19	performance	performance	NOUN
cana-2726	127	20	compared	compare	VERB
cana-2726	127	21	to	to	ADP
cana-2726	127	22	the	the	DET
cana-2726	127	23	other	other	ADJ
cana-2726	127	24	bitemporal_cva	bitemporal_cva	ADJ
cana-2726	127	25	and	and	CCONJ
cana-2726	127	26	svm	svm	ADJ
cana-2726	127	27	methods	method	NOUN
cana-2726	127	28	.	.	PUNCT
cana-2726	128	1	communications	communication	NOUN
cana-2726	128	2	on	on	ADP
cana-2726	128	3	applied	apply	VERB
cana-2726	128	4	nonlinear	nonlinear	ADJ
cana-2726	128	5	analysis	analysis	NOUN
cana-2726	128	6	issn	issn	NOUN
cana-2726	128	7	:	:	PUNCT
cana-2726	128	8	1074	1074	NUM
cana-2726	128	9	-	-	PUNCT
cana-2726	128	10	133x	133x	NUM
cana-2726	128	11	vol	vol	NOUN
cana-2726	128	12	32	32	NUM
cana-2726	128	13	no	no	NOUN
cana-2726	128	14	.	.	PUNCT
cana-2726	129	1	3s	3s	NUM
cana-2726	129	2	(	(	PUNCT
cana-2726	129	3	2025	2025	NUM
cana-2726	129	4	)	)	PUNCT
cana-2726	129	5	690	690	NUM
cana-2726	129	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2726	129	7	4	4	NUM
cana-2726	129	8	.	.	PUNCT
cana-2726	130	1	conclusions	conclusion	NOUN
cana-2726	130	2	:	:	PUNCT
cana-2726	130	3	the	the	DET
cana-2726	130	4	advancement	advancement	NOUN
cana-2726	130	5	in	in	ADP
cana-2726	130	6	remote	remote	ADJ
cana-2726	130	7	sensing	sense	VERB
cana-2726	130	8	satellite	satellite	NOUN
cana-2726	130	9	images	image	NOUN
cana-2726	130	10	technologies	technology	NOUN
cana-2726	130	11	has	have	AUX
cana-2726	130	12	huge	huge	ADJ
cana-2726	130	13	improved	improve	VERB
cana-2726	130	14	an	an	DET
cana-2726	130	15	accurate	accurate	ADJ
cana-2726	130	16	monitoring	monitoring	NOUN
cana-2726	130	17	of	of	ADP
cana-2726	130	18	environmental	environmental	ADJ
cana-2726	130	19	diversity	diversity	NOUN
cana-2726	130	20	mainly	mainly	ADV
cana-2726	130	21	in	in	ADP
cana-2726	130	22	urban	urban	ADJ
cana-2726	130	23	areas	area	NOUN
cana-2726	130	24	.	.	PUNCT
cana-2726	131	1	previously	previously	ADV
cana-2726	131	2	,	,	PUNCT
cana-2726	131	3	the	the	DET
cana-2726	131	4	classical	classical	ADJ
cana-2726	131	5	methods	method	NOUN
cana-2726	131	6	can	can	AUX
cana-2726	131	7	not	not	PART
cana-2726	131	8	easily	easily	ADV
cana-2726	131	9	integrate	integrate	VERB
cana-2726	131	10	with	with	ADP
cana-2726	131	11	spatial	spatial	ADJ
cana-2726	131	12	based	base	VERB
cana-2726	131	13	spectral	spectral	ADJ
cana-2726	131	14	information	information	NOUN
cana-2726	131	15	along	along	ADP
cana-2726	131	16	with	with	ADP
cana-2726	131	17	some	some	DET
cana-2726	131	18	detailed	detailed	ADJ
cana-2726	131	19	features	feature	NOUN
cana-2726	131	20	,	,	PUNCT
cana-2726	131	21	limiting	limit	VERB
cana-2726	131	22	their	their	PRON
cana-2726	131	23	overall	overall	ADJ
cana-2726	131	24	performance	performance	NOUN
cana-2726	131	25	of	of	ADP
cana-2726	131	26	detected	detect	VERB
cana-2726	131	27	changes	change	NOUN
cana-2726	131	28	in	in	ADP
cana-2726	131	29	the	the	DET
cana-2726	131	30	urban	urban	ADJ
cana-2726	131	31	areas	area	NOUN
cana-2726	131	32	.	.	PUNCT
cana-2726	132	1	the	the	DET
cana-2726	132	2	advanced	advanced	ADJ
cana-2726	132	3	deep	deep	ADJ
cana-2726	132	4	learning	learning	NOUN
cana-2726	132	5	based	base	VERB
cana-2726	132	6	techniques	technique	NOUN
cana-2726	132	7	that	that	PRON
cana-2726	132	8	accurately	accurately	ADV
cana-2726	132	9	extract	extract	VERB
cana-2726	132	10	both	both	CCONJ
cana-2726	132	11	spatial	spatial	ADJ
cana-2726	132	12	based	base	VERB
cana-2726	132	13	spectral	spectral	ADJ
cana-2726	132	14	information	information	NOUN
cana-2726	132	15	and	and	CCONJ
cana-2726	132	16	detailed	detailed	ADJ
cana-2726	132	17	features	feature	NOUN
cana-2726	132	18	during	during	ADP
cana-2726	132	19	feature	feature	NOUN
cana-2726	132	20	extraction	extraction	NOUN
cana-2726	132	21	offer	offer	VERB
cana-2726	132	22	high	high	ADJ
cana-2726	132	23	accuracy	accuracy	NOUN
cana-2726	132	24	in	in	ADP
cana-2726	132	25	urban	urban	ADJ
cana-2726	132	26	area	area	NOUN
cana-2726	132	27	change	change	NOUN
cana-2726	132	28	detection	detection	NOUN
cana-2726	132	29	.	.	PUNCT
cana-2726	133	1	in	in	ADP
cana-2726	133	2	this	this	DET
cana-2726	133	3	research	research	NOUN
cana-2726	133	4	study	study	NOUN
cana-2726	133	5	,	,	PUNCT
cana-2726	133	6	an	an	DET
cana-2726	133	7	advanced	advanced	ADJ
cana-2726	133	8	deep	deep	ADJ
cana-2726	133	9	learning	learning	NOUN
cana-2726	133	10	-	-	PUNCT
cana-2726	133	11	based	base	VERB
cana-2726	133	12	change	change	NOUN
cana-2726	133	13	detection	detection	NOUN
cana-2726	133	14	(	(	PUNCT
cana-2726	133	15	cd	cd	NOUN
cana-2726	133	16	)	)	PUNCT
cana-2726	133	17	approach	approach	NOUN
cana-2726	133	18	to	to	ADP
cana-2726	133	19	previous	previous	ADJ
cana-2726	133	20	classical	classical	ADJ
cana-2726	133	21	change	change	NOUN
cana-2726	133	22	detection	detection	NOUN
cana-2726	133	23	methods	method	NOUN
cana-2726	133	24	,	,	PUNCT
cana-2726	133	25	namely	namely	ADV
cana-2726	133	26	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	133	27	and	and	CCONJ
cana-2726	133	28	svm	svm	ADJ
cana-2726	133	29	to	to	PART
cana-2726	133	30	detect	detect	VERB
cana-2726	133	31	area	area	NOUN
cana-2726	133	32	changes	change	NOUN
cana-2726	133	33	in	in	ADP
cana-2726	133	34	australian	australian	ADJ
cana-2726	133	35	capital	capital	NOUN
cana-2726	133	36	territory	territory	NOUN
cana-2726	133	37	(	(	PUNCT
cana-2726	133	38	act	act	PROPN
cana-2726	133	39	)	)	PUNCT
cana-2726	133	40	in	in	ADP
cana-2726	133	41	ngunnawal	ngunnawal	PROPN
cana-2726	133	42	,	,	PUNCT
cana-2726	133	43	palmerston	palmerston	PROPN
cana-2726	133	44	and	and	CCONJ
cana-2726	133	45	new	new	ADJ
cana-2726	133	46	south	south	PROPN
cana-2726	133	47	wales	wales	PROPN
cana-2726	133	48	cities	city	NOUN
cana-2726	133	49	.	.	PUNCT
cana-2726	134	1	it	it	PRON
cana-2726	134	2	has	have	AUX
cana-2726	134	3	been	be	AUX
cana-2726	134	4	concluded	conclude	VERB
cana-2726	134	5	that	that	SCONJ
cana-2726	134	6	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	134	7	has	have	AUX
cana-2726	134	8	achieved	achieve	VERB
cana-2726	134	9	f1_score	f1_score	ADJ
cana-2726	134	10	0.5179	0.5179	NUM
cana-2726	134	11	and	and	CCONJ
cana-2726	134	12	svm	svm	ADJ
cana-2726	134	13	technique	technique	NOUN
cana-2726	134	14	has	have	AUX
cana-2726	134	15	achieved	achieve	VERB
cana-2726	134	16	f1_score	f1_score	ADJ
cana-2726	134	17	0.6988	0.6988	NUM
cana-2726	134	18	overall	overall	ADJ
cana-2726	134	19	accuracy	accuracy	NOUN
cana-2726	134	20	assessment	assessment	NOUN
cana-2726	134	21	.	.	PUNCT
cana-2726	135	1	on	on	ADP
cana-2726	135	2	the	the	DET
cana-2726	135	3	other	other	ADJ
cana-2726	135	4	hand	hand	NOUN
cana-2726	135	5	,	,	PUNCT
cana-2726	135	6	the	the	DET
cana-2726	135	7	proposed	propose	VERB
cana-2726	135	8	msmd_cnn	msmd_cnn	NUM
cana-2726	135	9	has	have	AUX
cana-2726	135	10	achieved	achieve	VERB
cana-2726	135	11	f1_score	f1_score	ADV
cana-2726	135	12	0.8635	0.8635	NUM
cana-2726	135	13	overall	overall	ADJ
cana-2726	135	14	accuracy	accuracy	NOUN
cana-2726	135	15	assessment	assessment	NOUN
cana-2726	135	16	.	.	PUNCT
cana-2726	136	1	based	base	VERB
cana-2726	136	2	on	on	ADP
cana-2726	136	3	different	different	ADJ
cana-2726	136	4	evaluation	evaluation	NOUN
cana-2726	136	5	criteria	criterion	NOUN
cana-2726	136	6	of	of	ADP
cana-2726	136	7	the	the	DET
cana-2726	136	8	results	result	NOUN
cana-2726	136	9	,	,	PUNCT
cana-2726	136	10	the	the	DET
cana-2726	136	11	bitemporal_cva	bitemporal_cva	PROPN
cana-2726	136	12	has	have	VERB
cana-2726	136	13	the	the	DET
cana-2726	136	14	poor	poor	ADJ
cana-2726	136	15	performance	performance	NOUN
cana-2726	136	16	in	in	ADP
cana-2726	136	17	the	the	DET
cana-2726	136	18	change	change	NOUN
cana-2726	136	19	detection	detection	NOUN
cana-2726	136	20	(	(	PUNCT
cana-2726	136	21	cd	cd	PROPN
cana-2726	136	22	)	)	PUNCT
cana-2726	136	23	.	.	PUNCT
cana-2726	137	1	the	the	DET
cana-2726	137	2	supervised	supervised	ADJ
cana-2726	137	3	machine	machine	NOUN
cana-2726	137	4	svm	svm	ADJ
cana-2726	137	5	algorithm	algorithm	NOUN
cana-2726	137	6	can	can	AUX
cana-2726	137	7	enhance	enhance	VERB
cana-2726	137	8	the	the	DET
cana-2726	137	9	accuracy	accuracy	NOUN
cana-2726	137	10	,	,	PUNCT
cana-2726	137	11	the	the	DET
cana-2726	137	12	proposed	propose	VERB
cana-2726	137	13	msmd_cnn	msmd_cnn	NUM
cana-2726	137	14	resulted	result	VERB
cana-2726	137	15	in	in	ADP
cana-2726	137	16	an	an	DET
cana-2726	137	17	exceptional	exceptional	ADJ
cana-2726	137	18	18	18	NUM
cana-2726	137	19	%	%	NOUN
cana-2726	137	20	increase	increase	NOUN
cana-2726	137	21	in	in	ADP
cana-2726	137	22	the	the	DET
cana-2726	137	23	overall	overall	ADJ
cana-2726	137	24	accuracy	accuracy	NOUN
cana-2726	137	25	of	of	ADP
cana-2726	137	26	the	the	DET
cana-2726	137	27	msmd_cnn	msmd_cnn	NUM
cana-2726	137	28	binary	binary	PROPN
cana-2726	137	29	change	change	NOUN
cana-2726	137	30	map	map	NOUN
cana-2726	137	31	.	.	PUNCT
cana-2726	138	1	references	reference	NOUN
cana-2726	138	2	:	:	PUNCT
cana-2726	139	1	[	[	X
cana-2726	139	2	1	1	X
cana-2726	139	3	]	]	X
cana-2726	139	4	guangliang	guangliang	PROPN
cana-2726	139	5	cheng	cheng	PROPN
cana-2726	139	6	,	,	PUNCT
cana-2726	139	7	change	change	VERB
cana-2726	139	8	detection	detection	NOUN
cana-2726	139	9	methods	method	NOUN
cana-2726	139	10	for	for	ADP
cana-2726	139	11	remote	remote	ADJ
cana-2726	139	12	sensing	sensing	NOUN
cana-2726	139	13	in	in	ADP
cana-2726	139	14	the	the	DET
cana-2726	139	15	last	last	ADJ
cana-2726	139	16	decade	decade	NOUN
cana-2726	139	17	:	:	PUNCT
cana-2726	139	18	a	a	DET
cana-2726	139	19	comprehensive	comprehensive	ADJ
cana-2726	139	20	review	review	NOUN
cana-2726	139	21	,	,	PUNCT
cana-2726	139	22	mdpi	mdpi	PROPN
cana-2726	139	23	,	,	PUNCT
cana-2726	139	24	remote	remote	ADJ
cana-2726	139	25	sens	sen	NOUN
cana-2726	139	26	.	.	PROPN
cana-2726	139	27	2024	2024	NUM
cana-2726	139	28	,	,	PUNCT
cana-2726	139	29	16(13	16(13	NUM
cana-2726	139	30	)	)	PUNCT
cana-2726	139	31	,	,	PUNCT
cana-2726	139	32	2355	2355	NUM
cana-2726	139	33	.	.	PUNCT
cana-2726	140	1	[	[	X
cana-2726	140	2	2	2	X
cana-2726	140	3	]	]	PUNCT
cana-2726	140	4	zhuo	zhuo	PROPN
cana-2726	140	5	zheng	zheng	PROPN
cana-2726	140	6	,	,	PUNCT
cana-2726	140	7	unifying	unify	VERB
cana-2726	140	8	remote	remote	ADJ
cana-2726	140	9	sensing	sense	VERB
cana-2726	140	10	change	change	NOUN
cana-2726	140	11	detection	detection	NOUN
cana-2726	140	12	via	via	ADP
cana-2726	140	13	deep	deep	ADJ
cana-2726	140	14	probabilistic	probabilistic	ADJ
cana-2726	140	15	change	change	NOUN
cana-2726	140	16	models	model	NOUN
cana-2726	140	17	:	:	PUNCT
cana-2726	140	18	from	from	ADP
cana-2726	140	19	principles	principle	NOUN
cana-2726	140	20	,	,	PUNCT
cana-2726	140	21	models	model	NOUN
cana-2726	140	22	to	to	ADP
cana-2726	140	23	applications	application	NOUN
cana-2726	140	24	,	,	PUNCT
cana-2726	140	25	isprs	isprs	NOUN
cana-2726	140	26	,	,	PUNCT
cana-2726	140	27	volume	volume	NOUN
cana-2726	140	28	215	215	NUM
cana-2726	140	29	,	,	PUNCT
cana-2726	140	30	september	september	PROPN
cana-2726	140	31	2024	2024	NUM
cana-2726	140	32	,	,	PUNCT
cana-2726	140	33	pages	page	NOUN
cana-2726	140	34	239	239	NUM
cana-2726	140	35	-	-	SYM
cana-2726	140	36	255	255	NUM
cana-2726	140	37	.	.	PUNCT
cana-2726	141	1	[	[	X
cana-2726	141	2	3	3	NUM
cana-2726	141	3	]	]	X
cana-2726	141	4	wang	wang	PROPN
cana-2726	141	5	,	,	PUNCT
cana-2726	141	6	l.	l.	PROPN
cana-2726	141	7	;	;	PUNCT
cana-2726	141	8	yan	yan	PROPN
cana-2726	141	9	,	,	PUNCT
cana-2726	141	10	j.	j.	PROPN
cana-2726	141	11	;	;	PUNCT
cana-2726	141	12	mu	mu	PROPN
cana-2726	141	13	,	,	PUNCT
cana-2726	141	14	l.	l.	PROPN
cana-2726	141	15	;	;	PUNCT
cana-2726	141	16	huang	huang	PROPN
cana-2726	141	17	,	,	PUNCT
cana-2726	141	18	l.	l.	PROPN
cana-2726	141	19	knowledge	knowledge	PROPN
cana-2726	141	20	discovery	discovery	PROPN
cana-2726	141	21	from	from	ADP
cana-2726	141	22	remote	remote	ADJ
cana-2726	141	23	sensing	sensing	NOUN
cana-2726	141	24	images	image	NOUN
cana-2726	141	25	:	:	PUNCT
cana-2726	141	26	a	a	DET
cana-2726	141	27	review	review	NOUN
cana-2726	141	28	.	.	PUNCT
cana-2726	142	1	wires	wire	NOUN
cana-2726	142	2	data	data	PROPN
cana-2726	142	3	min	min	PROPN
cana-2726	142	4	.	.	PROPN
cana-2726	142	5	knowl	knowl	PROPN
cana-2726	142	6	.	.	PUNCT
cana-2726	143	1	discov	discov	NOUN
cana-2726	143	2	.	.	PUNCT
cana-2726	144	1	2020	2020	NUM
cana-2726	144	2	,	,	PUNCT
cana-2726	144	3	10	10	NUM
cana-2726	144	4	,	,	PUNCT
cana-2726	144	5	e1371	e1371	X
cana-2726	144	6	.	.	PUNCT
cana-2726	145	1	[	[	X
cana-2726	145	2	4	4	X
cana-2726	145	3	]	]	PUNCT
cana-2726	145	4	l.	l.	PROPN
cana-2726	145	5	castellana	castellana	PROPN
cana-2726	145	6	,	,	PUNCT
cana-2726	145	7	a	a	DET
cana-2726	145	8	composed	compose	VERB
cana-2726	145	9	supervised	supervised	ADJ
cana-2726	145	10	/	/	SYM
cana-2726	145	11	unsupervised	unsupervised	ADJ
cana-2726	145	12	approach	approach	NOUN
cana-2726	145	13	to	to	PART
cana-2726	145	14	improve	improve	VERB
cana-2726	145	15	change	change	NOUN
cana-2726	145	16	detection	detection	NOUN
cana-2726	145	17	from	from	ADP
cana-2726	145	18	remote	remote	ADJ
cana-2726	145	19	sensing	sensing	NOUN
cana-2726	145	20	,	,	PUNCT
cana-2726	145	21	pattern	pattern	NOUN
cana-2726	145	22	recognition	recognition	NOUN
cana-2726	145	23	letters	letter	NOUN
cana-2726	145	24	,	,	PUNCT
cana-2726	145	25	volume	volume	NOUN
cana-2726	145	26	28	28	NUM
cana-2726	145	27	,	,	PUNCT
cana-2726	145	28	issue	issue	NOUN
cana-2726	145	29	4	4	NUM
cana-2726	145	30	,	,	PUNCT
cana-2726	145	31	1	1	NUM
cana-2726	145	32	march	march	NOUN
cana-2726	145	33	2007	2007	NUM
cana-2726	145	34	.	.	PUNCT
cana-2726	146	1	[	[	X
cana-2726	146	2	5	5	NUM
cana-2726	146	3	]	]	SYM
cana-2726	146	4	prabuddh	prabuddh	PROPN
cana-2726	146	5	kumar	kumar	PROPN
cana-2726	146	6	mishra	mishra	PROPN
cana-2726	146	7	,	,	PUNCT
cana-2726	146	8	land	land	NOUN
cana-2726	146	9	use	use	NOUN
cana-2726	146	10	and	and	CCONJ
cana-2726	146	11	land	land	NOUN
cana-2726	146	12	cover	cover	NOUN
cana-2726	146	13	change	change	NOUN
cana-2726	146	14	detection	detection	NOUN
cana-2726	146	15	using	use	VERB
cana-2726	146	16	geospatial	geospatial	ADJ
cana-2726	146	17	techniques	technique	NOUN
cana-2726	146	18	in	in	ADP
cana-2726	146	19	the	the	DET
cana-2726	146	20	sikkim	sikkim	PROPN
cana-2726	146	21	himalaya	himalaya	PROPN
cana-2726	146	22	,	,	PUNCT
cana-2726	146	23	india	india	PROPN
cana-2726	146	24	,	,	PUNCT
cana-2726	146	25	the	the	DET
cana-2726	146	26	egyptian	egyptian	ADJ
cana-2726	146	27	journal	journal	NOUN
cana-2726	146	28	of	of	ADP
cana-2726	146	29	remote	remote	ADJ
cana-2726	146	30	sensing	sensing	NOUN
cana-2726	146	31	and	and	CCONJ
cana-2726	146	32	space	space	NOUN
cana-2726	146	33	science	science	NOUN
cana-2726	146	34	,	,	PUNCT
cana-2726	146	35	volume	volume	NOUN
cana-2726	146	36	23	23	NUM
cana-2726	146	37	,	,	PUNCT
cana-2726	146	38	issue	issue	NOUN
cana-2726	146	39	2	2	NUM
cana-2726	146	40	,	,	PUNCT
cana-2726	146	41	august	august	PROPN
cana-2726	146	42	2020	2020	NUM
cana-2726	146	43	,	,	PUNCT
cana-2726	146	44	pages	page	NOUN
cana-2726	146	45	133	133	NUM
cana-2726	146	46	-	-	SYM
cana-2726	146	47	143	143	NUM
cana-2726	146	48	.	.	PUNCT
cana-2726	147	1	[	[	X
cana-2726	147	2	6	6	NUM
cana-2726	147	3	]	]	PUNCT
cana-2726	147	4	nishant	nishant	PROPN
cana-2726	147	5	mehra	mehra	PROPN
cana-2726	147	6	,	,	PUNCT
cana-2726	147	7	assessment	assessment	NOUN
cana-2726	147	8	of	of	ADP
cana-2726	147	9	land	land	NOUN
cana-2726	147	10	use	use	NOUN
cana-2726	147	11	land	land	NOUN
cana-2726	147	12	cover	cover	NOUN
cana-2726	147	13	change	change	NOUN
cana-2726	147	14	and	and	CCONJ
cana-2726	147	15	its	its	PRON
cana-2726	147	16	effects	effect	NOUN
cana-2726	147	17	using	use	VERB
cana-2726	147	18	artificial	artificial	ADJ
cana-2726	147	19	neural	neural	ADJ
cana-2726	147	20	network	network	NOUN
cana-2726	147	21	-	-	PUNCT
cana-2726	147	22	based	base	VERB
cana-2726	147	23	cellular	cellular	ADJ
cana-2726	147	24	automation	automation	NOUN
cana-2726	147	25	,	,	PUNCT
cana-2726	147	26	journal	journal	NOUN
cana-2726	147	27	of	of	ADP
cana-2726	147	28	engineering	engineering	NOUN
cana-2726	147	29	and	and	CCONJ
cana-2726	147	30	applied	apply	VERB
cana-2726	147	31	science	science	NOUN
cana-2726	147	32	,	,	PUNCT
cana-2726	147	33	j.	j.	PROPN
cana-2726	147	34	eng	eng	PROPN
cana-2726	147	35	.	.	PROPN
cana-2726	147	36	appl	appl	PROPN
cana-2726	147	37	.	.	PUNCT
cana-2726	148	1	sci	sci	PROPN
cana-2726	148	2	.	.	PROPN
cana-2726	149	1	71	71	NUM
cana-2726	149	2	,	,	PUNCT
cana-2726	149	3	70	70	NUM
cana-2726	149	4	(	(	PUNCT
cana-2726	149	5	2024	2024	NUM
cana-2726	149	6	)	)	PUNCT
cana-2726	149	7	.	.	PUNCT
cana-2726	150	1	[	[	X
cana-2726	150	2	7	7	X
cana-2726	150	3	]	]	X
cana-2726	150	4	s.	s.	PROPN
cana-2726	150	5	.	.	PUNCT
cana-2726	151	1	shivadekar	shivadekar	PROPN
cana-2726	151	2	,	,	PUNCT
cana-2726	151	3	b.	b.	PROPN
cana-2726	151	4	.	.	PUNCT
cana-2726	152	1	kataria	kataria	PROPN
cana-2726	152	2	,	,	PUNCT
cana-2726	152	3	s.	s.	PROPN
cana-2726	152	4	.	.	PUNCT
cana-2726	153	1	hundekari	hundekari	PROPN
cana-2726	153	2	,	,	PUNCT
cana-2726	153	3	kirti	kirti	PROPN
cana-2726	153	4	wanjale	wanjale	PROPN
cana-2726	153	5	,	,	PUNCT
cana-2726	153	6	v.	v.	PROPN
cana-2726	153	7	p.	p.	NOUN
cana-2726	153	8	balpande	balpande	PROPN
cana-2726	153	9	,	,	PUNCT
cana-2726	153	10	and	and	CCONJ
cana-2726	153	11	r.	r.	PROPN
cana-2726	153	12	.	.	PUNCT
cana-2726	154	1	suryawanshi	suryawanshi	NOUN
cana-2726	154	2	,	,	PUNCT
cana-2726	154	3	“	"	PUNCT
cana-2726	154	4	deep	deep	ADJ
cana-2726	154	5	learning	learning	NOUN
cana-2726	154	6	based	base	VERB
cana-2726	154	7	image	image	NOUN
cana-2726	154	8	classification	classification	NOUN
cana-2726	154	9	of	of	ADP
cana-2726	154	10	lungs	lung	NOUN
cana-2726	154	11	radiography	radiography	NOUN
cana-2726	154	12	for	for	ADP
cana-2726	154	13	detecting	detect	VERB
cana-2726	154	14	covid-19	covid-19	PROPN
cana-2726	154	15	using	use	VERB
cana-2726	154	16	a	a	DET
cana-2726	154	17	deep	deep	ADJ
cana-2726	154	18	cnn	cnn	NOUN
cana-2726	154	19	and	and	CCONJ
cana-2726	154	20	resnet	resnet	VERB
cana-2726	154	21	50	50	NUM
cana-2726	154	22	”	"	PUNCT
cana-2726	154	23	,	,	PUNCT
cana-2726	154	24	int	int	PROPN
cana-2726	154	25	j	j	PROPN
cana-2726	154	26	intell	intell	PROPN
cana-2726	154	27	syst	syst	PROPN
cana-2726	154	28	appl	appl	PROPN
cana-2726	154	29	eng	eng	PROPN
cana-2726	154	30	,	,	PUNCT
cana-2726	154	31	vol	vol	NOUN
cana-2726	154	32	.	.	PROPN
cana-2726	154	33	11	11	NUM
cana-2726	154	34	,	,	PUNCT
cana-2726	154	35	no	no	INTJ
cana-2726	154	36	.	.	NOUN
cana-2726	154	37	1s	1s	NUM
cana-2726	154	38	,	,	PUNCT
cana-2726	154	39	pp	pp	X
cana-2726	154	40	.	.	PUNCT
cana-2726	155	1	241–250	241–250	NUM
cana-2726	155	2	,	,	PUNCT
cana-2726	155	3	jan	jan	PROPN
cana-2726	155	4	.	.	PROPN
cana-2726	155	5	2023	2023	NUM
cana-2726	155	6	.	.	PUNCT
cana-2726	156	1	[	[	X
cana-2726	156	2	8	8	NUM
cana-2726	156	3	]	]	X
cana-2726	156	4	sibo	sibo	PROPN
cana-2726	156	5	yu	yu	PROPN
cana-2726	156	6	,	,	PUNCT
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cana-2726	156	8	sensing	sense	VERB
cana-2726	156	9	image	image	NOUN
cana-2726	156	10	change	change	NOUN
cana-2726	156	11	detection	detection	NOUN
cana-2726	156	12	based	base	VERB
cana-2726	156	13	on	on	ADP
cana-2726	156	14	deep	deep	ADJ
cana-2726	156	15	learning	learning	NOUN
cana-2726	156	16	:	:	PUNCT
cana-2726	156	17	multi	multi	ADJ
cana-2726	156	18	-	-	ADJ
cana-2726	156	19	level	level	ADJ
cana-2726	156	20	feature	feature	NOUN
cana-2726	156	21	cross	cross	NOUN
cana-2726	156	22	-	-	NOUN
cana-2726	156	23	fusion	fusion	NOUN
cana-2726	156	24	with	with	ADP
cana-2726	156	25	3d	3d	ADJ
cana-2726	156	26	-	-	PUNCT
cana-2726	156	27	convolutional	convolutional	ADJ
cana-2726	156	28	neural	neural	ADJ
cana-2726	156	29	networks	network	NOUN
cana-2726	156	30	,	,	PUNCT
cana-2726	156	31	mdpi	mdpi	PROPN
cana-2726	156	32	,	,	PUNCT
cana-2726	156	33	applied	applied	ADJ
cana-2726	156	34	sciences	science	NOUN
cana-2726	156	35	,	,	PUNCT
cana-2726	156	36	volume	volume	NOUN
cana-2726	156	37	14	14	NUM
cana-2726	156	38	,	,	PUNCT
cana-2726	156	39	issue	issue	NOUN
cana-2726	156	40	14	14	NUM
cana-2726	156	41	,	,	PUNCT
cana-2726	156	42	2024	2024	NUM
cana-2726	156	43	.	.	PUNCT
cana-2726	157	1	[	[	X
cana-2726	157	2	9	9	NUM
cana-2726	157	3	]	]	X
cana-2726	157	4	gong	gong	NOUN
cana-2726	157	5	,	,	PUNCT
cana-2726	157	6	m.	m.	NOUN
cana-2726	157	7	;	;	PUNCT
cana-2726	157	8	zhao	zhao	PROPN
cana-2726	157	9	,	,	PUNCT
cana-2726	157	10	j.	j.	PROPN
cana-2726	157	11	;	;	PUNCT
cana-2726	157	12	liu	liu	PROPN
cana-2726	157	13	,	,	PUNCT
cana-2726	157	14	j.	j.	PROPN
cana-2726	157	15	;	;	PUNCT
cana-2726	157	16	miao	miao	PROPN
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cana-2726	157	18	q.	q.	PROPN
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cana-2726	157	26	synthetic	synthetic	ADJ
cana-2726	157	27	aperture	aperture	NOUN
cana-2726	157	28	radar	radar	NOUN
cana-2726	157	29	images	image	NOUN
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cana-2726	158	5	netw	netw	NOUN
cana-2726	158	6	.	.	PUNCT
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cana-2726	159	2	.	.	PUNCT
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cana-2726	160	2	.	.	PUNCT
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cana-2726	161	2	,	,	PUNCT
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cana-2726	161	4	,	,	PUNCT
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cana-2726	161	6	.	.	PUNCT
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cana-2726	162	2	10	10	NUM
cana-2726	162	3	]	]	X
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cana-2726	162	16	comparative	comparative	ADJ
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cana-2726	162	18	:	:	PUNCT
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cana-2726	162	20	computing	computing	NOUN
cana-2726	162	21	service	service	NOUN
cana-2726	162	22	providers	provider	NOUN
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cana-2726	162	30	,	,	PUNCT
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cana-2726	162	34	,	,	PUNCT
cana-2726	162	35	pp	pp	ADJ
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cana-2726	163	2	,	,	PUNCT
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cana-2726	163	5	.	.	PUNCT
cana-2726	164	1	[	[	X
cana-2726	164	2	11	11	NUM
cana-2726	164	3	]	]	X
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cana-2726	164	5	,	,	PUNCT
cana-2726	164	6	n.	n.	NOUN
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cana-2726	165	1	ieee	ieee	PROPN
cana-2726	165	2	trans	trans	PROPN
cana-2726	165	3	.	.	PUNCT
cana-2726	166	1	syst	syst	PROPN
cana-2726	166	2	.	.	PUNCT
cana-2726	167	1	man	man	NOUN
cana-2726	167	2	.	.	PUNCT
cana-2726	168	1	cybern	cybern	PROPN
cana-2726	168	2	.	.	PUNCT
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cana-2726	169	2	,	,	PUNCT
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cana-2726	169	4	,	,	PUNCT
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cana-2726	169	7	66	66	NUM
cana-2726	169	8	.	.	PUNCT
cana-2726	170	1	[	[	X
cana-2726	170	2	12	12	NUM
cana-2726	170	3	]	]	PUNCT
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cana-2726	170	5	,	,	PUNCT
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cana-2726	170	9	,	,	PUNCT
cana-2726	170	10	m.	m.	NOUN
cana-2726	170	11	;	;	PUNCT
cana-2726	170	12	ghanbari	ghanbari	PROPN
cana-2726	170	13	,	,	PUNCT
cana-2726	170	14	h.	h.	PROPN
cana-2726	170	15	;	;	PUNCT
cana-2726	170	16	mohammadimanesh	mohammadimanesh	PROPN
cana-2726	170	17	,	,	PUNCT
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cana-2726	170	38	:	:	PUNCT
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cana-2726	170	41	-	-	PUNCT
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cana-2726	170	45	review	review	NOUN
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cana-2726	173	2	.	.	PUNCT
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cana-2726	174	2	obs	obs	PROPN
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cana-2726	176	2	13	13	NUM
cana-2726	176	3	]	]	PUNCT
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cana-2726	176	14	deep	deep	ADJ
cana-2726	176	15	learning	learning	NOUN
cana-2726	176	16	approach	approach	NOUN
cana-2726	176	17	for	for	ADP
cana-2726	176	18	hyperspectral	hyperspectral	ADJ
cana-2726	176	19	image	image	NOUN
cana-2726	176	20	classification	classification	NOUN
cana-2726	176	21	based	base	VERB
cana-2726	176	22	on	on	ADP
cana-2726	176	23	multifeature	multifeature	NOUN
cana-2726	176	24	local	local	ADJ
cana-2726	176	25	kernel	kernel	NOUN
cana-2726	176	26	descriptors	descriptor	NOUN
cana-2726	176	27	.	.	PUNCT
cana-2726	177	1	adv	adv	PROPN
cana-2726	177	2	.	.	PUNCT
cana-2726	177	3	space	space	NOUN
cana-2726	177	4	res	re	NOUN
cana-2726	177	5	.	.	PUNCT
cana-2726	178	1	2023	2023	NUM
cana-2726	178	2	,	,	PUNCT
cana-2726	178	3	72	72	NUM
cana-2726	178	4	,	,	PUNCT
cana-2726	178	5	1703–1720	1703–1720	NUM
cana-2726	178	6	.	.	PUNCT
cana-2726	179	1	[	[	X
cana-2726	179	2	14	14	NUM
cana-2726	179	3	]	]	PUNCT
cana-2726	179	4	sharifi	sharifi	NOUN
cana-2726	179	5	,	,	PUNCT
cana-2726	179	6	o.	o.	PROPN
cana-2726	179	7	;	;	PUNCT
cana-2726	179	8	mokhtarzadeh	mokhtarzadeh	NOUN
cana-2726	179	9	,	,	PUNCT
cana-2726	179	10	m.	m.	NOUN
cana-2726	179	11	;	;	PUNCT
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cana-2726	179	15	b.	b.	PROPN
cana-2726	180	1	a	a	DET
cana-2726	180	2	new	new	ADJ
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cana-2726	180	4	learning	learning	NOUN
cana-2726	180	5	approach	approach	NOUN
cana-2726	180	6	for	for	ADP
cana-2726	180	7	classification	classification	NOUN
cana-2726	180	8	of	of	ADP
cana-2726	180	9	hyperspectral	hyperspectral	ADJ
cana-2726	180	10	images	image	NOUN
cana-2726	180	11	:	:	PUNCT
cana-2726	180	12	feature	feature	NOUN
cana-2726	180	13	and	and	CCONJ
cana-2726	180	14	decision	decision	NOUN
cana-2726	180	15	level	level	NOUN
cana-2726	180	16	fusion	fusion	NOUN
cana-2726	180	17	of	of	ADP
cana-2726	180	18	spectral	spectral	ADJ
cana-2726	180	19	and	and	CCONJ
cana-2726	180	20	spatial	spatial	ADJ
cana-2726	180	21	features	feature	NOUN
cana-2726	180	22	in	in	ADP
cana-2726	180	23	multiscale	multiscale	PROPN
cana-2726	180	24	cnn	cnn	PROPN
cana-2726	180	25	.	.	PUNCT
cana-2726	181	1	geocarto	geocarto	PROPN
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cana-2726	182	4	,	,	PUNCT
cana-2726	182	5	4208–4233	4208–4233	NUM
cana-2726	182	6	.	.	PUNCT
cana-2726	183	1	https://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensing/vol/215/suppl/c	https://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensing/vol/215/suppl/c	PROPN
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cana-2726	183	4	https://www.sciencedirect.com/journal/the-egyptian-journal-of-remote-sensing-and-space-sciences	https://www.sciencedirect.com/journal/the-egyptian-journal-of-remote-sensing-and-space-science	VERB
cana-2726	183	5	https://www.sciencedirect.com/journal/the-egyptian-journal-of-remote-sensing-and-space-sciences/vol/23/issue/2	https://www.sciencedirect.com/journal/the-egyptian-journal-of-remote-sensing-and-space-sciences/vol/23/issue/2	PROPN
cana-2726	183	6	https://jeas.springeropen.com/	https://jeas.springeropen.com/	PROPN
cana-2726	183	7	https://www.mdpi.com/journal/applsci	https://www.mdpi.com/journal/applsci	PROPN
cana-2726	183	8	https://www.mdpi.com/2076-3417/14	https://www.mdpi.com/2076-3417/14	PROPN
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