Data/hora: 20/06/2024 13:00:16

Biblioteca(s): 	Embrapa Territorial.	
Data corrente: 	02/03/2009	
Data da última atualização: 	25/08/2014	
Autoria: 	LU, D.; BATISTELLA, M.; MORAN, E.	
Afiliação: 	DENGSHENG LU, Indiana University; MATEUS BATISTELLA, CNPM; EMÍLIO MORAN, Indiana University.	
Título: 	Integration of landsat TM and SPOT HRG Images for vegetation change detection in the Brazilian Amazon.	
Ano de publicação: 	2008	
Fonte/Imprenta: 	Photogrammetric Engineering & Remote Sensing, v. 74, n. 4, p. 421-430, 2008.	
ISBN: 	0099-1112	
Idioma: 	Português	
Conteúdo: 	Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation chance trajectories. This research indicates promising vegetation change techniques especially for vegetation gain and loss, even if very limited reference data are available.	
Palavras-Chave: 	Brazilian Amazon; Image collection and preprocessing; Vegetation Chance Detection.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/107250/1/2283.pdf	
Registro original: 	Embrapa Territorial (CNPM)	
Exemplares: 	CNPM - (2283-1) - UPC - AP - PP - 08/065 - AP - 2008.065 - DIS