Título:	Avaliação de índices espectrais aplicados a série multitemporal TM/Landsat-5 para o mapeamento de fitofisionomias e pastagem em ambiente de cerrado.
Autoria:	PAULA, S. C. DE BAYMA, G. VICENTE, L. E. LOEBMANN, D. G. dos S. W. NOGUEIRA, S. F. ANDRADE, R. G.
Afiliação:	STELLA CARVALHO DE PAULA, BOLSISTA CNPM; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPM; LUIZ EDUARDO VICENTE, CNPM; DANIEL GOMES DOS SANTOS W LOEBMANN, CNPM; SANDRA FURLAN NOGUEIRA, CNPM; RICARDO GUIMARAES ANDRADE, CNPM.
Ano de publicação:	2013
Referência:	In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 16., 2013, Foz do Iguaçú. Anais... São José dos Campos: INPE, 2013.
Páginas:	p. 1790-1792.
Conteúdo:	Abstract: According to the 2006 Brazilian Agricultural Census, Brazil has over 102 million hectares of planted pastures, of which 90% are pastures in good conditions and 10% are degreded planted pasture. In Cerrado biome environments, the vegetation class known as Cerrado grassland (CG) is often used as pasture area, and is thus named a natural pasture area. Differentiating pasture areas in Cerrado environments becomes more difficult due to the similarities in floristic composition. Remote Sensing (SR) is therefore an important instrument for mappings and modelings, for the development of several satellites and the data they produce enabled accompanying changes in land use and land cover. This monitoring may be performed using temporal series of vegetation indices (IVs), for they accompany vegetation's phenological and seasonal changes. Thus, the objective of this work is to use IVs' temporal series to differentiate Wooded Cerrado (WC), Cerrado grassland, vegetation class used as natural pasture (PN), and planted pastures (PP) using images of the TM sensor onboard Landsat-5 satellite. For nine years (2003 to 2011) of TM/Landsat-5 images, EVI, NDVI, NDWI and SAVI IVs temporal series of the IVs were generated. In the rainy period, the EVI showed the best results to differentiate Woooded Cerrado (WC), natural pasture and planted pasture classes. For further classifications, we recommend t sophisticated, spectral classifiers, to take advantage of the whole spectroradiometric scope of the dataset.
Thesagro:	Sensoriamento Remoto
Palavras-chave:	Índices espectrais Sensoriamento remoto multitemporal
Tipo do material:	Artigo em anais e proceedings
Acesso:	openAccess
Aparece nas coleções:	Artigo em anais de congresso (CNPM)