%0 Conference Proceedings
%4 dpi.inpe.br/sbsr@80/2008/11.13.09.28
%2 dpi.inpe.br/sbsr@80/2008/11.13.09.28.08
%@isbn 978-85-17-00044-7
%T Análise sazonal da qualidade e abrangência de imagens MODIS índice de vegetação para o bioma Cerrado
%D 2009
%A Ferreira Junior, Laerte Guimarães,
%A Rocha, Joana Carolina Silva,
%A Pontes, Marlon Nemayer Celestino de,
%A Araújo, Fernando Moreira de,
%@affiliation Universidade Federal de Goias
%@affiliation Universidade Federal de Goias
%@affiliation Universidade Federal de Goias
%@affiliation Universidade Federal de Goias
%@electronicmailaddress laerte@iesa.ufg.br
%@electronicmailaddress joana@geografia.grad.ufg.br
%@electronicmailaddress marlon@geografia.posgrad.ufg.br
%@electronicmailaddress fernando@geografia.grad.ufg.br
%E Epiphanio, José Carlos Neves,
%E Galvão, Lênio Soares,
%B Simpósio Brasileiro de Sensoriamento Remoto, 14 (SBSR)
%C Natal
%8 25-30 abr. 2009
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 1347-1352
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K Cerrado, séries temporais MOD13Q1, monitoramento de desmatamentos, Cerrado, MOD13Q1 time series, deforestation monitoring.
%X The Cerrado biome, strategically situated in the Brazilian Central Plateau and widely and heterogeneously spread along a variety of latitudes, longitudes and altitudes, is the richest savanna in the world and a major contributor to some of the largest and most important watershed basins in South America. On the other hand, the Cerrado is the most severely threatened biome in Brazil, with more than 40% of its original area already converted to agricultural crops and cultivated pastures. In this study, which is part of a larger effort aiming at the monitoring of the Cerrado vegetative cover, we evaluated the effective availability of moderate spatial resolution remote sensing data for the 2001 - 2007 period. The analysis of the 16 day composited MOD13Q1 (vegetation indices) product indicated that only data from April to September is capable of covering more than 80% of the biome remnant vegetation. Depending on the frequency at which the biome is to be monitored, alternatives to this critical data gap may include spatial and temporal interpolation (e.g. via algorithms like Timesat or frequency domain transformations), as well as the combined use of optical and SAR imagery.
%9 Análise e Aplicação de Imagens Multitemporais
%@language pt
%3 1347-1352.pdf