%0 Conference Proceedings
%4 dpi.inpe.br/sbsr@80/2008/11.17.20.40
%2 dpi.inpe.br/sbsr@80/2008/11.17.20.40.25
%@isbn 978-85-17-00044-7
%T Um método para analisar a distribuição espacial das áreas de vegetação secundária em áreas desflorestadas na Amazônia
%D 2009
%A Mello, Allan Yu Iwama de,
%A Alves, Diógenes Salas,
%@affiliation Instituto Nacional de Pesquisas Espaciais - INPE
%@affiliation Instituto Nacional de Pesquisas Espaciais - INPE
%@electronicmailaddress allan@dsr.inpe.br
%@electronicmailaddress dalves@dpi.inpe.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 5981-5988
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K deforestation, secondary vegetation, landscape fragmentation, desflorestamento, vegetação secundária, fragmentação da paisagem.
%X Deforestation in Brazilian Amazon is concentrated in some areas where the landscape tends to be dominated by pastures and partially by crops, with relatively few forest remnants, and some degree of secondary vegetation. Secondary vegetation can play an important role to mitigate deforestation impacts, although it has been suggested that it has decreasing importance in regions that concentrate most deforestation, according to studies based on analyses of Census data and classification of variable-sized sampling units based on remotely sensed imagery. The aim of this work is to define a method to analyze the spatial distribution of secondary vegetation based on the classification of randomly selected 10x10 km regular cells, and differentiating areas deforested before 1997 (old deforestation) from areas deforested after 2003 (new deforestation). Maps from INPE PRODES program were used as the source of deforestation data and Landsat TM imagery were classified to identify secondary vegetation in areas of old and new deforestation, in the randomly selected cells. Restricting classification to the randomly selected cells reduces the total classification time, contributes to better classification results by focusing on specific contexts, and can be used as the basis to differentiating secondary vegetation distribution according to both deforestation periods and visually-inferred landscape patterns.
%9 Mudança de Uso e Cobertura da Terra
%@language pt
%3 5981-5988.pdf