%0 Conference Proceedings
%4 dpi.inpe.br/marte2/2013/05.28.23.09.40
%2 dpi.inpe.br/marte2/2013/05.28.23.09.41
%@isbn 978-85-17-00066-9 (Internet)
%@isbn 978-85-17-00065-2 (DVD)
%F 235
%T Análise do uso e cobertura da terra de uma microbacia hidrográfica do Rio Fortaleza, no norte do RS
%D 2013
%A Rosa, Paulo Afonso da,
%A Gallio, Ezequiel,
%A Breunig, Fábio Marcelo,
%A Balbinot, Rafaelo,
%@electronicmailaddress paulo-darosa@hotmail.com
%E Epiphanio, José Carlos Neves,
%E Galvão, Lênio Soares,
%B Simpósio Brasileiro de Sensoriamento Remoto, 16 (SBSR)
%C Foz do Iguaçu
%8 13-18 abr. 2013
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 7631-7638
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The knowledge of changes occurring in the environment is important to reduce environmental impacts and to define planning strategies. Thinking about it, the purpose of this study was to evaluate land use changes in three different dates (1985, 1996, 2010) in a small watershed. For this were used the software SPRING, provided by the Brazilian National Institute for Space Research (INPE). Landsat 5 Thematic Mapper (TM) sensor imagens were geometrically corrected using Geocover 2000 orthorectified data base, with a RMSE up to 1. Land cover was performed by two approaches: manual image interpretation and supervised maximum likelihood (MAXVER) image classification. Land cover was classified in four classes: agricultural fields, forest, shadow and water. Both classification methods showed the predominance of agricultural land use with values up to 50.5% and 55.3% according the manual image interpretation and MAXVER classification of 2010 TM image, respectively. By analyzing forest coverage from 1985 to 2010 the methods lead to little different tendencies. According to manual image interpretation, forest present a monotonically increase from 1985 to 2010 (31.3%; 36.6% to 47.6% for 1985, 1996 and 2010, respectively) while MAXVER indicated a forest coverage decrease from 1985 to 1996 (29.1% to 25.5%) and an increase from 1996 to 2010 (25.5% to 37.9%). These results highlight the importance to take care in using automatic or semiautomatic image classifications to generate products and tendencies. Furthermore, both classifiers showed deficiency to mapping riparian vegetation. New studies are required to validate the present results.
%9 Mudança de Uso e Cobertura da Terra
%@language pt
%3 p0235.pdf