%0 Conference Proceedings
%4 sid.inpe.br/mtc-m18/2010/09.27.17.01
%2 sid.inpe.br/mtc-m18/2010/09.27.17.01.33
%T Gradient Pattern Analysis Applied to Multitemporal Land Cover Change Detection
%D 2010
%A Freitas, Ramon Morais de,
%A Rosa, Reinaldo Roberto,
%A Shimabukuro, Yosio Edemir,
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%E Rodrigues, Rita de Cássia Meneses,
%E Almeida, Wesley Gomes de,
%E Assis, Talita Oliveira,
%E Chalhoub, Ezzat Selim,
%E Cortivo, Fábio Dall,
%E França, Luis Fernando Amorim,
%E Macau, Elbert Einstein Nehrer,
%E Oliveira, Rudinei Martins de,
%E Pillat, Valdir Gil,
%E Santos, Laurita dos,
%E Serpa, Dalila Ribeiro,
%E Silva, José Demisio Simões da,
%E Silva, Marlon da,
%B Workshop dos Cursos de Computação Aplicada do INPE, 10 (WORCAP).
%C São José dos Campos
%8 20 e 21 out. 2010
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K Gradient Pattern Analysis, Amazonia, deforestation.
%X In this work, the Gradient Pattern Analysis - GPA was applied for the first time in MODIS spatial-temporal images over the Amazon region. The study area is a Large Scale Biosphere-Atmosphere Experiment in Amazonia LBA study site located in the Pará State, eastern Brazilian Amazonia. Using remote sensing images derived from MODIS - MOD09 8-day composite product from 2000 to 2009 was elaborated the EVI2 spatial-temporal series of the study area. For each pixel we performed smooth time-series applying wavelets transform method for noise reduction. The GPA objective was characterizing small symmetry breaking, amplitude and phase disorder due to spatial-temporal fluctuations driven by the deforestation and flooded changes detected by MODIS images. For the characterization of spatial-temporal series the Gradient Pattern Analysis showed a new approach to understand LULC changes directly in the remote sensing images.
%9 Tecnologia da informação e extração de informações
%@language en
%3 ramon78921_final.pdf