%0 Conference Proceedings
%4 sid.inpe.br/mtc-m18/2011/10.18.01.44
%2 sid.inpe.br/mtc-m18/2011/10.18.01.44.49
%T An On-line Visualization Tool Using MODIS and TRMM Time-series for Land Use and Land Cover Studies at South America
%D 2011
%A Freitas, Ramon Morais De,
%A Shimabukuro, Yosio Edemir,
%A Rosa, Reinaldo Roberto,
%A Adami, Marcos,
%A Arai, Egidio,
%A Sato, Fernando Yuzo,
%A Souza, Arley Ferreira De,
%A Rudorff, Bernardo F. T.,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%E Castro, Ana Paula Abrantes de,
%E Drummond, Isabela Neves,
%E Sandri, Sandra Aparecida,
%B Workshop dos Cursos de Computação Aplicada do INPE, 11 (WORCAP).
%C São José dos Campos
%8 8-10 nov. 2011
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K MODIS, remote sensing, time-series visualization, virtual globe.
%X This work presents the development of a tool for visualization of time-series derived from remote sensing sensors. This work introduces the new concept of Virtual Laboratory of Remote Sensing Time Series to support Land Use and Land Cover - LULC Changes studies over large spatial temporal datasets. The MODIS (Moderate Resolution Imaging Spectroradiometer) and TRMM (Tropical Rainforest Measuring Mission) time-series are used to support applications on the environmental monitoring as deforestation detection. The Virtual Laboratory of Remote Sensing Time Series is composed by a dataset with more than 500 million EVI2 (Enhanced Vegetation Index 2) profiles for the entire South America continent based on a 11 years history of daily MODIS data acquisition. The original EVI2 time series was filtered using the Daubechies (Db8) orthogonal Discrete Wavelets Transform. The filtering procedure smoothes high frequencies that are associated with clouds cover and sensor noises. The EVI2 time series were integrated into the virtual globe using Google Maps and Google Visualization Application Programming Interface functionalities. For each call of a geographic coordinate from the virtual globe the EVI2 profiles are instantaneously recovered for visualization. The tool demonstrated to be useful for rapid LULC change analysis to environmental monitoring, at the pixel level, over large regions.
%@language en
%3 worcap2011_submission_18.pdf