%0 Audiovisual Material
%4 sid.inpe.br/mtc-m21b/2017/09.29.17.25
%2 sid.inpe.br/mtc-m21b/2017/09.29.17.25.22
%T Environmental Monitoring in Brazil: Contributions of INPE in research, development and applications
%D 2017
%P 67
%A Namikawa, Laercio Massaru,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress laercio.namikawa@inpe.br
%B Semana Geomática Internacional, 7
%C Bogotá, Colômbia
%8 14-18 ago.
%I Instituto Nacional de Pesquisas Espaciais
%J São José dos Campos
%X INPE is the leading agency in Brazil for research, development and application of geotechnologies, and given that main national issues are related to the environment, there are many initiatives at INPE for Environmental Monitoring using Remote Sensing Images. These initiatives include operational systems, such as Programa Queimadas (Forest Fires Program) and Projeto PRODES (PRODES Project). These examples use satellite data from meteorological and remote sensing orbital platforms to release to experts, organizations, governments and general public, information in a easy consumption way. In addition, INPE researches and develops techniques and tools to manage, extract and share geoinformation. For environmental monitoring, research focus on change detection and the developed techniques are implemented in specialized platform to be used in operational way. To support the implementation of these platforms, INPE has been developing GIS and Image Processing software, with TerraLib being the current technology. The flexibility and extensive scope of TerraLib has allowed INPE to provide a platform to implement operational early warning systems based on automatically gathering dynamic data, processing this data with risk maps, and issue early warnings. The current version of this platform is called TerraMA2 Version 4.0, which is in Beta release phase. The experience at INPE at these two fronts indicates that future systems should integrate the automatic data gathering, analysis and early warning issuing with remote sensing images. To achieve this goal, some automatic change detection techniques were tested and are presented here, including index and color analysis. In addition, the possibility of using different sensors from different satellites is analyzed for a multi-scale and multi-representation change detection.
%@language pt
%3 Namikawa_Semana_Geoma?tica_BOA.pdf