%0 Conference Proceedings
%4 sid.inpe.br/iris@1912/2005/07.20.04.53.43
%2 sid.inpe.br/iris@1912/2005/07.20.04.54
%@issn 00660558
%F 7807
%T A change detection methodology for the Amazon Forest using multitemporal NOAA/AVHRR data and GIS-preliminary results
%D 1996
%A Mantovani, Angelica C. Di Maio,
%A Setzer, Alberto Waingort,
%@affiliation UNIVAP
%B International Symposium on Remote Sensing and GIS for Site Characterization, Aplications and Standards.
%C San Francisco, USA
%8 27-28 Jan. 1994
%I American Society for Testing and Materials
%P 43-46
%K Database systems, Digital signal processing, Forestry, Geographic information systems, Image processing, Mapping, Radiometers, Satellites, Advanced very high resolution radiometer, Amazon tropical forest, Change detection methodology, Deforestation, Satellite images, Remote sensing.
%X This paper describes initial results of a methodology developed to locate new deforestation in the Amazon Tropical forest. It combines automatic classification of the Advanced Very High Resolution Radiometer (NOAA/AVHRR)satellite images and a Geographic Information System (GIS)data base. Full resolution and geometrically corrected AVHRR channel 3 (3.7 m)images of different dates of the Amazon region are automatically compared in digital form. Places where changes in the original cover of the vegetation are detected between any two different images have their locations determined through a GIS. Initial tests in the north of the state of Mato Grosso, Brazil, are presented indicating the possibility of using AVHRR imagery operationally to detect new deforestation. Results comparing deforestation in the AVHRR channel 3 with corresponding high resolution LANDSAT-Thematic Mapper (TM)images indicated 56.5 of AVHRR correct location for 221 polygons of deforestation with different sizes. 90 of correct locations was obtained for the 50 TM polygons with deforestation greater than 3.1 Km2.
%@language en
%3 INPE 6440.pdf