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    A Change Detection Methodology for the Amazon Forest Using Multitemporal NOAA/AVHRR Data and GIS—Preliminary Results

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    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 μm) 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.


    Amazon, AVHRR images, deforestation, GIS, remote sensing

    Author Information:

    Di Maio Mantovani, AC
    Research Engineer and Assistant Professor, Laboratory of Geoprocessing, Universidade do Vale do Paraíba, S. J. Campos, SP

    Setzer, AW
    Scientist, Instituto Nacional de Pesquisas Espaciais—INPE/DSR, S. J. Campos, SP

    Committee/Subcommittee: D18.01

    DOI: 10.1520/STP18251S