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Data source downloaded from MODIS: https://earthexplorer.usgs.govKansas Biological Survey / Kansas Applied Remote Sensing ProgramAgricultureAmazonBrazilCerradoCottonDeforestationLand Cover MappingIntensificationLand Use ChangeMato GrossoMODISNDVIRemote SensingSoybeansSugarcane<DIV STYLE="text-align:Left;"><DIV><P><SPAN>The Kansas Biological Survey (KBS) and its representatives make no warranty or representation, either expressed or implied, with respect to the digital data and their documentation, their quality, performance, merchantability, or fitness for a particular purpose. The digital data are distributed on "as is" basis, and the user assumes all risk as to their quality, the results obtained from their use, and the performance of the data. In no event will the KBS or its representatives be liable for any direct, indirect, special, incidental or consequential damages resulting from and defect in the KBS's digital data or in their documentation. This disclaimer of warranty is exclusive and in lieu of all others, oral or written, expressed or implied. No agent or employee is authorized to make any modification, extension, or addition to this warranty.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><P><SPAN>Normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to characterize the spatial dynamics of agriculture in the state of Mato Grosso (MT), Brazil. With these data, it has become possible to track MT agriculture, which accounts for ~85% of Brazilian Amazon soy production. To interpret the satellite data, researchers from Empresa Brasileira de Pesquisa Agropecuária(Embrapa), the Brazilian equivalent of the USDA, collected an unprecedented amount of ground reference data in Mato Grosso by interviewing farmers, tracing field boundaries on printed satellite imagery and obtaining cropping histories for various parcels of land. This unique, spatially extensive 9-year (2005-2013) ground reference dataset was used to classify, with approximately 80% accuracy, the MODIS NDVI data. The results were merged with carefully processed annual forest and sugarcane coverages developed by Brazil's National Institute for Space Research (INPE) to produce land cover maps for MT for the 2001-2014 crop years, where a crop year runs from August of the preceding year through July of the nominal year. Static urban and water layers, obtained from the Brazilian Institute of Geography and Statistics (IBGE), round out the land cover maps.</SPAN></P></DIV></DIV>Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.4.1.56861-61.837150-49.921177-7.291091-18.1684955527240.0000005181240.000000210-6883680.000000 -2057280.000000-6883680.000000 -813840.000000-5557200.000000 -813840.000000-5557200.000000 -2057280.000000-6220440.000000 -1435560.000000Layer_19.0000001.00000082002_final_wgs84.img.vatTable9OIDOIDOID400Internal feature number.EsriSequential unique whole numbers that are automatically generated.ValueValueInteger10100CountCountDouble1900Raster DatasetdatasetEPSG8.8(9.3.1.2)20220407/9j/4AAQSkZJRgABAgEAYABgAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a
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