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Identifying irrigation areas with satellite images is a challenge that finds great potential in cloud computing solutions through the Google Earth Engine (GEE) tool, which facilitates the process of searching, filtering and manipulating large volumes of data. remote sensing without the need for paid software or image downloading. The present paper evaluated the automation of the supervised classification of irrigated areas in the region of Sorriso and Lucas do Rio Verde / MT with the CART algorithm in the GEE environment using bands 1-7 of the Landsat-8 satellite together with the NDVI, NDWI and SAVI indices. The NDWI index was the main distinguishing factor between irrigated and non-irrigated areas. The accuracy of supervised classification was 99.4%. The developed source code is avaliable in the appendix.

CLASSIFICAÇÃO SUPERVISIONADA DE ÁREA IRRIGADA UTILIZANDO ÍNDICES ESPECTRAIS DE IMAGENS LANDSAT-8 COM GOOGLE EARTH ENGINE