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Sobre estos mosaicos se derivan índices espectrales (NDVI, NBR, NBR2, SAVI y MNDWI) que, junto con puntos de calor de los sensores MODIS y VIIRS, sirven como insumo para una clasificación supervisada mediante el algoritmo de machine learning Random Forest, delimitando los polígonos de cicatrices de quema.\nLa capa resultante se depura y valida en ArcGIS Pro, eliminando polígonos superpuestos con cicatrices mapeadas en meses anteriores, territorios artificializados y superficies de agua, y verificando la calidad temática y topológica (adyacencia entre polígonos y área mínima cartografiable). Posteriormente, las cicatrices se clasifican según el tipo de cobertura vegetal afectada mediante la intersección con la capa Bosque/No Bosque (SMByC\u2013IDEAM, 2024) y con el mapa de coberturas de la tierra del SIMCOBA para la Amazonía colombiana (Instituto SINCHI, 2024). Finalmente, se generan estadísticas de área quemada por Unidad Espacial de Referencia (UER) y los resultados se publican en el portal del Sistema de Información Ambiental Territorial de la Amazonia colombiana \u2013 SIATAC, para apoyar la gestión de monitoreo, prevención y control de las quemas en la región.", "copyrightText": "Instituto Amazónico de Investigaciones Científicas - SINCHI. 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