2024-12-172024-12-172024-09-10https://repositorio.ifal.edu.br/handle/123456789/816The present study uses geoprocessing and remote sensing technologies to identify changes in land use and cover in the reference years (1992, 2002, 2012 and 2022) in Murici, Alagoas. The methodology used involves downloading images referring to land use and land cover maps in Google Earth Engine (GEE), through the MapBiomas tool, in its 8.0 collection, which uses annual mosaics of Landsat images based on predefined periods (collections) with spatial resolution of 30m x 30m for supervised classification of multispectral images. Using the Semi-Automatic Plugin (SCP) add-on to QGIS 3.26, each land use and land cover map was subjected to post-processing using the "Cross Classification" tool, allowing mapping and area calculation of use classes and soil cover, as well as transition data between classes, making it possible to ascertain the balance of gains and losses from one class to another between the decades analyzed. Between 1992 and 2022, a significant reduction in forest and savanna areas was identified, possibly driven by the expansion of agricultural activities. At the same time, urbanization has expressed progressive growth, which results in the reduction of other classes of use and coverage and can drive waterproofing, soil degradation and changes in water bodies. It is imperative, therefore, to adopt public policies that reconcile environmental conservation with local needs.ptCC0 1.0 UniversalGeoprocessamentoSensoriamento remotoMapbiomasAgriculturaGeoprocessingRemote sensingMapbiomesAgricultureTrabalho de Conclusão de CursoCIENCIAS AGRARIAS