SPATIOTEMPORAL ANALYSIS OF LAND USE AND LAND COVER USING REMOTE SENSING

Abstract

Land use and land cover (LULC) changes, essential to understanding environmental dynamics under human influence, are significantly intensified by the agricultural sector. This study aims to characterize and analyze spatiotemporal changes in an area primarily influenced by agricultural activities, using geoprocessing and remote sensing. The methodology involved acquiring satellite images from the wet and dry seasons of 1990, 2000, 2010, 2020, and 2023, then delineating and analyzing LULC classes. Among the analyzed periods, the most significant change was the shift from temporary crops to exposed soil, attributed to the fallow period. In contrast, forest areas, buildings, pastures, lagoons, transmission lines, motorways, and access roads underwent only minor alterations. Since 1990, pastures, forest cover, and temporary crops have been the most prevalent classes, totaling 735, 686, and 533 hectares, respectively, during the 2023 rainy season. In conclusion, the methods used here can be adapted to any region, and the resulting products provide essential tools for managers to devise strategies that enhance agricultural and environmental management.