ABSTRACT
This research analyzes land use and land cover dynamics in Joinville through remote sensing images. The methodology consists of three main steps: defining the study area, acquiring and processing images and spatial data, and reclassifying the images using a geographic information system. The images used are from the Landsat series, specifically Collection 8.0 of the MapBiomas Project, covering the period from 1985 to 2022. These images represent five primary classes: forest, non-forest natural formation, agricultural land, non-vegetated areas, and water bodies. The results indicate land use and land cover change rates ranging from 5 to 167% for increases, and from 5 to 53% for decreases. In conclusion, the approach presented significantly contributes to generating territorial indicators, which are important resources for territorial planning and management.