Land-use land-cover change analysis using remote sensing and geographic information systems in northen Rif, Morocco.

Abstract

Land use and land cover (LULC) maps play a crucial role in guiding planning and management efforts, this study present consideration of regarding trend analysis in the land use and land cover of the Al Hoceima in the northern-central Rif region over a span of 25 years, from 2000 to 2025. For this purpose, a series of Landsat images, namely an Enhanced Thematic Mapper Plus (ETM+) image from 2000, Landsat 8 operational land imager (OLI) image from 2014, and a Landsat 9 Operational Land Imager (OLI) image from 2025 were obtained and processed using GIS and RS Software tools. Supervised classification with the maximum likelihood (ML) algorithm was applied to generate LULC maps. 120 ground truth points for each classified image were used to conduct accuracy evaluations, with overall accuracy ranging from 87.5% to 90.8% and Kappa coefficient ranging from 0.82 to 0.87. In order to examine and analyze the changes in LULC, we conducted a post-classification comparison. The findings revealed clear trends of decreasing in forests and dense vegetation areas at the expense of other classes. Additionally, there was a slight increase in the built-up area, which is likely driven by population growth and rising economic activity.