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Description: The use of remote sensing images in the preparation and monitoring of land covers proved to be a very effective and successful technique for various types of land covers such as urban, water or urban cover… etc. The aim of this study is to prepare the land covers classification maps for the years 2016 and 2022 by using European Satellite Sentinel 2 images, for the two seasons (Spring and Autumn). The Anderson land cover classification system was adopted at the first level, using the supervised classification technique, the maximum probability method, and taking advantage of the integration between geographic information systems and remote sensing data. The error matrix was used to evaluate the accuracy of the land cover classification results. The results showed that the manner of the spatial distribution of the land cover classes during the years 2016 and 2022 is almost identical in terms of an increase in the area of vegetation and water cover during the spring season, and a decrease during the autumn season. In contrast to both the barren lands and the salty lands, which decrease during the spring and increase during the autumn season.