OICC Press Iranian Journal of Earth Sciences 2228-785X 17 1 2025 01 10 Landslide Susceptibility Mapping (LSM) of the Boudinar Basin (Morocco) using the Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP) method 1 10 10.57647/j.ijes.2025.1701.03 EN Morad Taher Applied Geosciences and Geological Engineering Research Team, FSTH, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0002-9273-2764 Mourabit Taoufik Department of Geology, Faculty of Science, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0002-5542-7074 Hajar El Talibi Applied Geosciences and Geological Engineering Research Team, FSTH, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0001-7549-6264 Afaf Amine Geosciences, water and Environment Laboratory, Department of Geology, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco https://orcid.org/0000-0002-9304-3987 Abdelhak Bourjila Laboratory of Engineering Sciences and Applications (LSIA), Materials Science, Energy and Environment (SM2E), ENSAH, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0003-2592-6179 Ali Errahmouni Department of Geology, Faculty of Science, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0003-2592-6179 Sadik Azzouzi Department of Geography, The Faculty of Letters and Human Sciences of Oujda, Mohammed first University, Oujda, Morocco https://orcid.org/0000-0002-3110-4262 Issam Etebaai Applied Geosciences and Geological Engineering Research Team, FSTH, Abdelmalek Essaˆadi University, Tetouan, Morocco https://orcid.org/0000-0001-5941-656X Journal Article 2025 01 10 Creating a landslide susceptibility map for the Boudinar basin is of paramount significance due to the region's susceptibility to landslides, which pose considerable risks to both human settlements and the environment. By integrating Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP), our study aims to address this challenge. These methods provide distinct advantages, as they facilitate spatial analysis and enable a thorough evaluation of the various factors contributing to landslide susceptibility. Therefore, various factors were considered in the study, including rainfall, lithology, slope, aspect, NDVI, distance from the fault, distance from the river, distance from the road, and elevation. The causative factors were divided into sub-factors, and weightages were assigned based on the AHP methodology. The resulting landslide susceptibility map was classified into three categories: low (5 %, 18 km2), moderate (69 %, 242 km2), and high (25 %, 88 km2). Nevertheless, the primary sources of uncertainty of our analysis include data quality, and the absence of field landslide inventory data for the validation process. Using Google Earth pro, the landslide inventory, consisting of 100 landslides, was used to validate the landslide susceptibility map, which had a prediction rate of 65.7% using the area under curve (AUC) technique. The LSM study is a valuable tool for construction planners and decision-makers. Therefore, by identifying high-risk areas, it aids in better preparedness and risk reduction efforts. Its integration into the planning process can significantly enhance the region's resilience to landslide hazards.