The Spatial Simulation of Urban Expansion in the Tal Afar City Using Artificial Intelligence and GIS (Iraqi National Journal of Earth Science (INJES), 2026)
Cities are rapidly expanding, often at the expense of agricultural land. Although urban areas occupy small spaces, their growth has led to significant changes and loss of a vital, fertile farmland national resource. This expansion is driven by a rising population, particularly in developing countries. The United Nations Organization predicts that by 2030, over 60% of the global population will live in cities, with 90% of this growth occurring in developing nations. This research addresses key questions: What are the future scenarios for urban expansion in Tal Afar, considering the land’s capacity? Do these scenarios vary within the city's urban area?. The study utilizes Geographic GIS to simulate future urban expansion in Tal Afar and identify potential scenarios until 2037. This is achieved using artificial intelligence through the Artificial Neural Networks (ANN) model within the GeoSOS software in GIS. The findings indicate that land cover classification helped in identifying urban expansion patterns in previous years. The ANN-CA simulation model projected an estimated urban land increase of about 22 km² by 2037. The scenarios suggest that expansion will primarily occur in highly suitable and suitable areas avoiding regions with low suitability.
Keywords: Urban Expansion, Spatial Simulation, Artificial Intelligence, GIS, Analytic Hierarchy Process (AHP), Tal Afar,