Geographic Information Systems for Urban and Town Planning: Applications, Analytical Approaches, Challenges and Future Perspectives

Geographic Information Systems (GIS) have evolved from digital mapping and spatial data management tools into analytical and decision-support environments for contemporary town planning. This review critically synthesizes 20 studies covering GIS applications in urban growth modelling, land-use planning, site suitability, transportation and accessibility, infrastructure planning, environmental management, disaster-risk assessment, development control, public participation, and integration with remote sensing, BIM, artificial intelligence and emerging digital technologies. The reviewed evidence indicates that the principal value of GIS in town planning lies in its ability to integrate heterogeneous spatial and attribute datasets, perform multi-criteria and network-based analysis, represent spatial relationships, visualize alternative development scenarios, and support monitoring and decision-making. However, the literature also shows recurring limitations associated with data quality, temporal updating, interoperability, model calibration and validation, technical capacity, institutional coordination, cost, privacy and unequal access to spatial information. A cross-study synthesis is used to organize GIS applications according to planning function, analytical method, decision stage and technology integration. The review identifies a transition from GIS as a mapping and inventory system toward an integrated planning-support ecosystem combining GIS with remote sensing, BIM, IoT, cloud platforms, 3D visualization and AI/ML. Based on the synthesis, a conceptual GIS-enabled town-planning framework is proposed, linking data acquisition and quality assurance with spatial analysis, scenario modelling, stakeholder participation, decision support and continuous monitoring. The review concludes that future research should prioritize interoperable and continuously updated spatial infrastructures, transparent multi-criteria modelling, validated predictive approaches, human-centred participatory interfaces and integrated GIS–RS–BIM–AI environments.