Smart Land Use Planning: Integrating Geographic Information Systems (GIS) with Graph Neural Networks (GNN) for Hazard Identification

This paper presents a novel approach to smart land use planning by integrating Geographic Information Systems (GIS) with Graph Neural Networks (GNN). The primary objectives are to conduct satellite imagery analysis for land use patterns, determine suitable zones for commercial and residential development, analyze vulnerability to natural hazards, develop a web-based platform for land use planning, and evaluate the methodology's performance on Indian cities. By leveraging the spatial analysis capabilities of GIS and the predictive power of GNN, we aim to enhance the efficiency and accuracy of urban planning processes.