How can Artificial Intelligence (AI) and drones be effectively used along with GIS and RS techniques in locational and areal planning? (Answer in 250 words)

GIS integrates spatial layers, remote sensing (RS) observes land and environmental change, drones provide fine-resolution data, and AI detects patterns for faster, evidence-based planning.

Locational planning

• Multi-criteria AI models can identify sites for hospitals, schools, logistics hubs and renewable-energy parks using roads, population, hazards, land values and service gaps.
• Network analysis can optimise ambulance routes, public transport and waste collection.
• Drone imagery supports cadastral surveys, construction monitoring and infrastructure condition assessment.

Areal planning

• RS time series and machine learning map urban expansion, crop health, groundwater stress, wetlands, forest cover and flood zones.
• Digital elevation models support watershed planning, drainage design and landslide susceptibility mapping.
• AI-based change detection can identify encroachment, illegal mining and disaster damage for targeted enforcement.

Governance and limits

• Ground verification, interoperable standards and updated base maps are essential to avoid automated errors.
• Privacy, drone safety, data ownership and algorithmic bias require clear safeguards.
• Local knowledge and public consultation must complement technical models, especially where relocation or land acquisition is proposed.

Keywords: GIS, RS, spatial analysis, machine learning, digital elevation model, geospatial governance.