Traditional assessment tools fail to account for complex spatiotemporal correlations and external volatility. Improving predictive accuracy reduces financial risk and resource misallocation in urban planning.

Fragmented and manual monitoring leads to undetected idle land and reclamation non-compliance. Automated detection prevents resource waste and regulatory oversight failures.

Fragmented planning data and scale mismatches prevent coherent land resource allocation. Resolving these inconsistencies ensures ecological resilience and prevents conflicting land-use designations.