Geoinformation-Based Simulation of Policy-Oriented Land-Use Scenarios for SDG-Oriented Spatial Planning in a Resource-Depleted City: Evidence from Huangshi, China

Rapid urban development has intensified conflicts between land development and ecological conservation, making spatially explicit land-use planning increasingly important for resource-depleted cities. This study develops a geoinformation-based decision-support framework for Huangshi, China, by integrating multi-scenario land-use modeling, production–living–ecological space analysis, landscape pattern assessment, and SDG 15 diagnostics. Four 2035 policy-oriented scenarios were compared: Business-as-Usual (BAU), Ecological Restoration Priority (ERP), Economic Development Priority (EDP), and Sustainable Development (SD). The results show that ERP delivers the strongest ecological performance, with ecological space reaching 46.47%, forest cover increasing from 35.40% to 36.80%, water area rising to 9.65%, net land degradation declining to −2.04%, and mean habitat quality reaching 0.484. SD provides a more balanced pathway, with ecological space of 44.80%, living space of 8.93%, a land-use stability rate of 96.36%, and a relatively low net degradation rate of 1.33%. BAU and EDP show higher ecological risks. The framework demonstrates how multi-source geospatial data and spatially explicit SDG diagnostics can support adaptive planning in resource-depleted cities.