Spatio-Temporal Evolution and Policy Drivers of Land Resource Carrying Capacity in Xuchang City, Central China (2000–2020)

Understanding the dynamics of Land Resource Carrying Capacity (LRCC) under rapid urbanization requires not only retrospective assessment but also operational tools for supporting future planning. This study develops a spatially explicit LRCC framework for Xuchang City (2000–2020) that integrates economic, land-use, and resource subsystems, and encodes key policy instruments as time-varying variables. Entropy weighting is used as a data-driven baseline for indicator aggregation, with robustness checks conducted using equal weighting and the analytic hierarchy process (AHP). Results show that Xuchang’s citywide LRCC increased from 0.56 in 2000 to 0.81 in 2020, corresponding to a 44.6% rise over the study period. This growth exhibits marked spatial heterogeneity across the urban area and is closely associated with changes in urbanization level, industrial restructuring, and land development intensity. The overall pattern of LRCC change is robust to alternative weighting schemes, supporting the comparability of the estimates across time. To explore potential futures, a scenario-based simulation is conducted in which a +2% increase in urbanization rate and a −10% reduction in land development intensity are translated into LRCC responses, yielding a predicted increase of about +0.023 (from 0.81 to approximately 0.833). This scenario illustrates how the framework can be used to evaluate trade-offs and synergies among development and conservation objectives. By quantifying the contributions of policy-related and socio-economic indicators to LRCC dynamics, the study provides an evidence-based tool for optimizing land governance and promoting sustainable urban development in rapidly urbanizing regions.