Revealing the trade-offs, synergies, and driving mechanisms among land use functions is essential for mitigating conflicts between functions, optimizing territorial spatial patterns, and providing policy support for regional sustainable development. Taking the Central Yunnan Urban Agglomeration as a case study, this study adopts a grid-based evaluation unit and employs a multi-model fusion approach to systematically analyze the interaction mechanisms among land use functions. By integrating the Pearson correlation method and root mean square deviation (RMSD) model, the trade-off and synergy relationships and their spatiotemporal evolution were quantitatively assessed. The XGBoost–SHAP model and optimized parameter-based geographical detector (OPGD) were introduced to identify the nonlinear characteristics and interaction effects of influencing factors on land use function trade-offs and synergies. In addition, a geographically weighted regression (GWR) model was used to explore spatial heterogeneity in these effects. The results indicate that (1) from 2010 to 2020, the overall synergy between production and ecological functions (PF (2) the dominant factors influencing land use function trade-offs and synergies include precipitation, slope, land use intensity, elevation, NDVI, Shannon diversity index (SHDI), distance to county centers, and distance to expressways; (3) these dominant factors exhibit strong nonlinear effects and significant threshold responses in shaping trade-offs and synergies among land use functions; and that (4) compared with the OLS model, the GWR model demonstrated higher fitting accuracy. This reveals that the impacts of natural, socio-economic, and landscape pattern factors on land use function interactions are characterized by pronounced spatial heterogeneity.
Ma et al. (Fri,) studied this question.
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