Rethinking the relationship between ecological conservation and urban land development: a spatial–machine learning integration approach

Abstract

Rapid urbanization has increasingly constrained ecological potential within intensively developed urban areas. Conflicts between ecosystem conservation and land development are recognized as major obstacles to optimizing urban ecological conditions, significantly impacting urban ecosystem performance. To address these challenges, this study advances beyond single-perspective ecological analyses by explicitly examining the coupling between ecological protection and urban development. Taking Nanjing as a case study, it analyzes the correlations between ecosystem protection assessment and urban development indicators at the plot level. By integrating spatial correlation analysis and interpretable machine learning, the study identifies four relationship types between ecological potential capacity (EPC) and land development intensity (LDI) and reveals their heterogeneous spatial patterns across the urban landscape. The findings reveal multiple forms of synergies and trade-offs between EPC and LDI, including plots characterized by both high ecological potential and high land development intensity. Further analysis indicates that these relationship types are associated with distinct combinations of artificial and natural environmental features. In highly developed areas, EPC–LDI relationships are primarily distinguished by built-environment attributes, whereas in less developed contexts, natural environmental conditions and changes play a more prominent role. These findings highlight the context-dependent and nonlinear nature of ecological–development coupling within built-up areas. By linking EPC–LDI relationship types, spatial patterns, and environmental contexts, this study offers a novel, integrative perspective and a fine-scale quantitative framework for interpreting ecological–development interactions and supporting differentiated planning strategies, thereby promoting more resilient and livable urban development.