Integrating ecological security assessment and problem area identification: Simulated annealing and multi-model fusion

Abstract

Accurately identifying ecological problem areas is crucial to prevent the expansion and exacerbation of ecological issues. However, existing methods for ecological security assessment and ecological problem identification struggle to precisely delineate ecological problem areas. This study comprehensively utilized a projection pursuit model optimized by simulated annealing, an obstacle degree model, and parameter-optimized geo-detectors to integrate and define ecological problem areas in the Chengdu Plain region. The research findings indicate: (1) The projection pursuit model optimized by simulated annealing increased the verification accuracy of ecological security assessment to 79.48%. (2) After approximately 2000 iterations, the model achieved the optimal balance between time cost and efficiency in precision enhancement. (3) The Chengdu Plain region, on the whole, is in a relatively secure ecological state. The ecological security level is closely related to topography, economic conditions, and urban-rural disparities. (4) The primary ecological issue in this area is environmental pollution, while ecological degradation is mainly associated with new urban development and urban expansion. (5) Relevant authorities should pay special attention to pollution emissions in urban built-up areas and take preventive measures against potential ecological degradation caused by new urban development.

Keywords

• Simulated annealing algorithm (SA)
• Projection tracing model
• Obstacle degree model
• The Most Appropriate Unit of Planning (MAUP)
• Ecological problem area