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This research aims to optimize ecological security patterns by integrating supply and demand perspectives using machine learning.

July 15, 2026LandOpen Access

Optimizing Ecological Security Patterns from a Supply–Demand Perspective Using XGBoost and Ecological Network Theory

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Randomized trial assesses ecological security patterns in urban regions, highlighting essential optimization strategies.

This research aims to optimize ecological security patterns by integrating supply and demand perspectives using machine learning.
Developed an integrated framework combining XGBoost and ecological network theory
Assessed the ecological security patterns in the Chengdu–Chongqing Urban Agglomeration
Analyzed spatial patterns and evaluated network connectivity
Enhanced connectivity of the ecological network by 136.46% through targeted optimization
Improved supply-demand balance by 35.4% after implementing optimization strategies
Identified optimal configurations with 'three zones, four corridors, six nodes' scheme

Feng et al. (2026) studied this question.

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