Construction and Optimization of Ecological Security Pattern in Kunming: Insights From Machine Learning Algorithms and Circuit Theory

ABSTRACT Constructing and optimizing an ecological security pattern (ESP) is a critical approach to safeguarding ecosystem health and promoting sustainable development, particularly in rapidly developing cities. However, traditional research methods often fail to accurately and effectively construct complex and dynamic ESPs. This limitation poses considerable challenges to the formulation of ecological restoration strategies and the maintenance of ecosystem stability. To address these challenges, the present study innovatively introduces an integrated methodological framework that combines the remote sensing ecological index (RSEI), morphological spatial pattern analysis (MSPA), landscape connectivity index (LCI), machine learning algorithms and circuit theory to construct the ESP of Kunming from 2000 to 2021. The framework is centered on the three elements ‘ecological source’, ‘ecological corridor’ and ‘ecological pinch point’, and further proposes targeted optimization strategies. Results demonstrate the substantial applicability and advantages of machine learning algorithms in ESP construction, and the XGBoost model emerging as the most effective approach for developing ecological resistance surfaces. Between 2000 and 2021, Kunming's ecological source area expanded from 882.90 to 1424.87 km 2 , forming a spatial pattern characterized by clustered distributions in the west and north and scattered distribution in the east. The total length of ecological corridors increased from 1141.28 to 1553.98 km, the number of connected corridors from 39 to 72 and ecological pinch points from 22 to 26. These changes have effectively mitigated ecological fragmentation, facilitated species migration and supported habitat restoration. Additionally, the number of ecological barriers grew from 21 to 31, particularly in the vicinity of Dianchi Lake. Given the obstructive impact of urbanization on the ecological network in this region, enhanced ecological protection and measures to restore network connectivity are imperative. Based on these findings, an optimized ESP framework, referred to as the ‘four zones and three belts’ model, was developed for Kunming city. This framework provides valuable theoretical and methodological insights for the construction and optimization of ESP in urban contexts.

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Publication Details

Journal
Land Degradation and Development
Published
2025-11-24
DOI
https://doi.org/10.1002/ldr.70330
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
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article

Construction and Optimization of Ecological Security Pattern in Kunming: Insights From Machine Learning Algorithms and Circuit Theory

Yutong Li, Lin Zhang, Shi Qi, K. Wei
Land Degradation and Development
Land Use and Ecosystem Services
article

Construction and Optimization of Ecological Security Pattern in Kunming: Insights From Machine Learning Algorithms and Circuit Theory

Yutong Li, Lin Zhang, Shi Qi, K. Wei
article en

Abstract

ABSTRACT Constructing and optimizing an ecological security pattern (ESP) is a critical approach to safeguarding ecosystem health and promoting sustainable development, particularly in rapidly developing cities. However, traditional research methods often fail to accurately and effectively construct complex and dynamic ESPs. This limitation poses considerable challenges to the formulation of ecological restoration strategies and the maintenance of ecosystem stability. To address these challenges, the present study innovatively introduces an integrated methodological framework that combines the remote sensing ecological index (RSEI), morphological spatial pattern analysis (MSPA), landscape connectivity index (LCI), machine learning algorithms and circuit theory to construct the ESP of Kunming from 2000 to 2021. The framework is centered on the three elements ‘ecological source’, ‘ecological corridor’ and ‘ecological pinch point’, and further proposes targeted optimization strategies. Results demonstrate the substantial applicability and advantages of machine learning algorithms in ESP construction, and the XGBoost model emerging as the most effective approach for developing ecological resistance surfaces. Between 2000 and 2021, Kunming's ecological source area expanded from 882.90 to 1424.87 km 2 , forming a spatial pattern characterized by clustered distributions in the west and north and scattered distribution in the east. The total length of ecological corridors increased from 1141.28 to 1553.98 km, the number of connected corridors from 39 to 72 and ecological pinch points from 22 to 26. These changes have effectively mitigated ecological fragmentation, facilitated species migration and supported habitat restoration. Additionally, the number of ecological barriers grew from 21 to 31, particularly in the vicinity of Dianchi Lake. Given the obstructive impact of urbanization on the ecological network in this region, enhanced ecological protection and measures to restore network connectivity are imperative. Based on these findings, an optimized ESP framework, referred to as the ‘four zones and three belts’ model, was developed for Kunming city. This framework provides valuable theoretical and methodological insights for the construction and optimization of ESP in urban contexts.

Land Degradation and Development
Beijing Forestry University (CN), Institute of Soil and Water Conservation (CN), Shanghai Hospital Development Center (CN), Shanghai Nanotechnology Promotion Center (CN)
Openalex Percentile: Top 66%
Land Use and Ecosystem Services
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