Evaluation of ecological geological environment carrying capacity and analysis of driving mechanisms based on normal cloud model and geodetector model

The Luoyang area of the Yellow River Basin, as a typical resource-based city, its special industrial structure and complex geological structure make the ecological and geological environment of the area extremely fragile. In order to realize the sustainable development of the region in this fragile ecological-geological environment, it is necessary to study its Ecological Geological Environmental Carrying Capacity (EGECC) to better serve the regional ecological-geological environment restoration and management work. This study constructs an indicator system encompassing three subsystems: Geological Environment (GE), Social Environment (SE), and Ecological Environment (EE). Based on game theory combination weighting (G1-IEW-GT) and the Normal Cloud model, the EGECC of Luoyang City from 2000 to 2022 was evaluated on a grid scale. Concurrently, a coupled model of geographic detectors and geographically weighted regression was established to recognize the spatial heterogeneity and driving mechanisms of the ecological geological environment system. The findings demonstrate that: (1) The overall EGECC in the Luoyang region of the YRB fluctuates upward, with the eastern area displaying more favorable conditions compared to the western region. (2) Over these twenty-two years, the geological environment system experienced initial deterioration followed by improvement, the ecological environment system remained relatively stable, and social and economic development continuously strengthened. (3) Landform types, elevation, human activity impact index, population density, and geological disaster susceptibility are the main driving elements for the assessment of the ecological geological environment system. Any pair of the 18 variables show varying degrees of enhancement effects on the EGECC. (4) The regression coefficients of the five major driving factors exhibit significant agglomeration characteristics in spatial distribution. Among them, geological disaster susceptibility has a negative driving effect on the EGECC, while landform, human activity impact index, and population density all display bidirectional effects. Overall, this study provides essential guidance for formulating ecological protection and restoration plans for the national territorial space in the Luoyang area of the YRB. Additionally, the evaluation methods established in this study have promotional value and can serve as a reference for the ecological geological spatial management of other resource-based cities.

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Publication Details

Journal
Scientific Reports
Published
2025-01-22
DOI
https://doi.org/10.1038/s41598-025-85761-1
Citations
7
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
22.72

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Evaluation of ecological geological environment carrying capacity and analysis of driving mechanisms based on normal cloud model and geodetector model

Yi Jia, Rongkun Dai, Xiujuan Liang, Weifei Yang et al.
7 citations
Scientific Reports
Advanced Decision-Making Techniques
22.72
article

Evaluation of ecological geological environment carrying capacity and analysis of driving mechanisms based on normal cloud model and geodetector model

Yi Jia, Rongkun Dai, Xiujuan Liang, Weifei Yang, Linzuo Zhang, Jiarui Yao, Jiang Zhang, Weifeng Li, Lin Jia, Changlai Xiao
article en
7 citations

Abstract

The Luoyang area of the Yellow River Basin, as a typical resource-based city, its special industrial structure and complex geological structure make the ecological and geological environment of the area extremely fragile. In order to realize the sustainable development of the region in this fragile ecological-geological environment, it is necessary to study its Ecological Geological Environmental Carrying Capacity (EGECC) to better serve the regional ecological-geological environment restoration and management work. This study constructs an indicator system encompassing three subsystems: Geological Environment (GE), Social Environment (SE), and Ecological Environment (EE). Based on game theory combination weighting (G1-IEW-GT) and the Normal Cloud model, the EGECC of Luoyang City from 2000 to 2022 was evaluated on a grid scale. Concurrently, a coupled model of geographic detectors and geographically weighted regression was established to recognize the spatial heterogeneity and driving mechanisms of the ecological geological environment system. The findings demonstrate that: (1) The overall EGECC in the Luoyang region of the YRB fluctuates upward, with the eastern area displaying more favorable conditions compared to the western region. (2) Over these twenty-two years, the geological environment system experienced initial deterioration followed by improvement, the ecological environment system remained relatively stable, and social and economic development continuously strengthened. (3) Landform types, elevation, human activity impact index, population density, and geological disaster susceptibility are the main driving elements for the assessment of the ecological geological environment system. Any pair of the 18 variables show varying degrees of enhancement effects on the EGECC. (4) The regression coefficients of the five major driving factors exhibit significant agglomeration characteristics in spatial distribution. Among them, geological disaster susceptibility has a negative driving effect on the EGECC, while landform, human activity impact index, and population density all display bidirectional effects. Overall, this study provides essential guidance for formulating ecological protection and restoration plans for the national territorial space in the Luoyang area of the YRB. Additionally, the evaluation methods established in this study have promotional value and can serve as a reference for the ecological geological spatial management of other resource-based cities.

Scientific ReportsVol. 15(1)
Jilin University (CN), Henan Polytechnic University (CN)
National Natural Science Foundation of China, Jilin University
Life in Land
Openalex Percentile: Top 1%
Advanced Decision-Making Techniques
22.72
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