Optimization of Land Pattern in Mining Area Based on the Improvement of Ecosystem Service Function—A Case Study of Fushun Mining Area

ABSTRACT Mining activities are prevalent worldwide and pose significant threats to the supply of ecosystem services (ESs) for humanity. Many mining areas face challenges related to recovery and reclamation following resource depletion. A key challenge for the sustainable development of these areas is how to achieve collaborative optimization of land pattern and enhancing ESs during the restoration process. To address the above challenges, we have innovatively analyzed land suitability through machine learning, and combined with ESs assessment (InVEST) and driving factor analysis (Geographic detector, Structural equation model) to explore the optimal land pattern for future Fushun mining area restoration. The findings are as follows: (1) From 1990 to 2020, water yield (WY), soil conservation (SC), and food production (FP) exhibited an increasing trend (8%, 3%, 22%), while habitat quality (HQ) and carbon sequestration (CS) showed a decreasing trend (12%, 4%). Plus model predicts that ESs will decrease 4%–60% in the future from 2030 to 2050. (2) Surface mining significantly impacts SC by indirectly altering terrain, which subsequently affects ESs that are coordinated with SC; normalized difference vegetation index (NDVI) is the main factor to improve ESs (0.2–0.6). (3) Machine learning analysis revealed that high forestland reclamation suitability is primarily concentrated in the open‐pit mine and factory boundaries, whereas mine pits are more suitable for water reclamation. The peripheral areas of the mining site are more suited for farmland and construction land reclamation. (4) Based on the results of land suitability and ecosystem services, the optimal land pattern under ESs enhancement scenarios was proposed. In the future, the land pattern of “pit water storage—in field farming—peripheral afforestation” should be formed to rationally restore land and comprehensively enhance ESs. This study proposes a new method for optimizing the land pattern of mining areas for the improvement of ecosystem services, which provides an important reference for the sustainable development of other mining areas in the world.

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Publication Details

Journal
Land Degradation and Development
Published
2026-08-14
DOI
https://doi.org/10.1002/ldr.70831
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
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article

Optimization of Land Pattern in Mining Area Based on the Improvement of Ecosystem Service Function—A Case Study of Fushun Mining Area

Changwei An, Luge Rong
Land Degradation and Development
Land Use and Ecosystem Services
article

Optimization of Land Pattern in Mining Area Based on the Improvement of Ecosystem Service Function—A Case Study of Fushun Mining Area

Changwei An, Luge Rong
article en

Abstract

ABSTRACT Mining activities are prevalent worldwide and pose significant threats to the supply of ecosystem services (ESs) for humanity. Many mining areas face challenges related to recovery and reclamation following resource depletion. A key challenge for the sustainable development of these areas is how to achieve collaborative optimization of land pattern and enhancing ESs during the restoration process. To address the above challenges, we have innovatively analyzed land suitability through machine learning, and combined with ESs assessment (InVEST) and driving factor analysis (Geographic detector, Structural equation model) to explore the optimal land pattern for future Fushun mining area restoration. The findings are as follows: (1) From 1990 to 2020, water yield (WY), soil conservation (SC), and food production (FP) exhibited an increasing trend (8%, 3%, 22%), while habitat quality (HQ) and carbon sequestration (CS) showed a decreasing trend (12%, 4%). Plus model predicts that ESs will decrease 4%–60% in the future from 2030 to 2050. (2) Surface mining significantly impacts SC by indirectly altering terrain, which subsequently affects ESs that are coordinated with SC; normalized difference vegetation index (NDVI) is the main factor to improve ESs (0.2–0.6). (3) Machine learning analysis revealed that high forestland reclamation suitability is primarily concentrated in the open‐pit mine and factory boundaries, whereas mine pits are more suitable for water reclamation. The peripheral areas of the mining site are more suited for farmland and construction land reclamation. (4) Based on the results of land suitability and ecosystem services, the optimal land pattern under ESs enhancement scenarios was proposed. In the future, the land pattern of “pit water storage—in field farming—peripheral afforestation” should be formed to rationally restore land and comprehensively enhance ESs. This study proposes a new method for optimizing the land pattern of mining areas for the improvement of ecosystem services, which provides an important reference for the sustainable development of other mining areas in the world.

Land Degradation and Development
University of Science and Technology Liaoning (CN), Liaoning University (CN), Liaoning University of Technology (CN)
Openalex Percentile: Top 12%
Land Use and Ecosystem Services
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