Evaluation of eco-environmental quality for the coal-mining region using multi-source data.

Area of Science:

• Environmental Science
• Ecology
• Geoscience

Background:

• The conflict between coal resource exploitation and ecological protection in western China is growing.
• Effective ecological environment evaluation is crucial for mitigating this conflict.

Purpose of the Study:

• To evaluate the eco-environment of the Ibei coalfield using integrated methods.
• To analyze spatial characteristics and identify driving factors of eco-environmental quality.

Main Methods:

• Genetic projection pursuit model and Geographic Information System (GIS) for eco-environment evaluation.
• Remote sensing and statistical data analysis.
• Spatial autocorrelation and geographic detector for spatial analysis and factor identification.

Main Results:

• Ibei Coalfield exhibits a heterogeneous eco-environment pattern, with the highest mining intensity area showing the worst quality.
• Mining intensity and surface subsidence are key human drivers, while precipitation, elevation, evaporation, NDVI, and land use are significant natural factors.
• Interaction effects of factors are substantial, and eco-environmental quality shows nonlinear correlations with impact indicators.

Conclusions:

• Spatial autocorrelation analysis identified distinct management, close attention, and protective areas.
• Tailored management strategies are proposed for different zones to support sustainable coal mining and eco-environmental protection.