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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Assessing ecological quality in open-pit coal mines based on different remote sensing indices.
Han Zhang1, Fei-Yue Li1, Yu-Yang He1
1College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.
Summary
The Surface Mine Ecological Index (SurMEI) best assesses ecological quality in diverse open-pit coal mine regions. Ecological restoration potential varies by zone, requiring tailored management strategies for effective land reclamation.
Area of Science:
- Environmental Science
- Remote Sensing
- Ecology
Background:
- Open-pit coal mines present ecological monitoring challenges due to regional variations in climate, vegetation, and soil.
- Accurate cross-regional ecological quality assessment requires evaluating the suitability of existing remote sensing indices.
Purpose of the Study:
- To compare the performance of four ecological quality assessment indices (RSEIs, LSESCI, RSEInew, SurMEI) for open-pit coal mines across diverse climatic-geomorphologic zones.
- To identify the most adaptable index for cross-regional ecological monitoring and analyze limitations of others.
- To assess ecological restoration potential and inform zonal management strategies.
Main Methods:
- Utilized Google Earth Engine and Landsat 8 OLI data for ecological quality assessment.
- Applied four indices: Standardized Remote Sensing Ecological Index (RSEIs), Land Surface Ecological Status Composition Index (LSESCI), New Remote Sensing-based Ecological Index (RSEInew), and Surface Coal Mine Ecological Index (SurMEI).
- Conducted comparative analysis, correlation analysis, spatial distribution identification, land cover response assessment, and field validation.
Main Results:
- The Surface Coal Mine Ecological Index (SurMEI) demonstrated the best performance (mean correlation coefficient 0.810) across four zones, indicating superior adaptability for cross-regional monitoring.
- RSEIs overestimated disturbances, LSESCI showed misclassification in complex terrains, and RSEInew performed poorly in arid zones due to index structure mismatches.
- Ecological restoration potential was highest in karst plateaus, intermediate in semi-arid regions, and lowest in arid Gobi zones.
Conclusions:
- SurMEI is the most suitable index for ecological quality assessment in open-pit coal mines across varied climatic-geomorphologic zones.
- Ecological restoration strategies must be tailored to specific zones ('zonal management') for optimal outcomes.
- This research provides a foundation for optimizing ecological monitoring models for mining areas.
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