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应用生态学报 ›› 2026, Vol. 37 ›› Issue (5): 1570-1582.doi: 10.13287/j.1001-9332.202605.027

• 研究论文 • 上一篇    下一篇

基于不同遥感生态质量评价指数评价露天煤矿生态质量

张涵1, 李飞跃1, 何雨阳1, 孟耀庆1, 李军1,2,3*, 蒲丽君1, 张成业1,3, 彭曼凌1   

  1. 1中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083;
    2天山实验室, 乌鲁木齐 830023;
    3煤炭精细勘探与智能开发全国重点实验室, 北京 100083
  • 收稿日期:2025-11-23 接受日期:2026-03-30 出版日期:2026-05-18 发布日期:2026-11-18
  • 通讯作者: * E-mail: junli@cumtb.edu.cn
  • 作者简介:张 涵, 女, 2003年生, 硕士研究生。主要从事矿区生态遥感监测研究。E-mail: hanzhang@student.cumtb.edu.cn
  • 基金资助:
    国家重点研发计划项目(2022YFF1303301)、丝绸之路经济带创新驱动发展试验区、乌昌石国家自主创新示范区科技发展计划项目(2023LQY02)、国家能源集团科技创新项目(GJNY-23-38)和宁波市镇海区“十四五”技术攻关重大专项(2024006)

Assessing ecological quality in open-pit coal mines based on different remote sensing indices.

ZHANG Han1, LI Feiyue1, HE Yuyang1, MENG Yaoqing1, LI Jun1,2,3*, PU Lijun1, ZHANG Chengye1,3, PENG Manling1   

  1. 1College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China;
    2Tianshan Laboratory, Urumqi 830023, China;
    3State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, Beijing 100083, China
  • Received:2025-11-23 Accepted:2026-03-30 Online:2026-05-18 Published:2026-11-18

摘要: 我国露天煤矿分布广泛,其生态环境监测易受水热条件、植被类型和土壤特征等地理异质性影响。为实现跨区域精准监测,亟需开展生态质量评价指数的适用性研究。本研究选取干旱戈壁、半干旱草原、半干旱高原和喀斯特高原4个典型气候-地貌区的露天煤矿为研究区,基于Google Earth Engine和统一的Landsat 8 OLI数据,分别采用标准化遥感生态指数(RSEIs)、地表生态状况组成指数(LSESCI)、新型遥感生态指数(RSEInew)和露天煤矿生态指数(SurMEI)开展生态质量评价;通过对比分析各指数的评价结果,结合相关性分析、空间分布识别、土地覆盖响应评估及典型矿区地面实测数据验证,揭示了各指数在不同气候-地貌区露天煤矿的适应性和局限性。结果表明:基于SurMEI的4个典型气候-地貌区露天煤矿的生态质量评价结果最优(平均相关系数为0.810),在跨区域评价中表现出良好的适应性;其余3个指数因指标结构与区域主导生态过程耦合不匹配而出现系统性偏差,RSEIs在湿润区因对归一化差异裸土指数过度敏感而产生“过度扰动”误判;LSESCI在复杂地形区因缨帽变换的亮度分量不稳定导致判别混淆;RSEInew在干旱区因新增PM2.5指标的判别力弱而失效。基于SurMEI的时空分析进一步揭示,不同气候-地貌区生态恢复潜力差异显著,其中,喀斯特高原区的生态恢复潜力最高,半干旱地区(包括草原和高原)居中,干旱戈壁区的修复潜力最低,生态修复需遵循“分区治理”原则。本研究结果为不同气候-地貌区露天煤矿生态质量精准监测和模型优选提供了理论依据。

关键词: 遥感生态质量评价, 气候-地貌区, 露天煤矿, 指数优选, 时空变化

Abstract: Open-pit coal mines are widely distributed in China, and the ecological monitoring of which is susceptible to geographical heterogeneity in hydrothermal conditions, vegetation types, and soil characteristics. To achieve accurate cross-regional monitoring, it is essential to evaluate the applicability of ecological quality assessment indices. Based on Google Earth Engine and uniform Landsat 8 OLI data, we used the 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) to evaluate ecological quality of open-pit coal mines in four typical climatic-geomorphologic zones (arid Gobi, semi-arid grassland, semi-arid plateau, and karst plateau). Through comparative analysis of the evaluation results of four indices, combined with correlation analysis, spatial distribution identification, land cover response assessment, and validation with synchronous field measurement data from typical mining areas, we analyzed the adaptability and limitations of each index in open-pit coal mines across different climatic-geomorphologic zones. The results showed that the ecological quality assessment based on SurMEI exhibited the best performance (mean correlation coefficient of 0.810) in the four typical climatic-geomorphologic zones, demonstrating good adaptability in cross-regional evaluations. The performance disparities among the other three indices arose from mismatches between their index structures and regionally dominant ecological processes. RSEIs overestimated disturbances in humid areas due to excessive sensitivity to the normalized difference bare soil index. LSESCI exhibited misclassification in complex terrains, owing to instability of the brightness component derived from the tasseled cap transformation. RSEInew failed in arid zones because of the weak discriminative power of its added PM2.5 indicator. Furthermore, spatiotemporal analysis based on SurMEI revealed significant differences in ecological restoration potential across different climatic-geomorphologic zones, with the highest potential in the karst plateau, intermediate in the semi-arid region (including grassland and plateau), and the lowest in the arid Gobi, indicating that ecological restoration should follow the principle of “zonal management”. This study would provide a theoretical basis for accurate monitoring of ecological quality and model optimization for open-pit coal mines across different climatic-geomorphologic zones.

Key words: remote sensing ecological quality assessment, climatic-geomorphologic zone, open-pit coal mine, index optimization, spatial and temporal variation