典型煤炭矿区生态健康遥感诊断

doi:10.13474/j.cnki.11-2246.2023.0012

测绘通报 ›› 2023, Vol. 0 ›› Issue (1): 71-76,94.doi: 10.13474/j.cnki.11-2246.2023.0012

典型煤炭矿区生态健康遥感诊断

陈逸雨^1,2, 曹春香¹, 徐敏¹, 谢波^1,2, 张九堂³

1. 中国科学院空天信息创新研究院遥感科学国家重点实验室, 北京 100101;
2. 中国科学院大学, 北京 100094;
3. 山西灵石华苑煤业有限公司, 山西晋中 031300

收稿日期:2022-02-23 发布日期:2023-02-08
通讯作者: 曹春香。E-mail:caocx@radi.ac.cn
作者简介:陈逸雨(1997-),女,硕士生,研究方向为环境健康遥感诊断。E-mail:chenyiyu19@mails.ucas.ac.cn
基金资助:
国家重点研发计划(2021YFB3901104);国家自然科学基金(41971394);国家林业和草原局林草科技创新发展与研究项目(2020132108)

Remote sensing diagnosis of ecological health in typical coal mining areas

CHEN Yiyu^1,2, CAO Chunxiang¹, XU Min¹, XIE Bo^1,2, ZHANG Jiutang³

1. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China;
2. University of Chinese Academy of Sciences, Beijing 100094, China;
3. Shanxi Lingshi Huayuan Coal Industry Co., Ltd., Jinzhong 031300, China

Received:2022-02-23 Published:2023-02-08

摘要/Abstract

摘要： 煤炭资源是我国重要的一次性能源,科学监测与评估矿区生态健康,对于维持经济发展与生态健康的平衡至关重要。本文选取位于山西省的3处典型煤炭矿区,基于2001—2021年的Landsat遥感数据,利用目视解译方法对露天矿区进行了多年用地类型演变格局分析;并分别对3处典型矿区的绿度、湿度、干度、热度进行了估算,应用知识粒度熵的权重计算方法,综合构建了矿区遥感生态指数(RSEI),完成了矿区生态健康多年遥感诊断。结果表明,两处露天矿区呈现边开采边复垦的生产模式,各有半数的研究年份RESI区域均值达到0.5以上;地下矿区的开采工作基本不造成地上扰动,其2001年以来的生态健康状况较为稳定,RSEI均值在0.7上下浮动;3处矿区2021年的RSEI均值分别为0.53、0.48、0.70。本文改进了传统的遥感生态指数构建方法,为煤炭矿区的长时序生态监测与遥感诊断提供了科学支撑。

关键词: 典型煤炭矿区, 生态, 指数, 知识粒度熵, 遥感诊断

Abstract: Coal resource is an important disposable energy source in China, and it is crucial to scientifically monitor and assess the ecological health of mining areas so as to maintain a balanced relationship between economic development and ecological health. In this study, three typical coal mining areas located in Shanxi province are selected. Landsat remote sensing data from 2001—2021 are used to analyze the multi-year land type evolution pattern of the open pit mining areas by visual interpretation. The greenness, humidity, dryness, and heat of the three typical mining areas are calculated, respectively. Then we construct a remote sensing ecological index(RSEI) of the mining areas based on the weight calculation method of knowledge granularity entropy, so as to complete the multi-year remote sensing diagnosis of mine ecological health. The results show that the two open-pit mines maintain reclamation while mining, and during half of the studying years their mean RSEI reach to 0.5. The underground mine area basically does not cause above-ground disturbance, and its ecological health is stable for many years. Its mean RSEI is around 0.7. In 2021, the mean RSEI values of the three mining areas are 0.53,0.48 and 0.70, respectively. This study improves the traditional remote sensing ecological index construction method, and provides scientific guidance for long time series ecological monitoring and remote sensing diagnosis of coal mining areas.

Key words: typical coal mining area, ecology, index, knowledge granularity entropy, remote sensing diagnosis

中图分类号:

P237

陈逸雨, 曹春香, 徐敏, 谢波, 张九堂. 典型煤炭矿区生态健康遥感诊断[J]. 测绘通报, 2023, 0(1): 71-76,94.

CHEN Yiyu, CAO Chunxiang, XU Min, XIE Bo, ZHANG Jiutang. Remote sensing diagnosis of ecological health in typical coal mining areas[J]. Bulletin of Surveying and Mapping, 2023, 0(1): 71-76,94.

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典型煤炭矿区生态健康遥感诊断

Remote sensing diagnosis of ecological health in typical coal mining areas

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