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Article

A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery

1
Henan Institute of Surveying and Mapping, Zhengzhou 450003, China
2
College of Surveying and Mapping and Geographic Information, North China University of Water Resources and Electric, Zhengzhou 450045, China
3
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
4
Department of Geography, University of Connecticut, Storrs, CT 06269-4148, USA
5
No.7 Geological Party, Henan Nonferrous Metals Geological and Mineral Bureau, Zhengzhou 450016, China
6
Henan Institue of Remote Sensing and Geomatics, Zhengzhou 450003, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(4), 933; https://doi.org/10.3390/rs15040933
Submission received: 15 November 2022 / Revised: 27 January 2023 / Accepted: 1 February 2023 / Published: 8 February 2023
(This article belongs to the Special Issue Integrating Earth Observations into Ecosystem Service Models)

Abstract

The excessive exploitation of mineral resources will lead to environmental pollution, resource depletion, environmental disaster, and other problems. The contradiction between the environment and development, and the management of the ecological environment in mining areas are urgent p-problems to be solved. An ecological environment assessment is an important part of the ecological environment in a mining area. The accurate evaluation of the ecological environment is the premise behind environmental governance in a mining area. However, current ecological assessment indicators were not developed specifically for mine environment monitoring and, thus, cannot provide an effective and comprehensive assessment of the mineral environment. To this end, in order to improve the environmental monitoring performance in mining areas, a novel Mine-Specific Eco-Environment Index (MSEEI) was proposed, integrating factors from five main aspects associated with minerals, including temperature, vegetation, soil moisture, atmospheric environment, and mining scale. Meanwhile, a widely concerned mine—Luanchuan mine—was used as the case area to test the performance of our MSEEI. The results showed a significant correlation between RSEI and MSEEI (p < 0.01). The mean correlation achieved between RSEI and MSEEI was 0.91, which was much higher than the correlations between RSEI and enhanced vegetation index (EVI), soil moisture monitoring index (SMMI), normalized difference built-up and soil index (NDBSI), PM2.5 concentration (DI), and heat (LST). In addition, based on our long-term MSEEI results of Luanchuan mine from 1997 to 2021, the ecological status of Luanchuan mine showed a trend of first declining and then rising. Specifically, the MSEEI first declined from 0.85 to 0.77 between 1997 and 2012, and then rebounded to about 0.8 in recent years. The MSEEI exhibited a good applicability in the ecological assessment of mining areas. Our MSEEI can provide useful guidance for mine environment monitoring. MSEEI can directly reflect the ecological damage after mining, provide scientific guidance for the exploitation and utilization of mineral resources, and promote the protection and sustainable development of Earth’s resources and mine ecological environments.
Keywords: Mine-Specific Eco-Environment Index (MSEEI); mining area; ecological assessment; remote sensing Mine-Specific Eco-Environment Index (MSEEI); mining area; ecological assessment; remote sensing

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MDPI and ACS Style

Zhang, P.; Chen, X.; Ren, Y.; Lu, S.; Song, D.; Wang, Y. A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery. Remote Sens. 2023, 15, 933. https://doi.org/10.3390/rs15040933

AMA Style

Zhang P, Chen X, Ren Y, Lu S, Song D, Wang Y. A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery. Remote Sensing. 2023; 15(4):933. https://doi.org/10.3390/rs15040933

Chicago/Turabian Style

Zhang, Peipei, Xidong Chen, Yu Ren, Siqi Lu, Dongwei Song, and Yingle Wang. 2023. "A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery" Remote Sensing 15, no. 4: 933. https://doi.org/10.3390/rs15040933

APA Style

Zhang, P., Chen, X., Ren, Y., Lu, S., Song, D., & Wang, Y. (2023). A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery. Remote Sensing, 15(4), 933. https://doi.org/10.3390/rs15040933

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