Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China
Dense mining areas are regions with relatively concentrated mining enterprises or occupied land, which are also regions with intense economic and resource development conflicts and environmental protection. However, ecological assessments by remotely sensed technology do not consider the characteris...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-02-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22012870 |
| _version_ | 1797942164892680192 |
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| author | Wen Song Hai-Hong Gu Wei Song Fu-Ping Li Shao-Ping Cheng Yi-Xuan Zhang Yan-Jun Ai |
| author_facet | Wen Song Hai-Hong Gu Wei Song Fu-Ping Li Shao-Ping Cheng Yi-Xuan Zhang Yan-Jun Ai |
| author_sort | Wen Song |
| collection | DOAJ |
| description | Dense mining areas are regions with relatively concentrated mining enterprises or occupied land, which are also regions with intense economic and resource development conflicts and environmental protection. However, ecological assessments by remotely sensed technology do not consider the characteristics of mining areas. To fill the knowledge gap, we employed seven indexes, i.e., fractional vegetation cover, greenness above bare soil, wetness, black particulates, land surface temperature, iron oxides, and the landscape fragmentation index, to construct the iron mine remote sensing-based ecological index (IM-RSEI) by Landsat data. We chose Qian’an City and Qianxi County in Tangshan City, China, as the study area where iron ore-related industries are concentrated. The results showed that the ecological environment generally deteriorated first and then improved that the IM-RSEI values for 1992, 2000, 2009, and 2018 were 0.5102, 0.4776, 0.4882, and 0.5001, respectively. The mean IM-RSEI values for the dense mining area and surrounding multi-gradient buffer zones, from near to far, were 0.5412, 0.5146, 0.5076, 0.4756, and 0.4563, implying that mining activities endangered the surrounding ecological quality. This study assessed the ecological environment in dense mining areas from multiple perspectives by remote sensing technology. The research conclusions can provide a reference for pollution control during mining development in Qian’an, Qianxi, and similar mining areas. |
| first_indexed | 2024-04-10T20:03:00Z |
| format | Article |
| id | doaj.art-d775d4a43dae49eca064a9f5c9906052 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-10T20:03:00Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-d775d4a43dae49eca064a9f5c99060522023-01-27T04:19:16ZengElsevierEcological Indicators1470-160X2023-02-01146109814Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions ChinaWen Song0Hai-Hong Gu1Wei Song2Fu-Ping Li3Shao-Ping Cheng4Yi-Xuan Zhang5Yan-Jun Ai6College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaCollege of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China; Hebei Key Laboratory of Mining Development and Security Technology, Tangshan 063210, China; Tangshan Key Laboratory of Resources and Environmental Remote Sensing, Tangshan 063210, China; Hebei Industrial Technology Institute of Mine Ecological Remediation, Tangshan 063210, China; Corresponding author at: College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaCollege of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China; Hebei Key Laboratory of Mining Development and Security Technology, Tangshan 063210, China; Tangshan Key Laboratory of Resources and Environmental Remote Sensing, Tangshan 063210, China; Hebei Industrial Technology Institute of Mine Ecological Remediation, Tangshan 063210, ChinaCollege of Mining Engineering, North China University of Science and Technology, Tangshan 063210, ChinaCollege of Mining Engineering, North China University of Science and Technology, Tangshan 063210, ChinaCollege of Mining Engineering, North China University of Science and Technology, Tangshan 063210, ChinaDense mining areas are regions with relatively concentrated mining enterprises or occupied land, which are also regions with intense economic and resource development conflicts and environmental protection. However, ecological assessments by remotely sensed technology do not consider the characteristics of mining areas. To fill the knowledge gap, we employed seven indexes, i.e., fractional vegetation cover, greenness above bare soil, wetness, black particulates, land surface temperature, iron oxides, and the landscape fragmentation index, to construct the iron mine remote sensing-based ecological index (IM-RSEI) by Landsat data. We chose Qian’an City and Qianxi County in Tangshan City, China, as the study area where iron ore-related industries are concentrated. The results showed that the ecological environment generally deteriorated first and then improved that the IM-RSEI values for 1992, 2000, 2009, and 2018 were 0.5102, 0.4776, 0.4882, and 0.5001, respectively. The mean IM-RSEI values for the dense mining area and surrounding multi-gradient buffer zones, from near to far, were 0.5412, 0.5146, 0.5076, 0.4756, and 0.4563, implying that mining activities endangered the surrounding ecological quality. This study assessed the ecological environment in dense mining areas from multiple perspectives by remote sensing technology. The research conclusions can provide a reference for pollution control during mining development in Qian’an, Qianxi, and similar mining areas.http://www.sciencedirect.com/science/article/pii/S1470160X22012870Iron-mine-remote sensing ecological index (IM-RSEI)Dense mining areaFactor analysisEcological changes |
| spellingShingle | Wen Song Hai-Hong Gu Wei Song Fu-Ping Li Shao-Ping Cheng Yi-Xuan Zhang Yan-Jun Ai Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China Ecological Indicators Iron-mine-remote sensing ecological index (IM-RSEI) Dense mining area Factor analysis Ecological changes |
| title | Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China |
| title_full | Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China |
| title_fullStr | Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China |
| title_full_unstemmed | Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China |
| title_short | Environmental assessments in dense mining areas using remote sensing information over Qian'an and Qianxi regions China |
| title_sort | environmental assessments in dense mining areas using remote sensing information over qian an and qianxi regions china |
| topic | Iron-mine-remote sensing ecological index (IM-RSEI) Dense mining area Factor analysis Ecological changes |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22012870 |
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