Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering
Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed...
Ausführliche Beschreibung
Autor*in: |
Zhong, Anya [verfasserIn] Wang, Zhen [verfasserIn] Zhang, Zixuan [verfasserIn] Hu, Chunming [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2024 |
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Schlagwörter: |
Mine remote sensing ecological index |
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Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Übergeordnetes Werk: |
Enthalten in: Environmental earth sciences - Springer Berlin Heidelberg, 2009, 83(2024), 20 vom: Okt. |
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Übergeordnetes Werk: |
volume:83 ; year:2024 ; number:20 ; month:10 |
Links: |
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DOI / URN: |
10.1007/s12665-024-11893-8 |
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Katalog-ID: |
SPR05774565X |
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520 | |a Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. | ||
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650 | 4 | |a Restoration effect |7 (dpeaa)DE-He213 | |
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700 | 1 | |a Hu, Chunming |e verfasserin |4 aut | |
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10.1007/s12665-024-11893-8 doi (DE-627)SPR05774565X (SPR)s12665-024-11893-8-e DE-627 ger DE-627 rakwb eng 550 VZ 38.95 bkl Zhong, Anya verfasserin aut Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. Mine remote sensing ecological index (dpeaa)DE-He213 Ecological environment quality (dpeaa)DE-He213 Change detection (dpeaa)DE-He213 Restoration effect (dpeaa)DE-He213 Remote-sensing evaluation (dpeaa)DE-He213 Wang, Zhen verfasserin aut Zhang, Zixuan verfasserin aut Hu, Chunming verfasserin aut Enthalten in Environmental earth sciences Springer Berlin Heidelberg, 2009 83(2024), 20 vom: Okt. (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:83 year:2024 number:20 month:10 https://dx.doi.org/10.1007/s12665-024-11893-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 38.95 VZ AR 83 2024 20 10 |
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10.1007/s12665-024-11893-8 doi (DE-627)SPR05774565X (SPR)s12665-024-11893-8-e DE-627 ger DE-627 rakwb eng 550 VZ 38.95 bkl Zhong, Anya verfasserin aut Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. Mine remote sensing ecological index (dpeaa)DE-He213 Ecological environment quality (dpeaa)DE-He213 Change detection (dpeaa)DE-He213 Restoration effect (dpeaa)DE-He213 Remote-sensing evaluation (dpeaa)DE-He213 Wang, Zhen verfasserin aut Zhang, Zixuan verfasserin aut Hu, Chunming verfasserin aut Enthalten in Environmental earth sciences Springer Berlin Heidelberg, 2009 83(2024), 20 vom: Okt. (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:83 year:2024 number:20 month:10 https://dx.doi.org/10.1007/s12665-024-11893-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 38.95 VZ AR 83 2024 20 10 |
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10.1007/s12665-024-11893-8 doi (DE-627)SPR05774565X (SPR)s12665-024-11893-8-e DE-627 ger DE-627 rakwb eng 550 VZ 38.95 bkl Zhong, Anya verfasserin aut Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. 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(DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:83 year:2024 number:20 month:10 https://dx.doi.org/10.1007/s12665-024-11893-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 38.95 VZ AR 83 2024 20 10 |
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10.1007/s12665-024-11893-8 doi (DE-627)SPR05774565X (SPR)s12665-024-11893-8-e DE-627 ger DE-627 rakwb eng 550 VZ 38.95 bkl Zhong, Anya verfasserin aut Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. Mine remote sensing ecological index (dpeaa)DE-He213 Ecological environment quality (dpeaa)DE-He213 Change detection (dpeaa)DE-He213 Restoration effect (dpeaa)DE-He213 Remote-sensing evaluation (dpeaa)DE-He213 Wang, Zhen verfasserin aut Zhang, Zixuan verfasserin aut Hu, Chunming verfasserin aut Enthalten in Environmental earth sciences Springer Berlin Heidelberg, 2009 83(2024), 20 vom: Okt. (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:83 year:2024 number:20 month:10 https://dx.doi.org/10.1007/s12665-024-11893-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 38.95 VZ AR 83 2024 20 10 |
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10.1007/s12665-024-11893-8 doi (DE-627)SPR05774565X (SPR)s12665-024-11893-8-e DE-627 ger DE-627 rakwb eng 550 VZ 38.95 bkl Zhong, Anya verfasserin aut Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. Mine remote sensing ecological index (dpeaa)DE-He213 Ecological environment quality (dpeaa)DE-He213 Change detection (dpeaa)DE-He213 Restoration effect (dpeaa)DE-He213 Remote-sensing evaluation (dpeaa)DE-He213 Wang, Zhen verfasserin aut Zhang, Zixuan verfasserin aut Hu, Chunming verfasserin aut Enthalten in Environmental earth sciences Springer Berlin Heidelberg, 2009 83(2024), 20 vom: Okt. (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:83 year:2024 number:20 month:10 https://dx.doi.org/10.1007/s12665-024-11893-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 38.95 VZ AR 83 2024 20 10 |
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Zhong, Anya |
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remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering |
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Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering |
abstract |
Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstractGer |
Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstract_unstemmed |
Abstract The extraction of minerals on an extensive scale, though a catalyst for economic advancement, precipitates notable ecological concerns. In recent years, due to decarbonization initiatives and the closure of numerous open-pit mines, increasing attention and research focus have been directed toward evaluating the effectiveness of ecological restoration in mining areas. This study leverages Landsat series imagery and employs the pseudo-invariant feature (PIF) method for radiometric normalization of remote sensing images, all within the framework of ecological engineering. In light of the significant consideration given to soil erosion and air pollution factors in the acceptance standards for ecological engineering, the Mine Remote Sensing Ecological Index (MRSEI) is developed based on the Pressure-State-Response (PSR) framework. This index is employed to perform spatiotemporal analysis and dynamic monitoring of the ecological quality in the restoration area of Wangping coal mine. The results illustrate that: Compared to the Remote Sensing Ecological Index (RSEI), the first principal component of the MRSEI consolidates the information of various sub-indicators more effectively. This allows for a more objective representation of the ecological quality. From 1990 to 2021, the average value of the MRSEI in the Wangping coal mining area shows an overall upward trend, increasing from 0.429 in 1990 to 0.731 in 2021, representing an improvement of 70.40%. The validation of the MRSEI indicates that this index accurately reflects the objective patterns of local ecological quality changes. Moreover, it is strongly correlated with various individual ecological indicators. The application and promotion of the MRSEI offer valuable insights for policymakers in developing plans for mine ecological restoration projects and strategies for regional coordinated development. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Remote sensing monitoring of ecological environment quality in mining areas under the perspective of ecological engineering |
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https://dx.doi.org/10.1007/s12665-024-11893-8 |
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Wang, Zhen Zhang, Zixuan Hu, Chunming |
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Wang, Zhen Zhang, Zixuan Hu, Chunming |
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10.1007/s12665-024-11893-8 |
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|
score |
7.1678753 |