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Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China
With the exploitation of coalfields, the eco-environment around the coalfields can become badly damaged. To address this issue, “mine greening” has been proposed by the Ministry of Land and Resources of China. The sustainable development of mine environments has now become one of the most prominent...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388114/ https://www.ncbi.nlm.nih.gov/pubmed/30759759 http://dx.doi.org/10.3390/ijerph16030511 |
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author | Wang, Xue Tan, Kun Xu, Kailei Chen, Yu Ding, Jianwei |
author_facet | Wang, Xue Tan, Kun Xu, Kailei Chen, Yu Ding, Jianwei |
author_sort | Wang, Xue |
collection | PubMed |
description | With the exploitation of coalfields, the eco-environment around the coalfields can become badly damaged. To address this issue, “mine greening” has been proposed by the Ministry of Land and Resources of China. The sustainable development of mine environments has now become one of the most prominent issues in China. In this study, we aimed to make use of Landsat 7 ETM+ and Landsat 8 OLI images obtained between 2005 and 2016 to analyze the eco-environment in a coalfield. Land cover was implemented as the basic evaluation factor to establish the evaluation model for the eco-environment. Analysis and investigation of the eco-environment in the Yuxian coalfield was conducted using a novel evaluation model, based on the biological abundance index, vegetation coverage index, water density index, and natural geographical factors. The weight of each indicator was determined by an analytic hierarchy process. Meanwhile, we also used the classic ecological footprint to calculate the ecological carrying capacity in order to verify the effectiveness of the evaluation model. Results showed that the eco-environment index illustrated a slowly increasing tendency over the study period, and the ecological quality could be considered as “good”. The results of the evaluation model showed a strong correlation with the ecological carrying capacity with a correlation coefficient of 0.9734. In conclusion, the evaluation method is a supplement to the time-series quantitative evaluation of the eco-environment, and also helps us to explore the eco-environment in the mining area. |
format | Online Article Text |
id | pubmed-6388114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63881142019-02-27 Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China Wang, Xue Tan, Kun Xu, Kailei Chen, Yu Ding, Jianwei Int J Environ Res Public Health Article With the exploitation of coalfields, the eco-environment around the coalfields can become badly damaged. To address this issue, “mine greening” has been proposed by the Ministry of Land and Resources of China. The sustainable development of mine environments has now become one of the most prominent issues in China. In this study, we aimed to make use of Landsat 7 ETM+ and Landsat 8 OLI images obtained between 2005 and 2016 to analyze the eco-environment in a coalfield. Land cover was implemented as the basic evaluation factor to establish the evaluation model for the eco-environment. Analysis and investigation of the eco-environment in the Yuxian coalfield was conducted using a novel evaluation model, based on the biological abundance index, vegetation coverage index, water density index, and natural geographical factors. The weight of each indicator was determined by an analytic hierarchy process. Meanwhile, we also used the classic ecological footprint to calculate the ecological carrying capacity in order to verify the effectiveness of the evaluation model. Results showed that the eco-environment index illustrated a slowly increasing tendency over the study period, and the ecological quality could be considered as “good”. The results of the evaluation model showed a strong correlation with the ecological carrying capacity with a correlation coefficient of 0.9734. In conclusion, the evaluation method is a supplement to the time-series quantitative evaluation of the eco-environment, and also helps us to explore the eco-environment in the mining area. MDPI 2019-02-12 2019-02 /pmc/articles/PMC6388114/ /pubmed/30759759 http://dx.doi.org/10.3390/ijerph16030511 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Xue Tan, Kun Xu, Kailei Chen, Yu Ding, Jianwei Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title | Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title_full | Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title_fullStr | Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title_full_unstemmed | Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title_short | Quantitative Evaluation of the Eco-Environment in a Coalfield Based on Multi-Temporal Remote Sensing Imagery: A Case Study of Yuxian, China |
title_sort | quantitative evaluation of the eco-environment in a coalfield based on multi-temporal remote sensing imagery: a case study of yuxian, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388114/ https://www.ncbi.nlm.nih.gov/pubmed/30759759 http://dx.doi.org/10.3390/ijerph16030511 |
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