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Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR

Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account...

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Autores principales: Zhang, Liya, Gao, Pengfei, Gan, Zhengzheng, Wu, Wenhao, Sun, Yafeng, Zhu, Chuanguang, Long, Sichun, Liu, Maoqi, Peng, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574917/
https://www.ncbi.nlm.nih.gov/pubmed/37836975
http://dx.doi.org/10.3390/s23198146
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author Zhang, Liya
Gao, Pengfei
Gan, Zhengzheng
Wu, Wenhao
Sun, Yafeng
Zhu, Chuanguang
Long, Sichun
Liu, Maoqi
Peng, Hui
author_facet Zhang, Liya
Gao, Pengfei
Gan, Zhengzheng
Wu, Wenhao
Sun, Yafeng
Zhu, Chuanguang
Long, Sichun
Liu, Maoqi
Peng, Hui
author_sort Zhang, Liya
collection PubMed
description Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account for a low proportion of the total, and the concentration of mineral resource distribution is low, meaning that traditional mining monitoring struggles to meet the needs of large-scale monitoring of mining areas in the province. The advantages of Interferometric Synthetic Aperture Radar (InSAR) technology in large-scale deformation monitoring were applied to identify and monitor the surface subsidence of coal mining fields in Hunan Province based on a Sentinel-1A dataset of 86 images taken from 2018 to 2020, and the process of developing surface subsidence was inverted by selecting typical mining areas. The results show that there are 14 places of surface subsidence in the study area, and accidents have occurred in 2 mining areas. In addition, the railway passing through the mining area of Zhouyuan Mountain is affected by the surface subsidence, presenting a potential safety hazard.
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spelling pubmed-105749172023-10-14 Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR Zhang, Liya Gao, Pengfei Gan, Zhengzheng Wu, Wenhao Sun, Yafeng Zhu, Chuanguang Long, Sichun Liu, Maoqi Peng, Hui Sensors (Basel) Article Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account for a low proportion of the total, and the concentration of mineral resource distribution is low, meaning that traditional mining monitoring struggles to meet the needs of large-scale monitoring of mining areas in the province. The advantages of Interferometric Synthetic Aperture Radar (InSAR) technology in large-scale deformation monitoring were applied to identify and monitor the surface subsidence of coal mining fields in Hunan Province based on a Sentinel-1A dataset of 86 images taken from 2018 to 2020, and the process of developing surface subsidence was inverted by selecting typical mining areas. The results show that there are 14 places of surface subsidence in the study area, and accidents have occurred in 2 mining areas. In addition, the railway passing through the mining area of Zhouyuan Mountain is affected by the surface subsidence, presenting a potential safety hazard. MDPI 2023-09-28 /pmc/articles/PMC10574917/ /pubmed/37836975 http://dx.doi.org/10.3390/s23198146 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Liya
Gao, Pengfei
Gan, Zhengzheng
Wu, Wenhao
Sun, Yafeng
Zhu, Chuanguang
Long, Sichun
Liu, Maoqi
Peng, Hui
Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title_full Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title_fullStr Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title_full_unstemmed Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title_short Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
title_sort surface subsidence monitoring of mining areas in hunan province based on sentinel-1a and ds-insar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574917/
https://www.ncbi.nlm.nih.gov/pubmed/37836975
http://dx.doi.org/10.3390/s23198146
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