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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10574917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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