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Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology
In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities in mining cl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146487/ https://www.ncbi.nlm.nih.gov/pubmed/35632120 http://dx.doi.org/10.3390/s22103711 |
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author | Wang, Huini Li, Kanglun Zhang, Jun Hong, Liang Chi, Hong |
author_facet | Wang, Huini Li, Kanglun Zhang, Jun Hong, Liang Chi, Hong |
author_sort | Wang, Huini |
collection | PubMed |
description | In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities in mining cluster areas. We adopted the Small Baseline Subset InSAR (SBAS-InSAR) technique to process Sentinel-1A SAR images over the research area from March 2017 to May 2021. The deformation estimation technology based on the robustness of PS points and DS points can be used for early identification of high-density surface subsidence in a large area of mines. The surface subsidence information can be obtained quickly and accurately, and the advantages of using InSAR technology to monitor long-time surface subsidence in complex mining cluster areas was explored in this study. By comparing the monitoring data of the Global Navigation Satellite System (GNSS) ground monitoring equipment, the accuracy error of large-scale surface settlement information is controlled within 8 mm, which has high accuracy. Meanwhile, according to the spatial characteristics of cluster mining areas, it is analyzed that the relationship between adjacent mining areas through groundwater easily leads to regional associated large-area settlement changes. Compared with the D-InSAR (Differential InSAR) technology applied in mine monitoring at the early stage, this proposed method can monitor a large range of long time series and optimize the problem of decoherence to some extent in mining cluster areas. It has important reference significance for early monitoring and early warning of subsidence disaster evolution in mining intensive areas. |
format | Online Article Text |
id | pubmed-9146487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91464872022-05-29 Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology Wang, Huini Li, Kanglun Zhang, Jun Hong, Liang Chi, Hong Sensors (Basel) Article In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities in mining cluster areas. We adopted the Small Baseline Subset InSAR (SBAS-InSAR) technique to process Sentinel-1A SAR images over the research area from March 2017 to May 2021. The deformation estimation technology based on the robustness of PS points and DS points can be used for early identification of high-density surface subsidence in a large area of mines. The surface subsidence information can be obtained quickly and accurately, and the advantages of using InSAR technology to monitor long-time surface subsidence in complex mining cluster areas was explored in this study. By comparing the monitoring data of the Global Navigation Satellite System (GNSS) ground monitoring equipment, the accuracy error of large-scale surface settlement information is controlled within 8 mm, which has high accuracy. Meanwhile, according to the spatial characteristics of cluster mining areas, it is analyzed that the relationship between adjacent mining areas through groundwater easily leads to regional associated large-area settlement changes. Compared with the D-InSAR (Differential InSAR) technology applied in mine monitoring at the early stage, this proposed method can monitor a large range of long time series and optimize the problem of decoherence to some extent in mining cluster areas. It has important reference significance for early monitoring and early warning of subsidence disaster evolution in mining intensive areas. MDPI 2022-05-13 /pmc/articles/PMC9146487/ /pubmed/35632120 http://dx.doi.org/10.3390/s22103711 Text en © 2022 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 Wang, Huini Li, Kanglun Zhang, Jun Hong, Liang Chi, Hong Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title | Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title_full | Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title_fullStr | Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title_full_unstemmed | Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title_short | Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology |
title_sort | monitoring and analysis of ground surface settlement in mining clusters by sbas-insar technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146487/ https://www.ncbi.nlm.nih.gov/pubmed/35632120 http://dx.doi.org/10.3390/s22103711 |
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