Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model

Underground coal mining activities often cause ground subsidence and damage to surface construction, which seriously threatens the lives and property of residents in mining areas. In this paper, the deformation of the Yang Juzhuang village, which is a residential area in the Huainan mining area (Chi...

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Main Authors:	Li Jinchao, Gao Fei, Lu Jiaguo, Tao Tingye
Format:	Article
Language:	English
Published:	De Gruyter 2019-11-01
Series:	Open Geosciences
Subjects:	sbas-insar disaster warning settlement prediction sentinel-1a gps
Online Access:	https://doi.org/10.1515/geo-2019-0058

id	doaj-206f95a4b6324037a38c43bfd01dfa0d
record_format	Article
spelling	doaj-206f95a4b6324037a38c43bfd01dfa0d2021-09-05T20:50:50ZengDe GruyterOpen Geosciences2391-54472019-11-0111173874910.1515/geo-2019-0058geo-2019-0058Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR modelLi Jinchao0Gao Fei1Lu Jiaguo2Tao Tingye3Hefei University of Technology, School of Civil and Hydraulic Engineering, Hefei, Anhui, ChinaHefei University of Technology, School of Civil and Hydraulic Engineering, Hefei, Anhui, ChinaThe 38th Research Institute of China Electronics Technology Group Corporation, Hefei, Anhui, ChinaHefei University of Technology, School of Civil and Hydraulic Engineering, Hefei, Anhui, ChinaUnderground coal mining activities often cause ground subsidence and damage to surface construction, which seriously threatens the lives and property of residents in mining areas. In this paper, the deformation of the Yang Juzhuang village, which is a residential area in the Huainan mining area (China), was monitored through an interferometric synthetic aperture radar (InSAR) time series analysis. The vertical displacements were detected using thirteen Sentinel-1A images that were acquired between December 2016 and May 2017. The validity and applicability of the method are verified by comparing the acquired images with the GPS measurement results. Because of the deformation characteristics of the mining area, a prediction model that is combined with a grey support vector machine regression (GM-SVR) is proposed, and the practical effects of the model are verified using the deformation monitoring results of the study area. The combination of this model and SBAS-InSAR provides rapid dynamic monitoring and enables the issuance of disaster warnings in the region.https://doi.org/10.1515/geo-2019-0058sbas-insardisaster warningsettlement predictionsentinel-1agps
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Li Jinchao Gao Fei Lu Jiaguo Tao Tingye
spellingShingle	Li Jinchao Gao Fei Lu Jiaguo Tao Tingye Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model Open Geosciences sbas-insar disaster warning settlement prediction sentinel-1a gps
author_facet	Li Jinchao Gao Fei Lu Jiaguo Tao Tingye
author_sort	Li Jinchao
title	Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model
title_short	Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model
title_full	Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model
title_fullStr	Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model
title_full_unstemmed	Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model
title_sort	deformation monitoring and prediction for residential areas in the panji mining area based on an insar time series analysis and the gm-svr model
publisher	De Gruyter
series	Open Geosciences
issn	2391-5447
publishDate	2019-11-01
description	Underground coal mining activities often cause ground subsidence and damage to surface construction, which seriously threatens the lives and property of residents in mining areas. In this paper, the deformation of the Yang Juzhuang village, which is a residential area in the Huainan mining area (China), was monitored through an interferometric synthetic aperture radar (InSAR) time series analysis. The vertical displacements were detected using thirteen Sentinel-1A images that were acquired between December 2016 and May 2017. The validity and applicability of the method are verified by comparing the acquired images with the GPS measurement results. Because of the deformation characteristics of the mining area, a prediction model that is combined with a grey support vector machine regression (GM-SVR) is proposed, and the practical effects of the model are verified using the deformation monitoring results of the study area. The combination of this model and SBAS-InSAR provides rapid dynamic monitoring and enables the issuance of disaster warnings in the region.
topic	sbas-insar disaster warning settlement prediction sentinel-1a gps
url	https://doi.org/10.1515/geo-2019-0058
work_keys_str_mv	AT lijinchao deformationmonitoringandpredictionforresidentialareasinthepanjiminingareabasedonaninsartimeseriesanalysisandthegmsvrmodel AT gaofei deformationmonitoringandpredictionforresidentialareasinthepanjiminingareabasedonaninsartimeseriesanalysisandthegmsvrmodel AT lujiaguo deformationmonitoringandpredictionforresidentialareasinthepanjiminingareabasedonaninsartimeseriesanalysisandthegmsvrmodel AT taotingye deformationmonitoringandpredictionforresidentialareasinthepanjiminingareabasedonaninsartimeseriesanalysisandthegmsvrmodel
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Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model

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