Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements

Determining the geographic location and spatial distribution of underground goaf is of great significance for the prevention of mining subsidence hazards and the detection of illegal mining. However, traditional goaf detection techniques mainly focus on geophysical methods that are labor intensive,...

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Main Authors: Weihao Zhang, Jiancun Shi, Huiwei Yi, Yan Zhu, Bing Xu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Remote Sensing
Subjects:
PIM
Online Access:https://www.mdpi.com/2072-4292/13/16/3204
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spelling doaj-b4366581359640e2a7db3178cf02b3bb2021-08-26T14:17:38ZengMDPI AGRemote Sensing2072-42922021-08-01133204320410.3390/rs13163204Underground Goaf Parameters Estimation by Cross-Iteration with InSAR MeasurementsWeihao Zhang0Jiancun Shi1Huiwei Yi2Yan Zhu3Bing Xu4School of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaDetermining the geographic location and spatial distribution of underground goaf is of great significance for the prevention of mining subsidence hazards and the detection of illegal mining. However, traditional goaf detection techniques mainly focus on geophysical methods that are labor intensive, have low efficiency, and are expensive. Due to the large range and off-site monitoring capability of interferometric synthetic aperture radar (InSAR) techniques, research on goaf location detection based on InSAR measurements has been increasing. This paper proposes a new method for locating underground goaf based on cross-iteration and InSAR measurements. Firstly, the functional relationship between the geometric parameters of the goaf and the line of sight (LOS) deformation retrieved by InSAR techniques is constructed. Then, the three initial model parameters of the probability integration method (PIM) are determined by mining geological conditions. Finally, the cross-iteration method is used to determine the parameters to characterize the spatial location of underground goaf. The experimental results show that the average relative errors of the simulated experiment and the real experiment are 1.5% and 5.1%, respectively, and the inverted goaf parameters are in good agreement with the real values. Moreover, the proposed method only requires the main lithology of the overlying rock in the goaf and does not depend on the accuracy of PIM model parameters. Therefore, this method has engineering application value for the detection of goaf lacking actual measurement data or that caused by illegal mining.https://www.mdpi.com/2072-4292/13/16/3204InSARPIMcross-iterationpositioning of underground goaf
collection DOAJ
language English
format Article
sources DOAJ
author Weihao Zhang
Jiancun Shi
Huiwei Yi
Yan Zhu
Bing Xu
spellingShingle Weihao Zhang
Jiancun Shi
Huiwei Yi
Yan Zhu
Bing Xu
Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
Remote Sensing
InSAR
PIM
cross-iteration
positioning of underground goaf
author_facet Weihao Zhang
Jiancun Shi
Huiwei Yi
Yan Zhu
Bing Xu
author_sort Weihao Zhang
title Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
title_short Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
title_full Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
title_fullStr Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
title_full_unstemmed Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
title_sort underground goaf parameters estimation by cross-iteration with insar measurements
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-08-01
description Determining the geographic location and spatial distribution of underground goaf is of great significance for the prevention of mining subsidence hazards and the detection of illegal mining. However, traditional goaf detection techniques mainly focus on geophysical methods that are labor intensive, have low efficiency, and are expensive. Due to the large range and off-site monitoring capability of interferometric synthetic aperture radar (InSAR) techniques, research on goaf location detection based on InSAR measurements has been increasing. This paper proposes a new method for locating underground goaf based on cross-iteration and InSAR measurements. Firstly, the functional relationship between the geometric parameters of the goaf and the line of sight (LOS) deformation retrieved by InSAR techniques is constructed. Then, the three initial model parameters of the probability integration method (PIM) are determined by mining geological conditions. Finally, the cross-iteration method is used to determine the parameters to characterize the spatial location of underground goaf. The experimental results show that the average relative errors of the simulated experiment and the real experiment are 1.5% and 5.1%, respectively, and the inverted goaf parameters are in good agreement with the real values. Moreover, the proposed method only requires the main lithology of the overlying rock in the goaf and does not depend on the accuracy of PIM model parameters. Therefore, this method has engineering application value for the detection of goaf lacking actual measurement data or that caused by illegal mining.
topic InSAR
PIM
cross-iteration
positioning of underground goaf
url https://www.mdpi.com/2072-4292/13/16/3204
work_keys_str_mv AT weihaozhang undergroundgoafparametersestimationbycrossiterationwithinsarmeasurements
AT jiancunshi undergroundgoafparametersestimationbycrossiterationwithinsarmeasurements
AT huiweiyi undergroundgoafparametersestimationbycrossiterationwithinsarmeasurements
AT yanzhu undergroundgoafparametersestimationbycrossiterationwithinsarmeasurements
AT bingxu undergroundgoafparametersestimationbycrossiterationwithinsarmeasurements
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