Position Inversion of Goafs in Deep Coal Seams Based on DS-InSAR Data and the Probability Integral Methods

Li, Tengteng; Zhang, Hongzhen; Fan, Hongdong; Zheng, Chunliu; Liu, Jiuli

doi:10.3390/rs13152898

Cited by 21 publications

(8 citation statements)

References 30 publications

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“…Based on the distribution function of the two datasets, the maximum value of the absolute value of the difference is made. It is analyzed that the random variables of DS points are stable under reparameterization [41]. The discriminant formula of the KS test can be expressed as…”

Section: Ds-insarmentioning

confidence: 99%

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

Zheng

Xie

He³

et al. 2022

Remote Sensing

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In recent years, the number of geological disasters in Sichuan Province has significantly increased due to the influence of earthquakes and extreme climate, as well as the disturbance to the geological environment by human activities. Thus, geological disaster monitoring is particularly important, which can provide some scientific basis for disaster prevention and reduction. In this paper, the interferometric synthetic aperture radar (InSAR) technology was introduced to monitor potential geological hazards, taking parts of Dujiangyan City, Wenchuan County, and Mao County in Sichuan Province, China as examples. Firstly, the data such as Sentinel-1A Terrain Observation with Progressive Scans (TOPS) Synthetic Aperture Radar (SAR) images and Precision Orbit Determination (POD) precise orbit ephemerides from 2018 to 2020, high-resolution optical satellite images and Digital Elevation Model (DEM) were collected. Secondly, the Differential InSAR (D-InSAR), Persistent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), Offset-Tracking, and Distributed Scatterer InSAR (DS-InSAR) algorithms were used to invert the surface deformation of the study area. Thirdly, according to the deformation results obtained by experiments, we used GF-1 and GF-2 optical images as a reference and combine the experimental results of InSAR algorithms to delineate the areas affected by geological disasters. A total of 49 geological disaster areas were obtained, mainly including landslides, collapses, and debris flow. Through field verification, the overall accuracy rate of InSAR deformation monitoring achieved 69.23%, and the accuracy rate of new potential hazards monitoring reached 63.64%. Among all InSAR methods, the DS-InSAR method outperformed and monitored the geological disaster areas well. Finally, the study area was divided into three elevation intervals and the applicability of different InSAR algorithms in different elevation intervals was discussed.

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Section: Ds-insarmentioning

confidence: 99%

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

Zheng

Xie

He³

et al. 2022

Remote Sensing

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“…Conventional methods cannot actually and intuitively illustrate the influence range of surface subsidence and the temporal and spatial evolution law of mining subsidence [38][39][40][41][42]. is reveals that the D-InSAR technique has the capability to reveal the minimal and large amount of land surface deformation observation data [43,44].…”

Section: Temporal and Spatial Analysismentioning

confidence: 99%

Deformation Monitoring and Spatiotemporal Evolution of Mining Area with Unmanned Aerial Vehicle and D-InSAR Technology

Tan

Zhu

et al. 2022

Mobile Information Systems

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The extraction of underground mineral sources has a significant negative impact on the local environment, results in land surface subsidence. As far as subsidence monitoring technology is concerned, leveling is the most accurate. However, leveling can only obtain discrete point data but not the whole area information of the subsidence basin. In this study, Differential Interferometric Synthetic Aperture Radar (D-InSAR) combined with Unmanned Aerial Vehicle (UAV) technology is used to study the subsidence characteristics of the whole working panel. In this analysis, the Huainan mining area is tested as a research area; measured data are compared to the elevation accuracy of the Digital Surface Model (DSM) data, which can be considered for the subsequent works of the mining area. Based on the subsidence affected area, the ground object-type information is recorded to provide basic information for the ecological restoration work after mining so that the data before and after mining can be obtained synchronously. Finally, the differential interference results and Digital Orthophoto Map (DOM) data are combined to assess the spatiotemporal evolution of working panel subsidence and its influence on surface features. The main novelty of the proposed work is combining UAV and D-InSAR to get more accurate analysis of mining subsidence. It can be done using the proposed method.

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“…Additionally, the phase unwrapping (PhU) consistency index threshold (set to 0.8 in this work) is used to determine the output mask of MP and generate the deformation products [38], [40]. After determining the linear deformation, the nonlinear deformation, noise phase and atmospheric phase are separated from the residual phase by temporal-spatial filtering algorithm [41].…”

Section: Estimating Deformation At Reliable Pixelsmentioning

confidence: 99%

An Improved Method for Phase Triangulation Algorithm Based on the Coherence Matrix Eigen-Decomposition in Time-Series SAR Interferometry

He²,

Zhuang

et al. 2021

IEEE Access

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Time-series SAR interferometry, which combines permanent scatterers (PSs) and distributed scatterers (DSs), has been strongly developed in recent years. Unlike PS, DS corresponds to a natural target whose neighboring pixels share similar reflectivity values. The selection of DS is relevant to the goodnessof-fit value, the estimation of which is based on all possible combined interferometric phases and fails to avoid the adverse effect of low-quality phases. This paper used eigen-decomposition of coherence matrix that constructed based on the identified homogeneous pixels to perform phase optimization, and then only the interferometric phases with low noise and clear fringes are utilized to measure the goodness-of-fit. 30 Sentinel-1A images were applied to test the improved method of land subsidence monitoring in Beijing, China. The deformation results of different methods were cross verified and the area statistics of the study area were carried out. The results show that the maximum subsidence monitored by the improved method is located in Jinzhan Town with a maximum rate of -109 mm/yr. This improved method extracts more measurement points with accuracy ensured, which is proved to be an effective way to provide the high spatial density of deformation measurements. The land subsidence in this area is mainly caused by the excessive exploitation of groundwater resources. This research provides support for the prevention and control work of relevant departments.

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Position Inversion of Goafs in Deep Coal Seams Based on DS-InSAR Data and the Probability Integral Methods

Cited by 21 publications

References 30 publications

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

Deformation Monitoring and Spatiotemporal Evolution of Mining Area with Unmanned Aerial Vehicle and D-InSAR Technology

An Improved Method for Phase Triangulation Algorithm Based on the Coherence Matrix Eigen-Decomposition in Time-Series SAR Interferometry

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