Detecting and Analyzing the Evolution of Subsidence Due to Coal Fires in Jharia Coalfield, India Using Sentinel-1 SAR Data

Riyas, Moidu Jameela; Syed, Tajdarul H.; Kumar, Hrishikesh; Kuenzer, Claudia

doi:10.3390/rs13081521

Cited by 15 publications

(2 citation statements)

References 73 publications

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“…Land subsidence, caused by both natural and anthropogenic processes, is a widespread phenomenon [1,2]. Land subsidence resulting from overexploitation of groundwater aquifers is common worldwide [3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport

Zheng,

Peng,

et al. 2024

Remote Sensing

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Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution mechanism. Beijing Capital International Airport (BCIA) has experienced uneven land subsidence since 1935, together with severe fissures significantly affecting its normal operations. In this study, the time-series InSAR method was successfully applied to monitor the gradual increase in uneven local subsidence and ground fissures activity at BCIA from June 2003 to March 2023. Initially, ENVISAT-ASAR, Cosmo-SkyMed, and Sentinel-1 data were processed by time-series InSAR techniques to generate deformation rate maps and time series for the airport area. Subsequently, a comparison was made between the displacement time series from InSAR and ground leveling measurements to assess the accuracy of InSAR-derived measurements. Through a comprehensive analysis of the distribution characteristics of land subsidence at the airport, a long-standing ground fault was located within the airport was identified. A preliminary discussion on the development status of this ground fissure was carried out based on the visual interpretation of optical images. Lastly, the inducing factors and evolutionary conditions of land subsidence were discussed. This case demonstrates the applicability of InSAR technology in identifying and monitoring geological processes such as land subsidence and ground fissure activities. It provides a scientific approach to exploring and studying the causes and formation mechanisms of land subsidence and ground fissures in the Beijing Capital Airport area.

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Section: Introductionmentioning

confidence: 99%

Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport

Zheng,

Peng,

et al. 2024

Remote Sensing

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“…The combustion caused by such fires consumes a large amount of coal. It can lead to the formation of an underground combustion goaf that renders the area susceptible to geological accidents, such as landslides, structural collapse, and fissures [3,4]. The combustion of coal releases toxic gases and emits a large amount of heat that degrades the ecological environment [5,6].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Surface Subsidence Using Distributed Scatterer InSAR with an Improved Statistically Homogeneous Pixel Selection Method in Coalfield Fire Zones

Tian

Fan

Cao³

et al. 2023

Remote Sensing

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Statistically homogeneous pixel (SHP) selection is an important process in the distributed scatterer interferometric synthetic aperture radar (DS-InSAR) approach. However, prevalent methods struggle to appropriately balance the efficiency and accuracy of selection. To solve this problem, the authors of this study improved the Hypothesis Test of Confidence Interval (HTCI) to propose an adaptive method to select the level of saliency and confidence interval for the HTCI, called Adp-HTCI. The proposed method can accurately select homogeneous pixels while inheriting the high efficiency of the HTCI. Once homogeneous pixels have been chosen, the eigenvalue decomposition of the covariance matrix is used to optimize their phase and perform temporal processing. We used the proposed method along with data on 31 scenes from the Sentinel-1 satellite from 2 June 2021 to 28 May 2022 to monitor the deformation of the surface of the fire zone in the Sikeshu coalfield. The selection results of homogeneous pixels indicate that the proposed Adp-HTCI algorithm can increase the number of selected homogeneous pixels while ensuring the accuracy of the selection results, thereby enhancing the estimation accuracy and reliability of subsequent parameter solving. The DS-InSAR results showed that the cumulative maximum subsidence in the study area within a year reached—138 mm and the point density used by the DS-InSAR approach was 17.28 times higher than that used by the StaMPS approach. The results of cross-analysis with the results of StaMPS verified the accuracy of the DS-InSAR-based approach.

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Fire safety assessment models based on machine learning methods for the coal industry

Sun¹,

Gura²,

Dong³

2022

Chemometrics and Intelligent Laboratory Systems

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Detecting and Analyzing the Evolution of Subsidence Due to Coal Fires in Jharia Coalfield, India Using Sentinel-1 SAR Data

Cited by 15 publications

References 73 publications

Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport

Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport

Monitoring Surface Subsidence Using Distributed Scatterer InSAR with an Improved Statistically Homogeneous Pixel Selection Method in Coalfield Fire Zones

Fire safety assessment models based on machine learning methods for the coal industry

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