Analysis of ground subsidence in coal mining area using SAR interferometry

Baek, Jin; Kim, Sang Wan; Park, Hyuck‐Jin; Jung, Hyung-Sup; Kim, Ki-Dong; Kim, Jeong Woo

doi:10.1007/s12303-008-0028-3

Cited by 63 publications

(34 citation statements)

References 14 publications

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“…이미 국내외에서 차분간섭기법을 이용한 폐광산 또 는 가행중인 광산의 지표변위에 대한 연구가 진행된 바 있다 (Jung et al, 2004;Chang et al, 2007;Baek et al, 2008;Wright and Stow, 1997 (Berardino et al, 2002). (Fig.…”

Section: 서 론unclassified

Analysis of Ground Subsidence using ALOS PALSAR (2006~2010) in Taebaek, Kangwon

Cho¹,

Kim²

2012

Economic and Environmental Geology

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We performed DInSAR (Differential Interferometric SAR) and SBAS (Small BAseline Subset) analysis using spaceborne SAR (Synthetic Aperture Radar) in order to detect a surface subsidence in Taebaek area, Kangwon, which are suitable to the monitoring of broad and inaccessible areas. During the period from October 2006 to June 2010, we acquired twenty-three ALOS PALSAR data sets (path/frame=425/730) for this study. The ninety-six differential interferograms with a perpendicular baseline less than 1100 m were constructed by ROI_PAC, then the mean velocity map of surface displacement was derived from SBAS analysis. As a result, it was confirmed that the ground displacement occurred about 4 cm/yr at Seokgong-Jangseong and Kyungdong mines and 2 cm/yr at SaehanEoryong-Jungdong and Hwangji mines in Taebaek area, Kangwon. It seems that the subsidence in study area is closely related to mining activities because the most of subsiding areas are well matched with mining areas. The subsidence at Kyungdong mine shows continuous and fast velocity in about 2 × 2 km area. Therefore the further analysis and the effort to prevent disaster are required in this area.

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Section: 서 론unclassified

Analysis of Ground Subsidence using ALOS PALSAR (2006~2010) in Taebaek, Kangwon

Cho¹,

Kim²

2012

Economic and Environmental Geology

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“…To overcome the above-mentioned limit of the TS-InSAR techniques, a strategy which first estimates the mean deformation between two time-adjacent SAR acquisitions and then integrates them to determine the time-series deformation has been proposed [13][14][15]. It is an alternative strategy for deriving ground surface time-series deformation with a highly nonlinear behavior.…”

Section: Introductionmentioning

confidence: 99%

Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model

et al. 2017

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Abstract:The seasonal variation of land cover and the large deformation gradients in coal mining areas often give rise to severe temporal and geometrical decorrelation in interferometric synthetic aperture radar (InSAR) interferograms. Consequently, it is common that the available InSAR pairs do not cover the entire time period of SAR acquisitions, i.e., temporal gaps exist in the multi-temporal InSAR observations. In this case, it is very difficult to accurately estimate mining-induced dynamic subsidence using the traditional time-series InSAR techniques. In this investigation, we employ a logistic model which has been widely applied to describe mining-related dynamic subsidence, to bridge the temporal gaps in multi-temporal InSAR observations. More specifically, we first construct a functional relationship between the InSAR observations and the logistic model, and we then develop a method to estimate the model parameters of the logistic model from the InSAR observations with temporal gaps. Having obtained these model parameters, the dynamic subsidence can be estimated with the logistic model. Simulated and real data experiments in the Datong coal mining area, China, were carried out in this study, in order to test the proposed method. The results show that the maximum subsidence in the Datong coal mining area reached about 1.26 m between 1 July 2007 and 28 February 2009, and the accuracy of the estimated dynamic subsidence is about 0.017 m. Compared with the linear and cubic polynomial models of the traditional time-series InSAR techniques, the accuracy of dynamic subsidence derived by the logistic model is increased by about 50.0% and 45.2%, respectively.

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“…However, besides widespread application in monitoring general landscape dynamics, the application of RS and GIS in monitoring and assessing mining effects on landscapes and environment and in associated geological changes and vegetation productivity dynamics is limited [10][11][12][13][14]20]. Although high-resolution Light Amplification by Stimulated Emission of Radiation (LASER), Interferometric Synthetic Aperture Radar (InSAR), and Light Detection and Ranging (LIDAR) mapping have been sparsely applied in small areas, environmental impacts in large mine reclamation areas have rarely been investigated using RS and GIS techniques [21][22][23][24][25][26][27]. Regular landscape management and monitoring at the surface level are crucial for the prevention of subsidence and development of early warning systems in a reclaimed mine area (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area

Padmanaban

Bhowmik

Cabral

2017

IJGI

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Abstract:Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e., subsidence, and degradation of vegetation productivity. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyze land-use and landcover dynamics, and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation productivity using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within four years, with 87.2% growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that the productivity of 66.5% of vegetation of the Kirchheller Heide was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.

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Analysis of ground subsidence in coal mining area using SAR interferometry

Cited by 63 publications

References 14 publications

Analysis of Ground Subsidence using ALOS PALSAR (2006~2010) in Taebaek, Kangwon

Analysis of Ground Subsidence using ALOS PALSAR (2006~2010) in Taebaek, Kangwon

Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model

A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area

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