Multi-sensor remote sensing analysis of coal fire induced land subsidence in Jharia Coalfields, Jharkhand, India

The subsidence in coal mines induced by surface and subsurface fires leading to roof collapse, infrastructure loss, and loss of lives is a prominent concern. In the study, satellite imagery from thermal and microwave remote sensing data is used to deduce the effect of coal fires on subsidence in the Jharia Coalfields, India. The Thermal Infrared data acquired from the Landsat-8 (band 10) is used to derive the temperature anomaly maps. Persistent Scatterer Interferometry analysis was performed on sixty Sentinel-1, C-band images, the results are corrected for atmospheric error using Generic Atmospheric Correction Online Service for InSAR (GACOS) atmospheric modelling data and decomposed into vertical displacement values to quantify subsidence. A zone-wise analysis of the hazard patterns in the coalfields was carried out. Coal fire maps, subsidence velocity maps, and land cover maps were integrated to investigate the impact of the hazards on the mines and their surroundings. Maximum subsidence of approximately 20 cm/yr. and temperature anomaly of up to 25 °C has been observed. The findings exhibit a strong positive correlation between the subsidence velocity and temperature anomaly in the study area. Kusunda, Keshalpur, and Bararee collieries are identified as the most critically affected zones. The subsidence phenomenon in some collieries is extending towards the settlements and transportation networks and needs urgent intervention. © 2021 The Author

Ground motion in areas of abandoned mining: application of the intermittent SBAS (ISBAS) to the Northumberland and Durham coalfield, UK

In this paper, we investigate land motion and groundwater level change phenomena using differential interferometric synthetic aperture radar (DInSAR) over the Northumberland and Durham coalfield in the United Kingdom. The study re-visits earlier research that applied a persistent scatterers interferometry (PSI) technique to ERS (European Remote Sensing) and ENVISAT (Environmental Satellite) data. Here, the Intermittent Small Baseline Subset (ISBAS) DInSAR technique is applied to ERS, ENVISAT and Sentinel-1 SAR datasets covering the late 1990s, the 2000s and the mid-2010s, respectively to increase spatial coverage, aid the geological interpretation and consider the latest Sentinel-1 data. The ERS data identify surface depressions in proximity to former collieries, while all three data sets ascertain broad areas are experiencing regional scale uplift, often occurring in previously mined areas. Uplift is attributed to increases in pore pressure in the overburden following the cessation of groundwater pumping after mine closure. Rising groundwater levels are found to correlate to ground motion measurements at selected monitoring sites, most notably in the surrounding area of Ashington. The area is divided by an impermeable EW fault; to the south, surface heave was identified as groundwater levels rose in the 1990s, whereas to the north, this phenomenon occurred two decades later in the 2010s. The data emphasize the complexity of the post-mining surface and subsurface environment and highlight the benefit that InSAR, utlizing the ISBAS technique, can provide in its charaterization

First Results from Sentinel-1A InSAR over Australia: Application to the Perth Basin

Past ground-based geodetic measurements in the Perth Basin, Australia, record small-magnitude subsidence (up to 7 mm/y), but are limited to discrete points or traverses across parts of the metropolitan area. Here, we investigate deformation over a much larger region by performing the first application of Sentinel-1A InSAR data to Australia. The duration of the study is short (0.7 y), as dictated by the availability of Sentinel-1A data. Despite this limited observation period, verification of Sentinel-1A with continuous GPS and independent TerraSAR-X provides new insights into the deformation field of the Perth Basin. The displacements recorded by each satellite are in agreement, identifying broad (>5 km wide) areas of subsidence at rates up to 15 mm/y. Subsidence at rates greater than 20 mm/y over smaller regions ( 2 km wide) is coincident with wetland areas, where displacements are temporally correlated with changes in groundwater levels in the unconfined aquifer. Longer InSAR time series are required to determine whether these measured displacements are representative of long-term deformation or (more likely) seasonal variations. However, the agreement between datasets demonstrates the ability of Sentinel-1A to detect small-magnitude deformation over different spatial scales (from 2 km–10 s of km) in the Perth Basin. We suggest that, even over short time periods, these data are useful as a reconnaissance tool to identify regions for subsequent targeted studies, particularly given the large swath size of radar acquisitions, which facilitates analysis of a broader portion of the deformation field than ground-based methods or single scenes of TerraSAR-X

Multitemporal monitoring of Karvina subsidence troughs using Sentinel-1 and TerraSar-X interferometry

Satellite SAR interferometry (InSAR) allows to observe borders of subsidence troughs created in undermined areas. There is a possibility to evaluate a subsidence velocity in the accuracy of a mm/year for the stable reflectors of the radio signal, e.g. buildings. We apply Permanent Scatterers (PS) and Quasi-PS (QPS) techniques for monitoring of mine-caused subsidence in the Karvina area situated in the Czech part of Upper Silesian Basin. We use PS technique as effective for observation of displacements of built structures (e.g. buildings) and QPS for monitoring of spatio-temporal development of subsidence troughs. The results reveal information valuable for an identification of deviations from expected effects of mining activities on the land surface and for the infrastructure which are potentially affected by the subsidence. We perform the processing of Sentinel-1 and high resolution TerraSAR-X to find how the lower spatial resolution of Sentinel-1 SAR affects the reliability of results. The assets of these new sensors, especially the short revisit time, can overcome the basic limits of InSAR methods connected with temporal lags between available SAR images. In previous Karvina area datasets (ERS, Envisat, Alos satellites) the basic temporal step used to be around one month. During such temporal length significant changes occured in vegetation cover or in cultivated soil causing a loss of coherence of radar measurements. In addition to this, the amount of subsidence of Karvina troughs has often exceeded detection limits of the SAR systems. A significant increase of the reliability of evaluated subsidence also in areas with a moderate vegetation cover is expected with the launch of Sentinel-1B since the short-term interferograms would not be affected by a full decorrelation.Web of Science141595

Modelling groundwater rebound in recently abandoned coalfields using DInSAR

Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make a significant cost-effective contribution to the progressive abandonment strategy of recently closed coalfields. Applications of DInSAR over coalfields have observed heave in coal measures rocks and temporal correlations between the rise of mine water and deformation time-series. The cessation of systematic dewatering can have a variety of detrimental impacts and knowledge of the time-scales (i.e. the rate of rebound) and structure of the mine system are crucial to the remediation strategy. Although mine plans and borehole measurements provide vital information in this regard, mine plans are often incomplete or inaccurate, whereas monitoring boreholes are spatially sparse. Consequently, groundwater can flow in unanticipated directions via goaf, mine shafts and roadways, making it difficult to determine where the impacts of rebound are likely to occur. In this study, ground deformation data obtained using ISBAS DInSAR on ENVISAT (2002–2009) and Sentinel-1 (2015–2019) data are used to develop a simple method to model groundwater rebound in abandoned coalfields. A forward analytical model based upon the principle of effective stress and mine water ponds is first implemented to estimate surface heave in response to changes in groundwater levels measured in monitoring boreholes. The forward model is then calibrated and validated using the ground deformation data. The DInSAR data were subsequently inverted to map the change in groundwater levels in greater detail across the coalfield and forecast surface discharges in order to support mitigation strategies

Land Subsidence Detection and Monitoring Using InSAR in Australia

The land surface is under constant movement in both horizontal and vertical directions. In some extreme circumstances there can be a sudden and significant subsidence event occur. These can be attributed to natural movement through earthquakes or through human intervention through extractive industries. Where these events occur, they can cause significant damage to the public infrastructure, housing and interruption to the people who live there. In some locations throughout Australia the disused underground mine sites are being developed into housing developments, particularly those close to urban areas such as Collingwood Park, Queensland. In the past in these there have been subsidence events occur and result in significant cost to the Government in damages. Due to the high costs incurred with traditional monitoring techniques it has been cost prohibitive to provide ongoing monitoring to areas, where these events occur with long time periods separating the events. In more recent times through an increase of earth observation satellites with onboard Synthetic Aperture Radar (SAR) sensors have decreased the time period of acquisition. This has improved the results and reliability of the remote sensing technique known as Differential Interferometric Synthetic Aperture Radar (DInSAR). Therefore, making ongoing monitoring of these areas more economical which provides a significant benefit to these areas for ongoing monitoring. This project conducted research into the detection and monitoring of Collingwood Park, Queensland located west of the city of Brisbane using the DInSAR technique. This site was chosen due to it having historically experienced subsidence events due to the collapse of the decommissioned underground mine. Due to its location it is an area where this type of research could be of great benefit and has the potential to provide the desired results. The project used several data sets between the period of November 2015 to December 2018 acquired by the Sentinel 1A satellite which is part of the broader earth observation mission Copernicus. These data sets were obtained through Alaskan Satellite Facility Vertex system. The generated results indicate that no significant subsidence event had occurred during this time period and the area remained reasonably stable to June 2018. The results for the time period June 2018 to December 2018 do indicate some parts of the suburb had experienced some movement averaging around 0.008 meters of uplift for that area. Upon further processing it was indicated that this had occurred somewhere in the period of October to December 2018, this result was surprising as any movement in the area was expected to be subsidence

Estimating Land Subsidence and Gravimetric Anomaly Induced by Aquifer Overexploitation in the Chandigarh Tri-City Region, India by Coupling Remote Sensing with a Deep Learning Neural Network Model

This study utilizes surface displacement data from Persistent Scatterer SAR Interferometry (PSInSAR) of Sentinel-1 satellite and groundwater storage change data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to understand land subsidence in the Chandigarh tri-city region. The satellite datasets are used along with the groundwater level data obtained from wells over the study area. Since the GRACE data are available at a much coarser spatial resolution of 1o by 1o, challenges remain in correlating the dataset with PSInSAR displacement that has been multi-looked at 14 m by 14 m resolution. Therefore, multiple sources of data (i.e., the monthly average of GRACE data, groundwater storage change and monthly average PSInSAR displacement per pixel, and interpolated groundwater level data from wells for 2017 to 2022) have been deployed into a deep learning multi-layer perceptron (DLMLP) model to estimate the groundwater storage change at the urban level. This has an indirect downscaling method that is carried out successfully using the DLMLP model for the estimation of groundwater storage changes at the urban level, which is usually complicated by applying direct downscaling methods on the GRACE data. Thus, the DLMLP model developed here is a distinctive approach considered for estimating the changes in groundwater storage using PSInSAR displacement, groundwater data from wells, and GRACE data. The DLMLP model gives an R2-statistics value of 0.91 and 0.89 in the training and testing phases, respectively, and has a mean absolute error (MAE) of 1.23 and root mean square error (RMSE) of 0.87

Integration of Synthetic Aperture Radar Interferometry (InSAR) and Geographical Information Systems (GIS) for monitoring mining induced surface deformations

Surface subsidence induced by mining is a source of risk to people, equipment and environment. It may also disrupt mining schedules and increase the cost of mine safety. To provide accurate assessment of the surface subsidence and its level of impact on mine production and environment, it is necessary to develop and introduce comprehensive subsidence monitoring systems. Current techniques for monitoring of surface deformation are usually based on classical survey principles. In general these techniques have disadvantages that limit their applicability: they follow point-by-point data collection techniques, they are relatively time-consuming and costly, they usually cover only a small area, they are not applicable for the monitoring of inaccessible areas and they are not able to collect data continuously.As a complementary or alternative technique, the thesis discusses the applicability of SAR interferometry for monitoring mining induced deformations. InSAR is a remote sensing technique that makes use of Synthetic Aperture Radar (SAR) observations to acquire change in terrain topography. In spite of the widespread application of the technique for monitoring large-scale deformations of the Earth crust, specific modifications are necessary for utilising the technology within a mining context. Limitations, such as difficulty to resolve deformation for a high gradient slope, difficulty to retrieve subsidence for localised highly dynamic ground movements and the unavailability of SAR images with the desired specifications restrict the potential to monitor high rate, localised mine subsidence on day-to-day basis.The secondary aim of the thesis is to present integration of InSAR and GIS in order to propose an optimum methodology for processing of InSAR data to determine mine subsidence. The presented research also involves detailed analysis of InSAR limitations. This in consequence has led to suggestions on how to improve current InSAR capability with respect to the mining needs.The thesis introduces a set of new GIS-based tools and methodologies that are integrated into a conventional InSAR processing technique, to further improve and facilitate application of InSAR in mining. The developed tools and techniques cover the three main stages of data processing (pre-processing, processing and postprocessing). The researcher tried to address InSAR.’s limitations associated with mining related applications and also to provide practical solutions to resolve these issues

Monitoring land subsidence of airport using InSAR time-series techniques with atmospheric and orbital error corrections

Land subsidence is one of the common geological hazards worldwide and mostly caused by human activities including the construction of massive infrastructures. Large infrastructure such as airport is susceptible to land subsidence due to several factors. Therefore, monitoring of the land subsidence at airport is crucial in order to prevent undesirable loss of property and life. Remote sensing technique, especially Interferometric Synthetic Aperture Radar (InSAR) has been successfully applied to measure the surface deformation over the past few decades although atmospheric artefact and orbital errors are still a concerning issue in this measurement technique. Multi-temporal InSAR, an extension of InSAR technique, uses large sets of SAR scenes to investigate the temporal evolution of surface deformation and mitigate errors found in a single interferogram. This study investigates the long-term land subsidence of the Kuala Lumpur International Airport (KLIA), Malaysia and Singapore Changi Airport (SCA), Singapore by using two multi-temporal InSAR techniques like Small Baseline Subset (SBAS) and Multiscale InSAR Time Series (MInTS). General InSAR processing was conducted to generate interferogram using ALOS PALSAR data from 2007 until 2011. Atmospheric and orbital corrections were carried out for all interferograms using weather model, namely European Centre for Medium Range Weather Forecasting (ECMWF) and Network De-Ramping technique respectively before estimating the time series land subsidence. The results show variation of subsidence with respect to corrections (atmospheric and orbital) as well as difference between multi-temporal InSAR techniques (SBAS and MInTS) used. After applying both corrections, a subsidence ranging from 2 to 17 mm/yr was found at all the selected areas at the KLIA. Meanwhile, for SCA, a subsidence of about less than 10 mm/yr was found. Furthermore, a comparison between two techniques (SBAS and MInTS) show a difference rate of subsidence of about less than 1 mm/yr for both study area. SBAS technique shows more linear result as compared to the MInTS technique which shows slightly scattering pattern but both techniques show a similar trend of surface deformation in both study sites. No drastic deformation was observed in these two study sites and slight deformation was detected which about less than 20mm/yr for both study areas probably occurred due to several reasons including conversion of the land use from agricultural land, land reclamation process and also poor construction. This study proved that InSAR time series surface deformation measurement techniques are useful as well as capable to monitor deformation of large infrastructure such as airport and as an alternative to costly conventional ground measurement for infrastructure monitoring

Doctor of Philosophy

dissertationDifferential Interferometric Synthetic Aperture Radar (DInSAR), a satellite-based remote sensing technique, is a practical method for measuring deformation of the earth's surface. In this investigation, the application of DInSAR for monitoring mine subsidence was evaluated for active underground mining regions in the Green River Basin in southwest Wyoming and the Wasatch Plateau in central Utah. Interferograms were generated using X-band (3-cm wavelength) Synthetic Aperture Radar data from the TerraSAR-X mission and L-band (24-cm wavelength) Synthetic Aperture Radar data from the Advanced Land Observing Satellite. In general, the DInSAR data have high spatial and temporal resolutions and show gradual, progressive subsidence. In the Green River Basin, displacements were estimated using both L-band and X-band data. In the Wasatch Plateau, displacements were only estimated using L-band data; areas affected by subsidence are identifiable in the X-band data, but precisely quantifying subsidence magnitudes is difficult as a result of significant phase noise. In the Green River Basin, the maximum subsidence magnitude was 150 cm over 690 days, estimated using L-band DInSAR. In the Wasatch Plateau, the maximum subsidence magnitude was 180 cm over 414 days. In both regions, as a result of low coherence in the areas with large displacements, the maximum displacements may be underestimated by tens of centimeters. Additionally, relationships between surface deformations measured by DInSAR and mining-induced seismicity (MIS) in the Green River Basin and the Wasatch Plateau were explored. Both regions exhibit large magnitude, relatively rapid subsidence, but the characteristics (rates and magnitudes) of MIS in the Wasatch Plateau study region and the Green River Basin are significantly different. In the Wasatch Plateau study region, surface displacements tend to precede seismicity, event rates tend to be high, and event magnitudes tend to be relatively low. In the Green River Basin, seismicity spatially correlates with surface displacements, but only over long periods. Seismic events tend to be relatively large in magnitude and the event rate tends to be low. Further investigations of differences in the seismic characteristics in the Wasatch Plateau and the Green River Basin and of the dependence of MIS and subsidence on regional geologic and mining parameters are warranted