Differential interferometry techniques on l-band data employed for the monitoring of surface subsidence due to mining

Mining activities in South Africa changes the natural environment in several ways. Challenges for mining companies lie in the detection and monitoring of surface subsidence and there exists a need for a long term monitoring system. Field-based techniques for deformation measurement are labour intensive and time consuming and, consequently, the implementation of these techniques for long-term monitoring is not ideal. On the other hand, satellite remote sensing data provides a synoptic view of an area and the repeat image acquisition strategy implies that the long-term monitoring of surface deformation is a possibility. This paper investigates the use of L-band ALOS PALSAR data for the detection and monitoring of surface subsidence due to underground mining activities in the Witbank Coalfields. Surface subsidence was detected for a period of over 3 years between 2007/08/16 and 2010/10/09. Centimetre scale surface deformation was detected in the study area and is associated with areas of active mining. The systematic evolution of the surface deformation basins over time was recognised and is consistent with the advance of the working face of the mine during the same period. The results confirm that L-band synthetic aperture radar data through dInSAR techniques can be used for the long-term monitoring of surface subsidence associated with mining activities

Parameters affecting interferometric coherence and implications for long-term operational monitoring of mining-induced surface deformation

Includes abstract.Includes bibliographical references.Surface deformation due to underground mining poses risks to health and safety as well as infrastructure and the environment. Consequently, the need for long-term operational monitoring systems exists. Traditional field-based measurements are point-based meaning that the full extent of deforming areas is poorly understood. Field-based techniques are also labour intensive if large areas are to be monitored on a regular basis. To overcome these limitations, this investigation considered traditional and advanced differential radar interferometry techniques for their ability to monitor large areas over time, remotely. An area known to be experiencing mining induced surface deformation was used as test case. The agricultural nature of the area implied that signal decorrelation effects were expected. Consequently, four sources of data, captured at three wavelengths by earth-orbiting satellites were obtained. This provided the opportunity to investigate different phase decorrelation effects on data from standard imaging platforms using real-world deformation phenomenon as test-case. The data were processed using standard dInSAR and polInSAR techniques. The deformation measurement results together with an analysis of parameters most detrimental to long-term monitoring were presented. The results revealed that, contrary to the hypothesis, polInSAR techniques did not provide an enhanced ability to monitor surface deformation compared to dInSAR techniques. Although significant improvements in coherence values were obtained, the spatial heterogeneity of phase measurements could not be improved. Consequently, polInSAR could not overcome ecorrelation associated with vegetation cover and evolving land surfaces. However, polarimetric information could be used to assess the scattering behaviour of the surface, thereby guiding the definition of optimal sensor configuration for long-term monitoring. Despite temporal and geometric decorrelation, the results presented demonstrated that mining-induced deformation could be measured and monitored using dInSAR techniques. Large areas could be monitored remotely and the areal extent of deforming areas could be assessed, effectively overcoming the limitations of field-based techniques. Consequently, guidelines for the optimal sensor configuration and image acquisition strategy for long-term operational monitoring of mining-induced surface deformation were provided

Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain

Subsidence related to multiple natural and human-induced processes affects an increasing number of areas worldwide. Although this phenomenon may involve surface deformation with 3D displacement components, negative vertical movement, either progressive or episodic, tends to dominate. Over the last decades, differential SAR interferometry (DInSAR) has become a very useful remote sensing tool for accurately measuring the spatial and temporal evolution of surface displacements over broad areas. This work discusses the main advantages and limitations of addressing active subsidence phenomena by means of DInSAR techniques from an end-user point of view. Special attention is paid to the spatial and temporal resolution, the precision of the measurements, and the usefulness of the data. The presented analysis is focused on DInSAR results exploitation of various ground subsidence phenomena (groundwater withdrawal, soil compaction, mining subsidence, evaporite dissolution subsidence, and volcanic deformation) with different displacement patterns in a selection of subsidence areas in Spain. Finally, a cost comparative study is performed for the different techniques applied.The different research areas included in this paper has been supported by the projects: CGL2005-05500-C02, CGL2008-06426-C01-01/BTE, AYA2 010-17448, IPT-2011-1234-310000, TEC-2008-06764, ACOMP/2010/082, AGL2009-08931/AGR, 2012GA-LC-036, 2003-03-4.3-I-014, CGL2006-05415, BEST-2011/225, CGL2010-16775, TEC2011-28201, 2012GA-LC-021 and the Banting Postdoctoral Fellowship to PJG

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

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

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions