Andre Theron

Sinkholes are global phenomena with significant consequences on the natural- and built environment. Significant efforts have been devoted to the assessment of sinkhole hazards to predict the spatial and temporal occurrence of future sinkholes as well as to detect small-scale deformation prior to collapse. Sinkhole hazard maps are created by considering the distribution of past sinkholes in conjunction with their geomorphic features, controlling conditions and triggering mechanisms. Quantitative risk assessment then involves the statistical analysis of sinkhole events in relation to these conditions with the aim of identifying high risk areas. Remote sensing techniques contribute to the field of sinkhole hazard assessment by providing tools for the population of sinkhole inventories and lend themselves to the monitoring of precursory deformation prior to sinkhole development. In this paper, we outline the background to sinkhole formation and sinkhole hazard assessment. We provide a review of earth observation techniques, both for the compilation of sinkhole inventories as well as the monitoring of precursors to sinkhole development. We discuss the advantages and limitations of these approaches and conclude by highlighting the potential role of radar interferometry in the early detection of sinkhole-induced instability resulting in a potential decrease in the risk to human lives and infrastructure by enabling proactive remediation.

In fire-prone ecosystems, periodic fires are vital for ecosystem functioning. Fire managers seek to promote the optimal fire regime by managing fire season and frequency requiring detailed information on the extent and date of previous burns. This paper investigates a Normalised Difference α-Angle (NDαI) approach to burn-scar mapping using C-band data. Polarimetric decompositions are used to derive α-angles from pre-burn and post-burn scenes and NDαI is calculated to identify decreases in vegetation between the scenes. The technique was tested in an area affected by a wildfire in January 2016 in the Western Cape, South Africa. The quad-pol H-A-α decomposition was applied to RADARSAT-2 data and the dual-pol H-α decomposition was applied to Sentinel-1A data. The NDαI results were compared to a burn scar extracted from Sentinel-2A data. High overall accuracies of 97.4% (Kappa = 0.72) and 94.8% (Kappa = 0.57) were obtained for RADARSAT-2 and Sentinel-1A, respectively. However, large omission errors were found and correlated strongly with areas of high local incidence angle for both datasets. The combined use of data from different orbits will likely reduce these errors. Furthermore, commission errors were observed, most notably on Sentinel-1A results. These errors may be due to the inability of the dual-pol H-α decomposition to effectively distinguish between scattering mechanisms. Despite these errors, the results revealed that burnt areas could be extracted and were in good agreement with the results from Sentinel-2A. Therefore, the approach can be considered in areas where persistent cloud cover or smoke prevents the extraction of burnt area information using conventional multispectral approaches.

Wild fires are often disastrous events, damaging infrastructure and the environment. However, in fire-prone ecosystems, periodic fires are vital for ecosystem functioning. Fire managers in these regions seek to promote the optimal fire regime by managing fire season and fire frequency. For this purpose, detailed information on the extent and date of previous burns over large areas are required. This paper proposes a Normalised Difference α-Angle approach to burn scar mapping using α-angles derived from a pre-burn scene and a post-burn RADARSAT-2 scene. A threshold-based segmentation approach was used to extract the burnt-area extent while minimizing speckle effects. The results of the burn scar extraction were compared to the extent of a burn scar derived from Sentinel-2 data. The results suggest that, in general, a good agreement between the two approaches was obtained with an overall accuracy of 0.98 achieved. High errors of omission was associated with areas of high local incidence angle. In general, the result suggests that SAR data, analysed using the proposed approach, can be used in areas where persistent cloud cover or smoke from active fires prevents the use of conventional approaches.

Surface subsidence associated with underground coal mining is a known concern due to the associated environmental as well as health and safety risks. This paper evaluates the potential of Sentinel-1 repeat-pass differential interferometry for monitoring mining-induced deformation. The area under investigation is a coal mining region in South Africa where pillar-extraction is taking place. The pillar extraction causes a weakening of pillars leading to roof collapse and subsequent deformation at the surface. The results of Sentinel-1 dInSAR analysis suggest that several deformation features could be observed during almost 2-years of monitoring and the evolution and progression of deformation basins over time could be studied. The results further indicate that operational monitoring of mining-induced deformation by Sentinel-1 interferometry would be possible assuming data continuity can be ensured. Since many mines are considering pillar-extraction as the end-of-life of the mine is reached, continued Sentinel-1 dInSAR observations can be incorporated into operational monitoring programmes.

Sinkholes are an unpredictable geohazard that endanger life and property in dolomitic terrains. Sinkholes are a significant threat in Gauteng, South Africa's most populated and urbanized province. Small-scale surface subsidence is frequently present prior to the collapse of a sinkhole. Therefore, the presence of precursory surface deformation can be exploited to develop early warning systems. Spaceborne synthetic aperture radar (SAR) differential interferometry (DInSAR) is able to monitor small-scale surface deformation over large areas and can be used to detect and measure precursors to sinkhole development. This letter investigates the use of repeat-pass DInSAR to detect sinkhole precursors in the Gauteng province. Twenty stripmap acquisitions from TerraSAR-X were acquired over a full year. DInSAR results revealed the presence of three previously unknown deformation features, one of which could be confirmed by subsequent field investigations. Furthermore, a water supply pipeline ruptured six months after the initial observation. The detection of the deformation, therefore, provided a viable early warning to landowners who were unaware of the subsidence. Detected deformation features were between 40 and 100 m in diameter. The maximum displacement measured was 50 mm over 55 days. Despite the successful detection, seven sinkhole events occurred in the observation period, for which no deformation could be detected. The results indicate that high-resolution X-band interferometry is able to monitor dolomite-induced instability in an urban environment. However, considerations related to SAR interferometry and physical sinkhole properties need to be addressed before DInSAR can be used in an operational early warning system.

Sinkholes are an unpredictable geohazard that endangers life and property in dolomitic terrains. They are a significant threat in Gauteng, South Africa's most populated and urbanized province. Small scale surface subsidence is frequently present prior to the collapse of a sinkhole. Therefore, the presence of precursory surface deformation can be exploited to develop early warning indicators. Spaceborne SAR interferometry is able to monitor small-scale surface deformation over large areas and was exploited to detect and measure precursors to sinkhole development. The first results of DInSAR-based monitoring of areas associated with sinkhole development using TerraSAR-X is presented here. Subsidence activity was detected on three successive interferograms over a 55 day period. The subsidence basin was approximately 100 m in diameter with a maximum vertical displacement of 66.7 mm. Field surveys revealed tension cracks along the edges of the subsidence basin. Dramatically, four months after the subsidence event, a high pressure water supply pipeline burst meters downslope of the basin. The first results indicate that high resolution, X-band interferometry is able to monitor dolomite-induced instability in an urban environment.