Browsing by Author "Theron, Andre"

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    Detection of sinkhole precursors through SAR interferometry
    (Stellenbosch : Stellenbosch University, 2017-03) Theron, Andre; Kemp, J.; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: Differential Interferometric Synthetic Aperture Radar (DInSAR) is a mature ground deformation monitoring technique and research presented in this thesis supports this technology as a key tool for an operational sinkhole early warning system in South Africa. Sinkholes are an unpredictable geohazard that endangers life and property in dolomitic terrains. They are a significant threat in Gauteng, the most populated and urbanised province in South Africa. More than 3000 events have been recorded here in the last ~50 years that has led to the loss of 37 lives and more than 1.2 billion Rands in property damage. There is a need for risk mitigation measures in areas that are already developed. Such measures will also allow further development of sinkhole-prone land. Small-scale surface subsidence is frequently present prior to the collapse of a sinkhole yet not much is known about this phenomenon. This is mostly due to the unpredictable nature of sinkholes and the challenges in monitoring large areas for small-scale deformation. Nevertheless, it is hypothesised that the presence of precursory surface deformation can be exploited to develop early warning systems to mitigate further damages. Spaceborne DInSAR is able to monitor small-scale surface deformation over large areas and can be exploited to detect and measure precursors to sinkhole development. Recently, there have been successful case studies supporting this technique for sinkhole precursor detection. Yet the operational limitations have not been determined. The first results of DInSAR-based monitoring effort of dolomite areas associated with sinkhole development are presented here. TerraSAR-X was tasked to acquire data from January 2015 – January 2016 with short revisit times (generally 11 days but up to 77 days) resulting in 21 interferometrically compatible images. Sequential image pairs were processed through conventional DInSAR processing workflows. Three previously unknown deformation basins were detected, one of which could be confirmed in the field. This confirmed subsidence ultimately led to a burst high-pressure water supply pipeline. The detected deformation basins were between 40 m and 100 m in diameter. The maximum displacement was measured as 7 cm over 55 days. Deformation before the infrastructure damage could be detected up to 6 months in advance. The detection could have provided a viable early warning to landowners who were unaware of the subsidence. Another event that remains unconfirmed by in-situ observations was characterised by unexplained ground uplift. These results indicate that high-resolution X-band DInSAR is able to monitor dolomite-induced instability in an urban environment. Although some deformation features were observed, seven sinkhole events occurred in the observation period for which no DInSAR deformation could be detected. Two factors were identified to be major challenges to the detection of precursory deformation, 1) the minimum detectable scale of deformation and 2) coherence loss due to temporal decorrelation, mainly because of ground disturbance during large rainfall events. The physical presence of precursors is further discussed as a fundamental limitation to early warning systems. Future research should explore ultra-high resolution sensors and consider advanced DInSAR processing techniques to overcome coherence limitations. This research supports the statement that DInSAR could contribute to an operational early warning system and further recommends that local geohazard policy should consider its capabilities. Keywords: Remote sensing, SAR, Interferometry, TerraSAR-X, Sinkhole, Precursor, Dolomite, Gauteng
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    A simple normalized difference approach to burnt area mapping using multi-polarisation C-band SAR
    (MDPI, 2017) Engelbrecht, Jeanine; Theron, Andre; Vhengani, Lufuno; Kemp, Jaco
    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