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

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

Validity and diagnostic attributes of a mathematics olympiad for junior high school contestants

The purpose of mathematics competitions, and in our case the South African Mathematics Olympiad (SAMO), is to promote problem solving skills and strategies, to generate interest and enthusiasm for mathematics and to identify the most talented mathematical minds. SAMO is organised in two divisions – a junior and a senior division - over three rounds. We analysed the results of the junior second round over seven years 2006-2012. Based on the literature a mathematical content framework was developed, dividing the mathematical content into seven broad content areas. In this paper we investigate the face validity, diagnostic attributes and predictive criterion validity of mathematics olympiad question papers over the period by focussing on the frequency of content area occurrence in the different items. We also look at performance of contestants in the different content areas as a broad diagnosis. Lastly we investigate the item performance, comparing the expected performance by the problem committee of experts setting the question papers and the actual performance of contestants. Topics such as numbers, algebra, patterns and functions, measurement, applications, modelling and logic were used abundantly whereas (quite surprisingly) there were few items on graphs, decimal fractions, spatial logic and vertices and edges of polygons, indicating that the face validity can be improved. Contestants performed best in items on algebra and weakest in items on statistics. The ability of the problem committee to anticipate student item performance varied considerably and was significantly worse in 2012 than in 2006, indicating better predictive criterion validity in 2006.http://www.tandfonline.com/loi/rmse202017-06-30hb2016Science, Mathematics and Technology Educatio

A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides

We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations

Remote sensing for assessing wetland-groundwater interaction in the Kogelberg Biosphere Reserve

Thesis (MA)--Stellenbosch University, 2005.ENGLISH ABSTRACT: The Table Mountain Group (TMG) Aquifer System is a regional fractured aquifer system with a large potential as a source of future water supplies in the Western and Eastern Cape. This system is currently under consideration for large-scale water abstraction. Many terrestrial ecosystems, however, are dependent on these groundwater resources for survival. Exploitation of ground water resources at a rate exceeding the rate of natural recharge would result in a lowering of the water table and the drying up of seeps. The main objective of this study was to determine if satellite remote sensing data can be used for the detection of groundwater-dependent wetlands, and secondly, to use multi-temporal imagery for estimating seasonal changes experienced in wetland communities in relation to surrounding vegetation. The Kogelberg Biosphere Reserve, situated approximately 30km to the east of Cape Point in the Western Cape, South Africa, was selected for investigation. To accomplish the objectives, three Landsat 7 ETM+ images (path/row: 175/84) captured on 22 September 2001, 18 May 2002 and 23 September 2002 were acquired. Image fusion of the multispectral bands (30m resolution) with the panchromatic band (15m resolution) provided 15m multispectral images for analysis purposes. Geometric correction, radiometric normalisation and atmospheric corrections was performed in order to ensure pixel-level comparability between images. Once comparability between images was guaranteed, vegetation indices and tasselled cap components were derived to provide threshold values of moisture stress indicators and productivity estimations of wetland communities in relation to surrounding non-wetland communities. Additionally, change vector analysis on these transformations provided the ability to detect and assess the seasonal changes experienced by these communities during an annual cycle. The results of these transformations were combined in a rule-based image classifier in order to assist in estimating the seasonal dependency of observed wetland communities. The ability to use Landsat 7 images and the abovementioned image processing procedures to identify wetland communities with a high probability of groundwater interaction was demonstrated with a high degree of accuracy (78%). It is recommended that future studies concentrate on increasing classification accuracies, while focusing on incorporating these techniques into a remote monitoring system for assessing the impacts of groundwater extraction on the groundwater-dependent wetland communities.AFRIKAANSE OPSOMMING: Die Tafelberg Groep (TBG) Akwifer is 'n regionale verskuiwingsakwifer sisteem met groot potensiaal as toekomstige waterbron vir die Wes- en Oos-Kaap. Grootskaalse grondwateronttrekking uit hierdie sisteem word tans ondersoek. Baie terrestriële ekosisteme is egter vir oorlewing van grondwaterbronne afhanklik. Grondwaterontginning teen 'n tempo hoër as die natuurlike aanvultempo sal die watertafel laat daal en syfersones laat opdroog. Die hoofdoel van die studie was om te bepaal of satellietbeelde gebruik kan word om grondwater-afhanklike vleilande waar te neem, en om 'n tydsreeks van beelde te gebruik om die seisoenale verandering in vleilandgemeenskappe relatief tot omliggende plantegroei te raam. Die Kogelberg Biosfeer Reservaat, ongeveer 30km oos van Kaappunt, is as studiegebied geïdentifiseer. Drie Landsat 7 beelde (baan/ry: 175/84) van 22 September 2001, 18 Mei 2002 en 23 September 2002 is ontleed. Die Landsat 7 multispektrale bande (30m resolusie) is met behulp van beeld-fusietegnieke met die panchromatiese band (15m resolusie) gekombineer om multispektrale beelde te lewer met 15m grondresolusie. Geometriese korreksie, radiometriese normalisering en atmosferiese korreksie is op elk van die beelde toegepas om beeld-selvlak vergelykings tussen beelde 'n moontlikheid te maak. Met beeldvergelykbaarheid verseker, is plantegroei-indekse en 'tassled cap' transformasies gebruik om afsnywaardes vir vleiland-identifikasie te bereken. Verder is veranderingsvektoranalises op die transformasies bereken om die seisoenale veranderinge oor die jaarsiklus in vleilande te bepaal. Die resultate hiervan is vervat in 'n reël-gebaseerde beeldklassifiseerder waarmee vleilande se seisoenale grondwater afhanklikheid geraam is. Die vermoë om vleilande met 'n hol! waarskynlikheid van grondwater interaksie uit Landsat 7 beelde te identifiseer is met 'n hol! vlak van totale akkuraatheid (78%) gedemonstreer. Die aanbeveling is dat toekomstige studies moet fokus op die verhoging van hierdie klassifikasie akkuraathede. Die tegnieke moet toegespits word op die ontwikkeling van 'n afstandswaarnemingstelsel om di

The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment

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

The use of Landsat and aerial photography for the assessment of coastal erosion and erosion susceptibility in False Bay, South Africa

CITATION: Callaghan, K., Engelbrecht, J. & Kemp, J. 2015. The use of Landsat and aerial photography for the assessment of coastal erosion and erosion susceptibility in False Bay, South Africa. South African Journal of Geomatics, 4(2):65-79.The original publication is available at http://www.sajg.org.zaCoastal erosion is a worldwide hazard, the consequences of which can only be mitigated via thorough and efficient monitoring of erosion. This study aimed to employ remote sensing techniques on aerial photographs and Landsat TM/ETM+ imagery for the detection and monitoring of coastal erosion in False Bay, South Africa. Vegetation change detection as well as post-classification change detection were performed on the Landsat imagery. Furthermore, aerial photographs were analysed using the Digital Shoreline Analysis System (DSAS), which determines statistical differences in shoreline position over time. The results showed that while the resolution of the Landsat imagery was not sufficient to quantify and analyse erosion along the beach itself, the larger area covered by the satellite images enabled the identification of changes in landcover conditions leading to an increased susceptibility to erosion. Notably, the post-classification change detection indicated consistent increases in built-up areas, while sand dune, beach, and sand (not beach) decreased. NDVI differencing led to the conclusion that vegetation health was decreasing while reflective surfaces such as bare sand and roads were increasing. Both of these are indicative of an increased susceptibility to coastal erosion. Aerial photographs were used for detailed analysis of four focus areas and results indicated that coastal erosion was taking place at all four areas. The higher resolution available on the aerial photographs was vital for the quantification of erosion and sedimentation rates.http://www.sajg.org.za/index.php/sajg/article/view/233Publisher's versio

Change detection of bare areas in the Xolobeni region, South Africa using Landsat NDVI

CITATION: Singh, R. G., Engelbrecht, J. & Kemp, J. 2015. Change detection of bare areas in the Xolobeni region, South Africa using Landsat NDVI. South African Journal of Geomatics, 4(2):138-148.The original publication is available at http://www.sajg.org.zaIdentification and protection of areas that are vulnerable to erosion is essential for the conservation of the sensitive wetlands and estuarine ecosystems along the Xolobeni coastal strip. The forecasting of these erosion susceptible areas requires an understanding of the inter- relationships of the critical factors that have influenced erosion potential over time. Vegetation and bare areas are some of the contributing factors that have influenced erosion at Xolobeni. This study used remote sensing as a tool to provide some information on the inter-relationship between vegetated classes and bare areas. Normalised Difference Vegetation Index (NDVI) data derived from multi-temporal Landsat 5 imagery has formed the baseline information for this study. A density slicing approach was adopted to classify the region into four vegetation structure classes of predominant land cover types. Post classification change detection data has provided an understanding of the relative susceptibility of the different vegetated classes to being degraded to bare areas. The results suggest that poorly vegetated regions were most susceptible to further degradation and an elevated susceptibility to erosion. On the other hand, moderately and densely vegetated regions were less susceptible to land degradation. The information can be used to identify measures to mitigate the effects of land degradation in vulnerable areas.http://www.sajg.org.za/index.php/sajg/article/view/257Publisher's versio

A simple normalized difference approach to burnt area mapping using multi-polarisation C-band SAR

CITATION: Engelbrecht, J., et al. 2017. A simple normalized difference approach to burnt area mapping using multi-polarisation C-band SAR. Remote Sens, 9(8):764, doi:10.3390/rs9080764.The original publication is available at http://www.mdpi.com/2072-4292/9/8/764In 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 approacheshttp://www.mdpi.com/2072-4292/9/8/764Publisher's versio