Browsing by Author "Engelbrecht, Jeanine"

Now showing 1 - 4 of 4
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    Change detection of bare areas in the Xolobeni region, South Africa using Landsat NDVI
    (CONSAS Conference, 2015-06) Kemp, Jaco; Singh, Rebekah Gereldene; Engelbrecht, Jeanine
    Identification 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.
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    Remote sensing for assessing wetland-groundwater interaction in the Kogelberg Biosphere Reserve
    (Stellenbosch : Stellenbosch University, 2005-12) Engelbrecht, Jeanine; Zietsman, H. L.; Riemann, K.; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    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.
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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
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    The use of Landsat and aerial photography for the assessment of coastal erosion and erosion susceptibility in False Bay, South Africa
    (CONSAS Conference, 2015-06) Callaghan, Kerry; Engelbrecht, Jeanine; Kemp, Jaco
    Coastal 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.