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Development of a numerical geohydrological model for a fractured rock aquifer in the Karoo, near Sutherland, South Africa

  • Authors: Maqhubela, Akhona
  • Date: 2024-04
  • Subjects: Groundwater -- South Africa -- Northern Cape , Hydrogeology -- South Africa -- Northern Cape , Remote sensing , Geographic information systems
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10948/64163 , vital:73659
  • Description: The regional scale method in groundwater storage observation introduces uncertainties that hinder the evaluation of the remaining lifespan of depleted aquifers. The scarcity of precipitation data presents significant global challenge, especially in semi-arid regions. This study constructs a regional numerical hydrogeological model that identifies the potential impacts of climate change on the water balance for the South African Gravimetric Observation Station in Sutherland. The purpose of this study is to understand mechanisms controlling groundwater in the fractured rock aquifer. The climate data from the Weather forecast data over the last ten years was collected from the South African Weather Service. and groundwater levels data assessed the potential impacts of climate change on water balance components, especially precipitation and evapotranspiration. Precipitation is the primary recharge parameter in this study and had the highest level recorded in winter, with May having the highest precipitation rates of 24,62mm. The instrument conducted two profile investigations in a single day to detect geological abnormalities at various depths, achieving an impressive accuracy of up to 0.001 mV. The fact that groundwater flows from regions of higher hydraulic heads to areas of lower hydraulic charges, confirms that riverbeds in Sutherland act as preferential conduits for subsurface recharge. The profile and processed geophysical maps show low chances of getting groundwater in this observed area due to extensively great depth, approximately 150 – 210 m. The river package from MODFLOW model shows little inflow to the study nearby well locations. These model results showed a negative difference between water flowing in and out of the system of about -7m3 between 2002 and 2020. Groundwater flows faster at borehole five, where the hydraulic conductivity is large. The resulting regional hydrogeological model offered valuable insights into how climate change might influence the distribution and accessibility of groundwater resources. In the context of Sutherland, a negative groundwater budget value signaled that groundwater extraction or consumption surpassed the natural replenishment or recharge of the aquifer. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2022
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  • Date Issued: 2024-04

Quantifying the impact of the spatio-temporal variability of land use/land cover on surface run-off generation and groundwater recharge in the luvuvhu river catchment area as a study area

  • Authors: Ramuhovhi, Dakalo Ndivhuwo Stella
  • Date: 2024-04
  • Subjects: Remote sensing , Geographic information systems , Groundwater flow
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10948/64322 , vital:73675
  • Description: Assessing the spatio-temporal dynamics of land use land cover (LULC) change on hydrological response is vital for catchment sustainability and developing proper management strategies. The study aimed to assess the spatiotemporal effects and implications of LULC dynamics on surface runoff in the Luvuvhu River Catchment, Limpopo Province, using the Soil and Water Assessment Tool (SWAT) model. Satellite images of Landsat 5-thematic mapper and Landsat 8 operational land imager for the years 1990 and 2021 were used to explore the characteristics of LULC for this study by adopting the maximum likelihood (ML) supervised classification method. Five LULC classes were classified in this study; namely, water, built-up area, bare surface, dense vegetation, and sparse vegetation. The classification results show good accuracy values in the range of 76% (1990) and 84% (2021) with overall kappa of 63.8% and 72.8% for 1990 and 2021, respectively. For the purpose of this study, integration of geospatial technique and SWAT model were configured to operate at a monthly time interval over a span of 34 years, specifically from 1979 to 2013 to simulate surface runoff. The SWAT simulation process was executed using a digital elevation model, soil, LULC, and weather data. The analysis of LULC for 1990 and 2021 runoff modelling, it was found that, the runoff depth increased gradually from 3249 mm to 5162.5 mm during 1990 and 2021 LULC change, respectively. The R2, ENS, PBIAS, and RSR values for the calibration and the validation were 0.81 and 0.76, and 0.72 and 0.68, 0.64 and 0.58, 0.54 and 0.63 respectively. These values indicate good correlation between the observed and simulated stream flow data Therefore, suitable and timely management measures must be taken by policy decision-makers to enable sustainable development and to protect the catchment’s natural resources in order to reduce the severity of the changes. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2024
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  • Date Issued: 2024-04

Relating vegetation distribution to cycles of erosion and deposition in the Kromme River wetlands

  • Authors: Jarvis, Samuel Cameron
  • Date: 2023-10-13
  • Subjects: Biogeomorphology South Africa Kromme Estuary (Eastern Cape) , Earth observation , Remote sensing , Niche construction , Wetland ecology , Geomorphology , Ecological succession , Optical radar , Prionium serratum
  • Language: English
  • Type: Academic theses , Master's theses , text
  • Identifier: http://hdl.handle.net/10962/424582 , vital:72166
  • Description: The role of geomorphic disturbance has been increasingly recognized as fundamental in the creation and functioning of wetlands. This is true of the Kromme River wetland which has been formed through repeated cycles of erosion and deposition. However, the response – and influence – of wetland plants to these sorts of disturbance has not been investigated. This study sought to fill this knowledge gap by classifying vegetation communities over a range of hydrological and geomorphic disturbance regimes that have happened over the last few decades, and relating those vegetation communities to environmental factors. The study identified seven vegetation communities based on their species composition and abundance, which were related to geomorphic disturbance events. A conceptual model that accounts for vegetation distribution in the Kromme wetland was developed. Soil saturation was the most important factor explaining vegetation community distribution, which, in turn, is influenced by cycles of erosion and deposition. Following an erosional event on the valley floor, Prionium serratum dominated wetland is converted to a number of other vegetation communities. On the floodplain surface adjacent to the eroded gully, the Prionium serratum dominated wetland is transformed over time to Cynodon dactylon and Sporobolus fimbriatus communities. Prionium serratum clumps immediately adjacent to the recently incised gullies are able to persist, having sufficient access to water. Within the newly formed gullies, Juncus lomatophyllus colonizes the gully beds flooded to a shallow depth, Miscanthus capensis colonizes the gully bars and Setaria incrassata colonizes the exposed gully banks. Localised depositional features close to the thalweg in the gully are colonized by Prionium serratum seedlings and vegetative propagules. These plants represent the regenerating phase of Prionium serratum wetland, which also colonizes depositional floodouts downstream of the newly-formed gully. The Stenotaphrum secundatum community dominates drier, more elevated areas of the floodout. Over time, as the gully fills, Prionium serratum expands beyond the gully onto the valley floor, to replace the floodplain communities Cynodon dactylon and Sporobolus fimbriatus. Over time, Prionium serratum is thought to colonize the valley floor as the gully fills, stabilising it and promoting diffuse flow. Many restoration efforts in damaged palmiet wetlands have been focused on the preservation of intact palmiet communities upstream of erosional headcuts, with limited understanding of vegetation dynamics associated with the cut-and-fill cycles that naturally occur in these wetlands. Understanding the regeneration of Prionium serratum following erosional events is thus important for wetland restoration, as it should focus more attention on promoting palmiet restoration on depositional floodouts downstream of eroded gullies. A secondary aim of this study was to explore the possibility of mapping palmiet communities in Kromme River wetland using remote sensing techniques. Using a combination of ground-truthed data from this and previous studies in the Kromme River wetland, together with raster layers derived from a LiDAR survey, an overlay analysis was developed to effectively map the distribution of the Prionium serratum dominated community. The overlay was created using a machine learning library in RStudios known as Rpart. The results found that the model were 91% effective in classifying the distribution of the Prionium serratum community. A secondary finding was that the inclusion of a Relative Elevation Model in the overlay analysis allowed for the identification of Prionium serratum communities vulnerable to degradation following previous geomorphic disturbance events and those Prionium serratum communities that are likely to persist following a geomorphic disturbance event. , Thesis (MSc) -- Faculty of Science, Geography, 2023
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  • Date Issued: 2023-10-13

Remote sensing as a monitoring solution for water hyacinth (Pontederia crassipes) in the context of the biological control programme at Hartbeespoort Dam

  • Authors: Kinsler, David Louis
  • Date: 2023-10-13
  • Subjects: Remote sensing , Water hyacinth South Africa Hartbeespoort , Aquatic weeds Biological control South Africa Hartbeespoort , Megamelus scutellaris , Eutrophication
  • Language: English
  • Type: Academic theses , Master's theses , text
  • Identifier: http://hdl.handle.net/10962/424599 , vital:72167
  • Description: Water hyacinth (Pontederia crassipes (C.Mart.) Solms (Pontederiaceae)) is a significant aquatic weed both globally and in South Africa. Despite notable success with biological control of other invasive macrophytes, the plant remains as a problematic weed in many aquatic systems in South Africa, particularly due to the eutrophic status of many of its water systems, as well as the plant’s tolerance to cooler climatic conditions than most of its existing biological control agents. Hartbeespoort Dam, located about 30 kilometres west of Pretoria, South Africa, has been infamously infested with water hyacinth for decades, which impacts the important socioeconomic utility of the dam and functioning of natural ecological processes in the system. The dam has a long history of efforts to control water hyacinth, which include widespread herbicidal spray, mechanical removal and classical biological control programmes since the early 1990s - mostly with limited or short-lived success. However, after the introduction of a new, cold-tolerant biological control agent, Megamelus scutellaris Berg (Hemiptera: Delphacidae) in 2018 with an inundative release strategy, the water hyacinth dropped significantly from a maximum cover of about 45 percent (819 hectares) down to less than two percent (40 hectares) over a three-month period (November 2019 – January 2020). This was significant, as it marked the first successful biological control of water hyacinth in a eutrophic, temperate system in South Africa. However, due to the scale of Hartbeespoort Dam (1820 hectares) and the high spatiotemporal variation of the floating mats across time and space, quantifying and monitoring these rapid changes has proved difficult. In response to this problem, this thesis proposed a remote sensing solution to address the need for accurate, timely and readily accessible monitoring data of the water hyacinth population on the dam. Leveraging the temporally frequent (< 5 days revisit time) Sentinel-2 multispectral satellite data, as well as the powerful cloud-computing resources of Google Earth Engine, this thesis developed and deployed a relatively simple and robust index-based decision tree classification method to demonstrate the value of these technologies as an effective monitoring and analysis tool for monitoring large macrophyte infestations. To this end, several challenges had to be overcome in order to produce easily accessible data that was accurate and reliable. For example, due to the size of the Sentinel-2 Level-1C image dataset from August 2015 to March 2021 (n = 654), an automated process of filtering out clouded images was required. Additionally, the co-presence of algal and cyanobacterial blooms necessitated the development of a novel index, coined the Algae Resistant Macrophyte Index (ARMI), to deal with the challenges of accurate macrophyte detection. The high spatiotemporal variability of the floating mats meant that a typical, location-based confusion matrix as a means of assessing the accuracy of the decision tree classifier required a different approach which compared the total classified areas with higher resolution images. This thesis aims to demonstrate the utility of remote sensing tools to provide effective monitoring information to managers, researchers and other stakeholders. There is scope to expand to more areas in South Africa and beyond and may prove an invaluable tool to augment and support on-going and future macrophyte monitoring programmes. , Thesis (MSc) -- Faculty of Science, Geography, 2023
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  • Date Issued: 2023-10-13

Estimating estuarine suspended sediment concentration through spectral indices and band ratios derived from Sentinel-2 data: a case of Umzimvubu Estuary, South Africa

  • Authors: Tshazi, Zamavuso
  • Date: 2022-11
  • Subjects: Sediments (Geology) , Suspended sediments , Remote sensing
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10353/27743 , vital:69406
  • Description: The current study was aimed at evaluating the reliability and efficacy of selected remote sensing band ratios and indices in accurately estimating the spatial patterns of suspended sediment concentration level in Umzimvubu Estuary, Eastern Cape, South Africa. Sentinel-2 imagery was acquired on the 29th of March 2022. Band reflectance values were extracted from Sentinel -2 imagery, and laboratory measurements of suspended sediment concentration were obtained from samples collected from fifty (50) sampling points in the estuary on the 29th of March 2022. Sentinel-2 imagery was then validated with the field data in estimating and mapping the suspended sediment concentration. Several remote sensing band ratios Red/(Green plus Near-Infrared), Near-Infrared/Green, Red plus Near-Infrared/Green, Blue(Green plus Red)/Blue and Green plus Near-Infrared)/Blue and indices, that is the Normalised Difference Turbidity Index (NDTI), Normalized Difference Suspended Sediment Index (NDSSI) and Normalized Suspended Material Index (NSMI)) were then used to predict the suspended sediment concentration from Sentinel-2 imagery. The accuracy of band ratios and indices was evaluated by correlating the prediction against the observed suspended sediment concentration from Sentinel-2 imagery. A total of 50 points were randomly surveyed in the Umzimvubu estuary for analyzing suspended sediment concentration. Results indicate that the Blue (Green plus Red)/Blue, the Green plus Near-Infrared)/Blue and NMSI performed well based on their R-squared. The Blue (Green plus Red)/Blue and Green + Near-Infrared)/Blue band ratios had 0.86 and 0, 94, respectively. While NSMI yielded an R-squared of 0,76 and RMSE of 19,2 mg/L. The results in the current study indicate that Sentinel-2 imagery can reliably estimate the concentration of suspended sediment level in the Umzimvubu Estuary using band ratios and indices. , Thesis (MSc) -- Faculty of Science and Agriculture, 2022
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  • Date Issued: 2022-11

Towards an improved understanding of episodic benthic turbidity events (Benthic Nepheloid Layer) on the Eastern Agulhas Bank, South Africa

  • Authors: Johnstone, Brett Mordaunt
  • Date: 2022-10-14
  • Subjects: Nepheloid layer , Turbidity , Loligo reynaudii , Fisheries South Africa , Oceanography , Remote sensing , Altimetry , Climatic changes
  • Language: English
  • Type: Academic theses , Master's theses , text
  • Identifier: http://hdl.handle.net/10962/362883 , vital:65371
  • Description: The harvest of Loligo reynaudii, or "chokka," represents a critical source of revenue and job creation in the historically impoverished Eastern Cape Province of South Africa. Due to the importance of visual stimuli in the reproductive processes, it has been hypothesized that a primary driver of successful reproduction is the clarity of the water column. The presence of increased particulate matter concentrations within the water column generates turbid conditions near the seafloor (visibility < 1m), that are proposed to restrict spawning activity. This benthic nepheloid layer (BNL) contains both organic and inorganic components, with the BNL intensity a function of bottom turbulence, substratum type, and detritus level. However, the spatial and temporal resolution of BNL intensity on the Eastern Agulhas Bank (EAB) and the environmental drivers thereof remain unknown. Here we show that benthic turbidity events are a common but highly variable occurrence on the EAB. Results from a 17-month time-series of in-situ and remote sensing data between 2002 – 2004 in Algoa Bay, supplemented by experiments in other bays important for spawning, show that turbid conditions existed for ∼ 30 % of the sample period. Exploration of environmental drivers, including the influence of wind, altimeter-derived significant wave height (Hs), sea surface temperature (SST), and chlorophyll-a (Chl-a) concentrations indicate that BNL intensity does not conform to a "one-size-fits-all" approach. Rather, complex local hydrological and physiochemical parameters control the BNL characteristics on the EAB. Global warming is likely to increase the frequency and intensity of extreme westerly-wind and storm events, promoting BNL events on the Eastern Agulhas Bank and possibly causing a shift in the reproductive strategy of chokka squid to the cooler mid shelf region. This is likely to have consequences for both the species in terms of reproductive success and the fishery, which is concentrated on inshore spawning aggregations. Future research needs to quantify and characterize the constituents, source particles and spatial-temporal variability of BNL events in order to build a predictive capacity. Through incorporating the qualitative analysis of the dynamics of nepheloid layers on the EAB into Regional Oceanographic Models (ROMS), General Linear Models (GLM) and particle distribution models such as DELFT-3D, it is possible to move toward predicting the timing and intensity of these events. , Thesis (MSc) -- Faculty of Science, Ichthyology and Fisheries Science, 2022
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  • Date Issued: 2022-10-14

Ecological infrastructure importance for drought mitigation in rural South African catchments: the Cacadu Catchment case example

  • Authors: Xoxo, Beauten Sinetemba
  • Date: 2021-10
  • Subjects: Sustainable Development Goals , Water security South Africa , Remote sensing , Watershed restoration South Africa , Restoration ecology South Africa , Ecosystem services South Africa , SDG 15.3.1‎
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10962/191203 , vital:45070
  • Description: Water scarcity is recognised as one of the significant challenges facing many countries, including South Africa. The threat of water scarcity is exacerbated by the coupled impacts of climate and anthropogenic drivers. Ongoing droughts and continued land cover change and degradation influence the ability of catchments to partition rainwater runoff, thereby affecting streamflow returns. However, quantifying land degradation accurately remains a challenge. This thesis used the theoretical lens of investing in ecological infrastructure to improve the drought mitigation function in rural catchments. This theoretical framework allows for a social-ecological systems approach to understand and facilitate science-based strategies for promoting ecosystem recovery. Specifically, this study aimed to explore the role and benefit of ecological infrastructure for improving drought mitigation, and consequently, water security for rural communities. Thus, this study sought to assess the consequences of human actions to catchment health status using the 15th Sustainable Development Goal indicator for the proportion of degraded land over the total land area as a surrogate. Secondly, hydrological modelling was used to describe how different land covers influence catchment hydrology, which related to how ecological infrastructure enables drought risk-reduction for mitigation regulation. Finally, this study developed a spatial prioritisation plan for restoration to improve drought mitigation for four focal ecological infrastructure (EI) categories (i.e. wetlands, riparian margins, abandoned agricultural fields and grasslands). The focal EI categories were selected for their importance in delivering water-related ecosystem services when sustainably managed. Chapter 1 sets the scene (i.e. provides the study background) and Chapter 2 provides a review of the literature. In Chapter 3, the recently released global GIS toolbox (TRENDS.EARTH) was used for tracking land change and for assessing the SDG 15.3.1 degradation indicator of i.e. Cacadu catchment over 15 years at a 300 m resolution. The results showed a declining trend in biomass productivity within the Cacadu catchment led to moderate degradation, with 16.79% of the total landscape degraded, which was determined by the pugin using the one-out, all-out rule. The incidence of degradation was detected in middle reaches of the catchment (i.e. S10F-J), while some improvement was detected in upper reaches (S10A-C) and lower reaches (S10J). In Chapter 4, a GIS-based Analytic Hierarchical Process (AHP) based on community stakeholder priorities, open-access spatial datasets and expert opinions, was used to identify EI focal areas that are best suitable for restoration to increase the drought mitigation capacity of the Cacadu catchment. The collected datasets provided three broad criteria (ecosystem health, water provision and social benefit) for establishing the AHP model using 12 spatial attributes. Prioritisation results show that up to 89% of the Cacadu catchment is suitable for restoration to improve drought mitigation. Catchments S10B-D, and S10F, S10G and S10J were highly prioritised while S10A, S10E and S10H received low priority, due to improving environmental conditions and low hydrological potential. Areas that were prioritised with consideration for local livelihoods overlap the areas for drought mitigation and form a network of villages from the middle to lower catchment reaches. Prioritised restoration areas with a consideration of societal benefit made up 0.56% of wetlands, 4.27% of riparian margins, 92.06% of abandoned croplands, and 51.86% of grasslands. Chapter 5 reports on use of the Pitman groundwater model to help understand the influence of land modification on catchment hydrology, and highlight the role of restoration interventions. The Cacadu catchment is ungauged, therefore the neighbouring Indwe catchment was used for parameter transfer through a spatial regionalisation technique. Results suggest that degradation increases surface runoff and aggravates recharge reduction, thereby reducing streamflow during low flow periods. In areas where there is natural land cover recovery, the Pitman Model simulated similar dry season streamflow to the natural land cover. Combining the outcomes from the three assessments allowed the study to highlight the role and benefits of ecological infrastructure in terms of drought mitigation. Study findings were interpreted to make recommendations for the role and benefit of ecological infrastructure for drought mitigation at a landscape scale and tertiary catchment level, within the context of available management options. The results support the notion that multiple science data sources can promote investments in ecological infrastructure. However, better spatial and temporal resolution datasets at a national level are still needed to improve the accuracy of studies such as the one outlined in this thesis. The study recommends adopting better ecosystem protection approaches and collaborative governance at multiple levels to reduce the vulnerability of rural communities to drought impacts. , Thesis (MSc) -- Faculty of Science, Institute for Water Research, 2021
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  • Date Issued: 2021-10

Assessing Drought Conditions using NDVI, Land Surface Temperature and Precipitation in Amathole District Municipality, Eastern Cape, Province, South Africa

  • Authors: Dyosi, Masonwabe
  • Date: 2021-05
  • Subjects: Remote sensing , Earth sciences--Remote sensing
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10353/20793 , vital:46570
  • Description: The world is faced with unprecedented environmental changes, which can be linked to population growth, and economic development. Several studies have indicated that these changes are likely to accelerate in the future and cause adverse impact on the environment. To this end, the Eastern Cape Province and in particular the Amathole District Municipality (ADM) has recorded high number of climate change related disasters such as prolonged drought conditions witnessed during the winter season of 2008, 2009, 2014 and 2015 among others. To this end, this study aimed to use remote sensing imagery to assess and document drought occurrences in the ADM from 2007 to 2017. To accomplish the aim, the Normalized Difference Vegetation Index, Land Surface Temperature and Precipitation were explored to assess drought spatiotemporal occurrences. To assess the relationship between abovementioned variables, the Pearson’s correlation was used. For the analysis a total of 396 satellite imagery (MODIS NDVI and Land Surface Temperature as well as TRMM precipitation) were used. The study results revealed that different correlations exist between the three variables. The strength of correlations differed by season. Furthermore, it was revealed that the drought conditions in the district differed in the spatial distribution. The study accurately identified the drought episodes which occurred in the ADM in the years 2008, 2009, 2014, 2015 and 2016. The chosen methodology and variables proved to be suitable for analysing drought conditions offering space and temporal variation dimension, which is vital in monitoring disasters such as drought. , Thesis (MSc) (Geography) -- University of Fort Hare, 2021
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  • Date Issued: 2021-05

Monitoring the impact of deforestation on an aquatic ecosystem using remote sensing: a case study of the Mngazana mangrove forest in the eastern cape province.

  • Authors: Madasa, Akhona
  • Date: 2020-12
  • Subjects: Remote sensing , Mangrove forests , Climatic changes
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10353/20815 , vital:46598
  • Description: Coastal mangrove vegetation at Mngazana continues to be threatened and reduced periodically due to unmonitored harvesting. Covering an area of 148ha, the Mngazana mangrove forest remains unreserved, thus, research on the Mngazana mangroves is essential in order to monitor their state and sustainable management. Since in-situ monitoring of mangrove areas is both challenging and time-consuming, remote sensing technologies have been used to monitor these ecosystems. This study was carried out to monitor the impact of deforestation using ASTER satellite images over ten years: from 2008 - 2018. Validation was carried out by comparing classification results with the ground-referenced data, which yielded satisfactory agreement, with an overall accuracy of 94.64 percent and Kappa coefficient of 0.93 for 2008; and in 2009, the overall accuracy was 88.62 percent and a Kappa coefficient of 0.85. While the overall accuracy of 95.08 percent and a Kappa coefficient of 0.92 for 2016 and 2018 were observed, the overall accuracy of 93.58 percent and a Kappa coefficient of 0.91 was yielded. NDVI and SAVI indices were used as monitoring indicators. The results obtained in the study indicated that the canopy density of the mangrove forest remained unchanged in the years under investigation. However, insignificant changes in canopy density were identified between 2009 and 2016. , Thesis (MSc) (Applied Remote Sensing & GIS) -- University of Fort Hare, 2021
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  • Date Issued: 2020-12

Woody plant encroachment in arid and mesic South African savanna-grasslands: same picture, different story?

  • Authors: Skowno, Andrew Luke
  • Date: 2018
  • Subjects: Savanna ecology South Africa Eastern Cape , Remote sensing , Woody plants South Africa Eastern Cape , Grasslands South Africa Eastern Cape , Plant invasions South Africa Eastern Cape
  • Language: English
  • Type: text , Thesis , Doctoral , PhD
  • Identifier: http://hdl.handle.net/10962/62603 , vital:28212
  • Description: Woody plant encroachment in South Africa’s savanna-grasslands has been considered a rangeland management problem since the early 1900s. This phenomenon, which has been observed globally, is particularly important in Africa given the extent of tropical grassy biomes on the continent and their importance for rural livelihoods. In this study, local and regional scale approaches were used to investigate woody cover change in South Africa across the important savanna-grassland rainfall threshold of 650 mm mean annual precipitation (MAP). The aim was to test this threshold using remote sensing and demographic surveys in order to better understand the patterns, mechanisms and drivers of encroachment. Rates of encroachment and population demographics of Vachelia karroo were compared at arid and mesic savanna sites in the Eastern Cape, using time-series analysis of historical aerial photographs in conjunction with field surveys. Changes in the extent of woodland vs. grassland were then quantified at a national scale (1990-2013) by combining optical and synthetic aperture radar remote sensing data. This produced the first map of woodland- grassland shifts for South Africa and provided the basis for a spatially explicit investigation of the key drivers of change. The local studies revealed higher rates of encroachment at mesic sites than at arid sites, with a correlation between drought and rate of encroachment at the arid site. Vachelia karroo seedlings and stunted saplings were more prevalent at mesic sites than at arid sites and the growth form of adult trees differed significantly between sites. The national remote sensing investigation showed that woodland replaced grassland in over 5% of South Africa’s savanna- grasslands between 1990 and 2014, at rates consistent with other global and regional studies. Spatially explicit models showed a pattern of incremental expansion of woodland along a ‘tree front’ and complex relationships between woodland increase and fire, rainfall, terrain ruggedness and temperature. Overall, the local and regional scale findings of this work highlight the importance of the savanna rainfall threshold (~650 mm MAP) and the presence / absence of fire in understanding savanna dynamics and woody cover change in the context of global drivers such as elevated atmospheric CO2.
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  • Date Issued: 2018

The application of GIS and remote sensing to assess the effect of periodic flooding on communities along the Juskeiriver: A case study of Alexandria Township, Johannesburg, South Africa

  • Authors: Mawasha, Tshepo Sylvester
  • Date: 2016
  • Subjects: Remote sensing Geographic information systems -- South Africa , Remote sensing
  • Language: English
  • Type: Thesis , Masters , MSc
  • Identifier: http://hdl.handle.net/10948/45613 , vital:38918
  • Description: Floods are water induced disasters that led to temporary induction of dry and cause serious damages in the affected location such as loss of valuable assets, lives and destruction of infrastructure. Flooding had become common in Alexandra Township during rainfall season and the recorded impact of periodic flooding on communities is increasing at an alarming rate. This study seeks to identify populations vulnerable to flooding and to map-out areas at high risk of flood disasters, using GIS and RS as a tool. For GIS application different types of maps were produced, namely, flood vulnerability, hazards, risk and risk index map highlighting areas at risk of being affected by flooding. Flood risk index maps identify three categories of risk zones; low and high risk zone. The household units within each of the risk zones was calculated and the total was estimated to be 762 for low-risk and 32 486 for high risk zone. The SRTM Digital Elevation Model (DEM) and multi-temporal Satellite Probatoire d’Observation de la Terra (SPOT) satellite images for 1997, 2006 and 2013 of the area was used for land-use and land-cover (LULC) change analyses using maximum-likelihood post-classification comparison. Results reveal that tremendous urban development had taken place in the study area along the Jukskei River area for the past sixteen years. It was observed that there was a sharp decrease in vegetation from 237ha (1997) to 134ha (2006) to 68ha (2013). This may had a negative impact on the environment around this area by decreasing surface runoff. The trend however, shows that bare surface and vegetation land-cover class has no potential to recover. Questionnaires aimed at all the residents in the study area were used to assess the effect of periodic flooding on communities. Community leader and City of Johannesburg Disaster Management Unit (CoJDMU) interviews were also conducted to get more insight about floods management in the study area. Finally, strategies for alleviating flood risk in the study area were discussed and some recommendations were made to help the government and municipal authorities to improve and development sustainable flood mitigation measures.
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  • Date Issued: 2016

A multiscale remote sensing assessment of subtropical indigenous forests along the wild coast, South Africa

  • Authors: Blessing, Sithole Vhusomuzi
  • Date: 2015
  • Subjects: Forests and forestry -- South Africa -- Remote sensing , Forest conservation , Remote sensing , Geographic information systems
  • Language: English
  • Type: Thesis , Doctoral , PhD
  • Identifier: vital:10677 , http://hdl.handle.net/10948/d1021169
  • Description: The subtropical forests located along South Africa’s Wild Coast region, declared as one of the biodiversity hotspots, provide benefits to the local and national economy. However, there is evidence of increased pressure exerted on the forests by growing population and reduced income from activities not related to forest products. The ability of remote sensing to quantify subtropical forest changes over time, perform species discrimination (using field spectroscopy) and integrating field spectral and multispectral data were all assessed in this study. Investigations were conducted at pixel, leaf and sub-pixel levels. Both per-pixel and sub-pixel classification methods were used for improved forest characterisation. Using SPOT 6 imagery for 2013, the study determined the best classification algorithm for mapping sub-tropical forest and other land cover types to be the maximum likelihood classifier. Maximum likelihood outperformed minimum distance, spectral angle mapper and spectral information divergence algorithms, based on overall accuracy and Kappa coefficient values. Forest change analysis was made based on spectral measurements made at top of the atmosphere (TOC) level. When applied to the 2005 and 2009 SPOT 5 images, subtropical forest changes between 2005-2009 and 2009-2013 were quantified. A temporal analysis of forest cover trends in the periods 2005-2009 and 2009-2013 identified a decreasing trend of -3648.42 and -946.98 ha respectively, which translated to 7.81 percent and 2.20 percent decrease. Although there is evidence of a trend towards decreased rates of forest loss, more conservation efforts are required to protect the Wild Coast ecosystem. Using field spectral measurements data, the hierarchical method (comprising One-way ANOVA with Bonferroni correction, Classification and Regression Trees (CART) and Jeffries Matusita method) successfully selected optimal wavelengths for species discrimination at leaf level. Only 17 out of 2150 wavelengths were identified, thereby reducing the complexities related to data dimensionality. The optimal 17 wavelength bands were noted in the visible (438, 442, 512 and 695 nm), near infrared (724, 729, 750, 758, 856, 936, 1179, 1507 and 1673 nm) and mid-infrared (2220, 2465, 2469 and 2482 nm) portions of the electromagnetic spectrum. The Jeffries-Matusita (JM) distance method confirmed the separability of the selected wavelength bands. Using these 17 wavelengths, linear discriminant analysis (LDA) classified subtropical species at leaf level more accurately than partial least squares discriminant analysis (PLSDA) and random forest (RF). In addition, the study integrated field-collected canopy spectral and multispectral data to discriminate proportions of semi-deciduous and evergreen subtropical forests at sub-pixel level. By using the 2013 land cover (using MLC) to mask non-forested portions before sub-pixel classification (using MTMF), the proportional maps were a product of two classifiers. The proportional maps show higher proportions of evergreen forests along the coast while semi-deciduous subtropical forest species were mainly on inland parts of the Wild Coast. These maps had high accuracy, thereby proving the ability of an integration of field spectral and multispectral data in mapping semi-deciduous and evergreen forest species. Overall, the study has demonstrated the importance of the MLC and LDA and served to integrate field spectral and multispectral data in subtropical forest characterisation at both leaf and top-of-atmosphere levels. The success of both the MLC and LDA further highlighted how essential parametric classifiers are in remote sensing forestry applications. Main subtropical characteristics highlighted in this study were species discrimination at leaf level, quantifying forest change at pixel level and discriminating semi-deciduous and evergreen forests at sub-pixel level.
  • Full Text:
  • Date Issued: 2015

Monitoring carbon stocks in the sub-tropical thicket biome using remote sensing and GIS techniques : the case of the Great Fish River Nature Reserve and its environs, Eastern Cape province, South Africa

  • Authors: Nyamugama, Adolph
  • Date: 2013
  • Subjects: Fragmented landscapes -- South Africa -- Eastern Cape -- Remote sensing , Environmental degradation -- South Africa -- Eastern Cape , Remote sensing , Geographic information systems
  • Language: English
  • Type: Thesis , Doctoral , PhD
  • Identifier: vital:10672 , http://hdl.handle.net/10948/d1020303
  • Description: The subtropical thicket biome in the Eastern Cape Province of South Africa has been heavily degraded and transformed due overutilization during the last century. The highly degraded and transformed areas exhibit a significant loss of above ground carbon stocks (AGC) and loss of SOC content. Information about land use /cover change and fragmentation dynamics is a prerequisite for measuring carbon stock changes. The main aim of this study is to assess the trends of land use/cover change, fragmentation dynamics, model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, quantify and map the spatial distribution of SOC concentrations in the partial subtropical thicket cover in the Great Fish River Nature Reserve and environs (communal rangelands). Multi-temporal analyses based on 1972 Landsat MSS, 1982 and 1992 Landsat TM, 2002 Landsat ETM and 2010 SPOT 5 High Resolution images were used for land use/cover change detection and fragmentation analysis. Object oriented post-classification comparison was applied for land use/cover change detection analysis. Fragmentation dynamics analysis was carried out by computing and analyzing landscape metrics in land use/cover classes. Landscape fragmentation analyses revealed that thicket vegetation has increasingly become fragmented, characterized by smaller less linked patches of intact thicket cover. Landscape metrics for intact thicket and degraded thicket classes reflected fragmentation, as illustrated by the increase in the Number of Patches (NP), Patch Density (PD), Landscape Shape Index (LSI), and a decrease in Mean Patch Size (MPS). The use of remote sensing techniques and landscape metrics was vital for the understanding of the dynamics of land use/cover change and fragmentation. Baseline land use/cover maps produced for 1972, 1982, 1992 2002 and 2010 and fragmentation analyses were then used for analyzing carbon stock changes in the study area. To model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, a method based on the integration of RS and GIS was employed for the estimation of AGC stocks in a time series. A non-linear regression model was developed using NDVI values generated from SPOT 5 HRG satellite imagery of 2010 as the independent variable and AGC stock estimates from field plots as the dependent variable. The regression model was used to estimate AGC stocks for the entire study area on the 2010 SPOT 5 HRG and also extrapolated to the 1972 Landsat MSS, 1982 and 1992 Landsat TM, and 2002 Landsat ETM. The AGC stocks for the period 1972 -1982, 1982-1992, 1992-200) and 2002-2010 were compared by means of change detection analysis. The comparison of AGC stocks was carried out at subtropical thicket class level. The results showed a decline of AGC stocks in all the classes from 1972 to 2010. Degraded and transformed thicket classes had the highest AGC stock losses. The decline of AGC stocks was attributed to thicket transformation and degradation which were caused by anthropogenic activities. To map and quantify SOC concentration in partial (fractional) thicket vegetation cover, the spectral reflectance of both thicket vegetation and bare-soils was measured in situ. Soil samples were collected from the sampling sites and transported to the laboratory for spectral reflectance and SOC measurements. Thicket vegetation and bare soil reflectance were measured using spectroscopy both in situ and under laboratory conditions. Their respective endmembers were extracted from ASTER imagery using the Pixel Purity Index (PPI). The endmembers were validated with in situ and laboratory thicket and bare-soil reflectance signatures. The spectral unmixing technique was applied to ASTER imagery to discriminate pure pixels of thicket vegetation and bare-soils; a residual spectral image was produced. The Residual Spectral Unmixing (RSU) procedure was applied to the residual spectral image to produce an RSU soil spectrum image. Partial Least Squares Regression (PSLR) model was developed using spectral signatures of a residual soil spectrum image as the independent variable and SOC concentration measured from soil samples as the dependent variable. The PSLR prediction model was used to predict SOC concentration on the RSU soil spectral image. The predicted SOC concentration was then validated with SOC concentration measured from the field plots. A Strong correlation (R2 = 0.82) was obtained between the predicted SOC concentration and the SOC concentration measured from field samples. The PSLR was then used to generate a map of SOC concentration for the Great Fish River Nature Reserve and its environs. Areas with very low SOC concentrations were found in the degraded communal villages, as opposed to the higher SOC values in the protected area. The results confirmed that RS techniques are key to estimating and mapping the spatial distribution of SOC concentration in partial subtropical thicket vegetation. Partial thicket vegetation has a huge influence on the soil spectra; it can influence the prediction of SOC concentration. The use of the RSU approach eliminates partial thicket vegetation cover from bare soil spectra. The residual soil spectrum image contains enough information for the mapping of SOC concentration. The technique has the potential to augment the applicability of airborne imaging spectroscopy for soil studies in the sub-tropical thicket biome and similar environments.
  • Full Text:
  • Date Issued: 2013
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