School of Geography, Archaeology and Environmental Studies (ETDs)

Permanent URI for this communityhttps://hdl.handle.net/10539/38007

Browse

Start date: 2020Subject: search.filters.subject.SDG-13: Climate action

Search Results

Now showing 1 - 10 of 24
  • Thumbnail Image
    Item
    Spatiotemporal characteristics of surface water in Sua Pan, Botswana, using Earth Observation data: 1992–2022
    (University of the Witwatersrand, Johannesburg, 2024-10) Peplouw, Muchelene Tiara; Adam, Elhadi; Grab, Stefan
    Surface water is a critical resource for sustaining both human and ecological health. However, climate change and human actions threaten its availability in semi-arid regions like Botswana. In addition, current research on monitoring and understanding surface water dynamics in Botswana lacks the application of remote sensing and machine learning. This highlights a crucial gap in knowledge that this study aims to address. This study investigates the spatiotemporal dynamics of land use/land cover (LULC) and surface water extent changes in Sua Pan, Botswana, from 1992 to 2022. Employing remote sensing, machine learning, and statistical techniques, the research offers valuable insights into the intricate relationships between land cover modifications, surface water variations, and climatic variables. Google Earth Engine (GEE) facilitated efficient analysis of Landsat imagery for LULC mapping. Random Forest (RF) effectively classified several land cover types within Sua Pan. To address the challenges of saline environments, a novel water index, the Saline Water Index (SWI), was developed specifically for Sua Pan. The McNemar statistical test compared the performance of SWI to established indices like the Modified Normalised Difference Water Index (MNDWI) and the Normalised Difference Salinity Index (NDSI). Surface water variations were analysed using homogeneity tests and the Mann-Kendall trend test. The relationships between hydro climatic data (rainfall, evapotranspiration, land surface temperature) retrieved from GEE and surface water area for both wet and dry seasons were evaluated using Pearson correlation coefficients and visualised by line and area graphs. Additionally, the influence of the El Niño Southern Oscillation (ENSO) on rainfall and surface water area was assessed using Analysis of Variance (ANOVA) to identify the specific ENSO phases that exert an influence. The findings demonstrate the effectiveness of GEE for LULC mapping with the RF algorithm, achieving moderate to high classification accuracy (65.2% - 90.69%) and Kappa coefficients (0.54 - 0.85). Surface water and bare area exhibited increasing trends (coefficients: 13.017 and 9.0609, respectively), whereas vegetation and salt hard pan showed decreasing trends (-16.786 and -5.3081, respectively). The newly developed SWI outperformed MNDWI and NDSI in detecting surface water, achieving the highest overall accuracy (94%) compared to MNDWI (64%) and NDSI (59%). The McNemar test confirmed no significant statistical difference between the SWI map and the validation dataset (p = 0.2673), while both MNDWI and NDSI maps showed significant differences (p < 0.0001). Utilising SWI, the study revealed that surface water was most prevalent in central and northeastern regions, with an average coverage of 33%. Seasonal homogeneity tests indicated a non-homogenous distribution of surface water area in wet seasons, with abrupt changes in 1994 and 2003. Conversely, dry seasons exhibited a homogenous distribution. The Mann-Kendall trend test identified a statistically significant (p-value = 0.01) but weak positive trend (tau = 0.329) for surface water areas in wet seasons. In contrast, the dry seasons displayed a non-significant (p-value = 0.734) and a very weak positive trend (tau = 0.043). Surface water area, rainfall, evapotranspiration, and temperature consistently increase during the wet seasons compared to the dry seasons. Notably, increased evapotranspiration significantly impacted surface water presence. ENSO exhibited no significant influence on either rainfall or surface water extent (p-value > 0.05 for both). These findings highlight the potential of earth observation data for real-time surface water monitoring in salt pans. The developed techniques offer valuable insights for policy decisions regarding environmental management and conservation efforts in Sua Pan. In addition, the study emphasises the importance of cost-effective approaches for water change assessment, particularly appropriate for under-resourced regions.
  • Thumbnail Image
    Item
    The Influence of Climate Change on the Speed of Movement of Tropical Cyclones in the South Indian Ocean
    (University of the Witwatersrand, Johannesburg, 2024-07) Mahomed, Aaliyah; Fitchett, Jennifer
    Recent studies on the speed of movement of tropical cyclones indicate that anthropogenic warming has resulted in a 10% global decrease of tropical cyclone translation speeds over the period 1949-2016. The recent increase in high intensity storms could severely impact Southern Hemisphere regions which are considerably more vulnerable than their Northern Hemisphere counterparts. High intensity storms occurring at a lower speed would worsen the impacts of tropical cyclones resulting in prolonged periods of flooding, storm surges, and winds. This would subsequently lead to a loss of lives, economic loss and infrastructural and agricultural damage. However, studies have challenged this slowdown, suggesting that the transition to the geo-stationary era, introduces heterogeneity to tropical cyclone data. Additionally, imprecise estimates of tropical cyclone frequency influences the average speed of tropical cyclones, thereby impacting trend analysis. Using tropical cyclone data from National Oceanic and Atmospheric Administration (NOAA) International Best Track Archive for Climate Stewardship (IBTrACS), this study explores the current translation speed debate for the South Indian Ocean, over the period 1991-2021. The results of this study indicate that the translation speed of tropical cyclones has increased at a rate of 0.06km/h/yr over the 30-year period (r = 0.06 p = 0.19). Whilst the translation speed debate remains at an aggregated global scale, a comprehensive understanding of the influence of climate change on tropical cyclones is crucial for generating forecasts as this enables vulnerable regions to plan and adjust to evolving tropical cyclones.
  • Thumbnail Image
    Item
    Assessing the Validity of the Exclusion of Night-time Thermal Comfort in Tourism Climate Indices
    (University of the Witwatersrand, Johannesburg, 2024-09) Mnguni, Zandizoloyiso; Fitchett, Jennifer
    Biometeorological indices are instruments that can be used to streamline complex climatic information for economic and other decision-making. Indices hold inherent assumptions where the use of an index is only reliable and valuable if those assumptions are true. The Holiday Climate Index (HCI) is presented as the improved version of the TCI, with a key difference being the removal of night-time thermal comfort due to the assumption that air conditioning is ubiquitous throughout Europe. This study investigated the validity of this exclusion of night-time thermal comfort in tourism climate indices, particularly for the HCI using the six European cities for which the index was developed – Barcelona, Stockholm, London, Istanbul, Paris and Rome. The assumption of ubiquitous air conditioning was investigated using Booking.com accommodation listings, the night-time economy and prevalence of night-time activities outside of each accommodation establishment, and whether tourists experienced adverse thermal comfort during the night through posted reviews. Without the air conditioning filter applied, the proportion of listings categorized as offering air conditioning ranged from 28.8% for Stockholm to 98.9% for Rome. With the filter applied, the proportions ranged from 96.4% for Stockholm and 99.0% for Paris. A total of 24,252 TripAdvisor reviews were also examined for both accommodation establishments and night-time tourist activities. The reviews were manually examined for the mention of weather, climate, night-time temperature and air conditioning. The findings of this study exhibit a range of night-time activities, many of which are outdoors, where tourists did comment on night-time thermal comfort. The research disproves the claim of the original authors, and it was found that air conditioning is not ubiquitous. Therefore, the assumption that the HCI is based on is problematic, and the index should be used with caution. Moreover, a similar approach in index validity testing should be performed prior to future studies seeking to apply indices.
  • Thumbnail Image
    Item
    Modelling for Rainwater Harvesting Structures Using Geospatial Techniques
    (University of the Witwatersrand, Johannesburg, 2024-10) Makaringe, Precious Nkhensani; Atif, Iqra
    Climate change poses a significant threat, leading to droughts, floods, and hindering sustainable development. Water scarcity is a growing concern, particularly in developing countries like South Africa, where limited freshwater resources are further strained by climate variability. This research explores the potential of rainwater harvesting (RWH) as a strategy to address water scarcity in such regions. This study aims to model potential rainwater harvesting sites in Lynwood Park, Pretoria, South Africa, utilising geospatial techniques. Object-Based Image Classification (OBIC) was employed to extract building footprints from high-resolution satellite imagery. Microsoft and Google building footprints were utilised to determine the suitable automated building footprints for Lynnwood Park. ArcGIS Pro software served as the primary platform for spatial data analysis and mapping potential RWH sites. Data integration included high-resolution satellite imagery, a Digital Elevation Model (DEM), building footprints, and rainfall data. Additionally, questionnaires were distributed to estimate population and water demand within the study area. The research demonstrates the efficacy of geospatial tools in identifying suitable locations for RWH systems. Indicating that steeper slopes in the southern region of Lynnwood Park have limited collection from large rooftops, while the flatter north offered greater potential. Rainfall graphs and PRWH results suggest that over half of Lynwood Park's annual water demand could be met through rooftop rainwater collection. However, factors such as system losses due to evaporation, inefficiencies in collection and storage, and variability in rooftop sizes across different buildings would need to be incorporated into more detailed models, as well as water quality analysis for rooftop harvested water in future studies. This study highlights the potential of RWH as a viable water security strategy in water-scarce regions. The findings contribute to the development of geospatial approaches for RWH implementation, promoting water security and sustainability in a changing climate.
  • Thumbnail Image
    Item
    Remote sensing-based assessment of mangrove forest changes and related regulatory frameworks for the sustainability and conservation of coastal ecosystems in Zanzibar Island, Tanzania-East Africa
    (University of the Witwatersrand, Johannesburg, 2024-10) Mohamed, Mohamed Khalfan; Adam, Elhadi
    Mangroves are vital components of the world's coastal ecosystems, yet they face significant threats from storm surges, tidal waves, commercial aquaculture, and expanding human settlements. These challenges have heightened the need for accurate mangrove maps to gauge ecosystem degradation. However, mapping mangroves at species and community levels is challenging due to the inaccessibility of these environments. Remote sensing offers an efficient alternative to conventional field-based methods by enabling data collection in these challenging ecosystems. This study aimed to apply remote sensing techniques to map mangrove forest changes and species in two protected bays in Zanzibar, Tanzania. The thesis focuses on four key areas. First, it examines the history of mangrove management in Zanzibar, from colonial times (1890) to the present, highlighting policies, laws, and community involvement in conservation. The colonial authority implemented several land administration laws and regulations to protect mangrove forests. However, mangrove forests suffered significant degradation from 1930 to the end of World War II. The post-independence policy framework established the legal foundation for the introduction of community involvement in mangrove conservation. The legal foundation for introducing community participation in mangrove protection was established by post-independence policy structures such as the National Forest Conservation and Management Act of 1996. Nevertheless, sustainable mangrove use remains inadequate. Second, the study compared community perceptions of mangrove ecosystem services using chi-squared tests and one-way ANOVA. Household surveys showed that provisioning services (PS) were the most identified (84%). Supporting (SS), regulating (RS), and cultural services (CS) were rated by 46.2%, 45.4%, and 21.0%, respectively. Statistical analyses indicated significant differences in the awareness of RS (χ2 = 6.061, p = 0.014) and SS (χ2 = 6.006, p = 0.014) between Chwaka, Charawe, Ukongoroni, Unguja Ukuu, and Uzi wards. There were no significant differences in the identification of PS (χ2 = 1.510, p = 0.919) and CS (χ2 = 1.601, p = 0.901). The study found that residents’ occupations did not determine their reliance on mangrove ecosystem services (χ2 = 8.015; p = 0.1554). Third, changes in mangrove cover in Menai Bay and Chwaka Bay between 1973 and 2020 were analyzed using Landsat data. TerrSet geospatial software was used to classify land cover. The SEGMENTATION module grouped pixels based on spectral similarity, and the images segments were transformed into training sites and signature classes using the SEGTRAIN module. Finally, the segments were classified with the SEGCLASS module into a pixel-based land cover map. Separation of land cover classes was determined using the Jeffries–Matusita (J-M) distance and the transformed divergence (TD) index. For Chwaka Bay, overall classification accuracy ranged from 82.5% to 92.7%, while for Menai Bay, it ranged between 85.5% and 94.5%. Producer and user accuracies ranged from 72% to 100%, with kappa coefficients (κ) between 0.72 and 0.90. Menai Bay experienced a 6.8 ha yearly decline in mangrove cover between 1973 and 2020, while Chwaka Bay saw a 48.5 ha annual decrease. Fourth, the study aimed to map mangrove species in Menai Bay using metrics extracted from the Landsat 9 OLI-2 dataset, i.e., vegetation indices (VIs) and gray-level co-occurrence matrices (GLCMs). A critical step in this study was identifying the contribution of vegetation indices and texture features to classifying mangroves. Training data from very high-resolution (VHR) unmanned aerial vehicle (UAV) data covering parts of the study area helped identify five major mangrove species, i.e., Rhizophora mucronata, Ceriops tagal, Sonneratia alba, Avicennia marina, and Bruguira gymnorrhiza. Results showed that textural features attained overall classification accuracy of 68.29% (kappa = 0.62) and 67.07% (kappa = 0.60) for random forest (RF) and support vector machine (SVM), respectively. Vegetation indices (VIs) recorded overall accuracy of 72.64% (kappa = 0.67) and 67.78% (kappa = 0.61) for RF and SVM. Overall, this study demonstrates the potential of remote sensing technologies for mapping mangrove forest changes and species in challenging environments like Zanzibar’s protected bays. By integrating historical policy analysis with modern geospatial techniques, the research highlights the significant role of both legal frameworks and community involvement in mangrove conservation. The community surveys underscore the varying perceptions of mangrove ecosystem services across different wards, with provisioning services being the most recognized. These findings underscore the importance of advancing remote sensing applications and refining conservation strategies to ensure the sustainability of mangrove ecosystems. Additionally, the analysis of long-term changes in mangrove cover from 1973 to 2020 reveals a concerning decline, particularly in Chwaka Bay. Lastly, the study’s classification of mangrove species using Landsat 9 OLI-2 data, vegetation indices, and texture metrics achieved notable accuracy, emphasizing the value of remote sensing in distinguishing species-level characteristics.
  • Thumbnail Image
    Item
    Assessing the inter-annual and inter-seasonal climate-induced variation in caseload of respiratory diseases
    (University of the Witwatersrand, Johannesburg, 2024-06) Motlogeloa, Ogone
    In South Africa, acute upper respiratory diseases pose a significant public health challenge, influenced heavily by climatic factors. Recognizing the critical need for detailed seasonal analysis. This thesis delves into the inter-annual and inter-seasonal impacts of climate on disease caseloads, offering four pivotal contributions to health biometeorology. The first contribution refines the understanding of the acute upper respiratory disease season in South Africa, previously recognized as the winter months of May to September. This research provides a more granular analysis by pinpointing specific onset timings and fluctuations within the season that are crucial for optimizing healthcare responses, particularly in vaccination schedules. The second contribution is an in-depth analysis of climatic variables affecting acute upper respiratory disease prevalence. Utilizing Spearman's correlation analyses and the Distributed Lag Non-linear Model across Johannesburg, Cape Town, and Gqeberha, this study identifies negative correlations between temperature and disease cases, pinpointing significant risk thresholds most prevalent during the winter peak. The third contribution investigates the impact of extreme climate events (ECEs) over twelve years, elucidating how, while individual ECEs influence medical aid claims and disease incidence, it is the broader seasonal patterns that predominantly dictate acute upper respiratory disease prevalence. The fourth contribution offers a nuanced exploration of the climate-health nexus, demonstrating that routine weather variations play a more significant role in the peak transmission of acute upper respiratory viruses than extreme events. This thesis elucidates the substantial yet nuanced influence of climate on respiratory health in South Africa. By specifying the disease season with greater precision and clarifying the relationship between temperature variations and disease prevalence, the research provides essential data for health practitioners to plan targeted interventions. This study moves beyond the focus on extreme weather events to expose the subtler, yet more consistent, impact of seasonal climate shifts on health outcomes, enriching our understanding and serving as a vital reference for enhancing disease preparedness in an era marked by climatic uncertainty.
  • Thumbnail Image
    Item
    The Wind Energy Potential of South Africa’s Eastern Cape Province in a Changing Climate
    (University of the Witwatersrand, Johannesburg, 2024-10) Landwehr, Gregory Brent; Engelbrecht, Francois; Lennard, Chris
    Due to the abundance of wind and solar renewable energy resources across South Africa, and the comparative low cost of installation and operation of wind and solar energy infrastructure, it is inevitable that the country’s dependence on fossil fuels for energy will decline in the future. At a practical level, developing wind energy facilities entails a complex array of activities and the ~20-30 year life spans of such facilities intrinsically implies that they will experience climate change. However, insufficient research and related modelling have been undertaken in South Africa to quantify future variability and systematic changes in the wind resource as it relates to specific synoptic weather types and wind energy production. The aim of this thesis is to develop methodologies to understand the synoptic drivers of regional wind energy production potential and in turn assess how and why South Africa’s wind energy production potential may change as a function of changing circulation patterns in a changing climate. The wind energy potential of the Eastern Cape Province of South Africa is quantified using energy yield analysis techniques. These results are mapped onto commonly occurring synoptic types for the region to assign an energy potential to each. When the changing frequency of these synoptic weather types is calculated in a climate change impacted future using Global Climate Models, it is possible to quantify the change in wind energy potential in the long term. Results show that the synoptic-circulation pattern with the highest wind energy potential is the Atlantic Ocean ridging High with its centre at about 30 °S, behind a northward displaced mid-latitude cyclone. Global Climate Model projections of the frequency occurrence of these high energy synoptic states show a decrease in frequency at all global warming temperature thresholds and in turn a decrease in wind energy production. The likely cause of this being the poleward expansion of the descending limb of the Hadley circulation which shifts these synoptic systems southwards. The methodologies presented in this thesis provide South Africa with the necessary climate change risk assessment and mitigation capability to address these impacts on the wind energy sector in South Africa.
  • Thumbnail Image
    Item
    Peat dynamics in the Angolan Highlands
    (University of the Witwatersrand, Johannesburg, 2023-03) Lourenco, Mauro Cesar; Woodborne, Stephan; Fitchett, Jennifer
    The Angolan Highlands is a war stricken, threatened, and under-studied area. The region is hydrologically and ecologically important and supports extensive tropical peatland deposits. Peatland preservation has been acknowledged to address climate change, is sensitive to drought and fire, and is directly influenced by vegetation and hydrological conditions. However, little research has been conducted in the Angolan Highlands. This study addresses gaps in the literature through four key contributions. The first is a critical review of peat definitions: the implications of disparate definitions are detailed, and a new proposed definition for peatlands in the interest of climate science is provided. The second is the first map of peatland extent in the Angolan Highlands, containing details on the age and growth dynamics. The study presents a conservative estimate of peatland extent that is much larger than previously estimated for Angola and is a crucial first step in facilitating the preservation of this deposit. The third contribution is the first historical assessment of drought and vegetation response in the region. This contains a 40-year drought and 20-year vegetation history, demonstrating that drought occurrence is increasing and there is a strong relationship between precipitation and the peatland vegetation region. The fourth contribution is the first assessment of the contemporary (2001-2020) fire regime of these peatlands, and reveals that among all land cover classes, peatlands burn more frequently and at a higher proportion. Investigation into the peat dynamics of the Angolan Highlands indicate that they have critical importance and are naturally resistant to both droughts and fire. Failure to preserve these deposits will have direct implications on the communities, environment, and surrounding areas.
  • Thumbnail Image
    Item
    Estimating rooftop solar energy potential using spatial radiation models and thermal remote sensing: The case of Witwatersrand University
    (University of the Witwatersrand, Johannesburg, 2023) Ndemera, Rudo Hilda; Adem, Ali K.; Adam, Elhadi
    The main purpose of this research was to estimate the University of Witwatersrand building’s rooftop solar energy potential using the GIS-based solar Area Solar Radiation (ASR) analyst upward hemispherical view shed algorithm. The two major datasets used in this research for rooftop solar energy potential modelling are building footprint data and the Digital Surface Model. Building footprint data, specifically rooftop area was extracted using machine learning CNTK unified toolkit and deep neural networks. The data was presented as individual polygon shape files for each building. The high-resolution Digital Surface Model imagery was sourced from the Advanced Land Observation Satellite. Pre-processing of the imagery was done for atmospheric correction. The DSM was then used in the Area Solar Radiation model to create an upward view shed for every point on the study area which is essential for computing solar radiation maps. The efficiency of using this algorithm is that it considers the shading effects caused by surrounding topography and surrounding man-made features, alterations in the azimuth angle and the position of the sun. Apart from the incoming solar radiation reaching the rooftops, the elevation and orientation of the rooftop cells limit the solar panel tilt angle and intensity of the incoming solar radiation, respectively. These factors were used in setting the suitability criteria together with solar radiation for the identification of suitable rooftop cells in this research. The relationship between land surface temperature and solar radiation values was assessed to determine if it can be used as an indicator for solar panel efficiency. Results from this research indicate that the University of Witwatersrand receives high levels of incoming solar radiation and has a high solar energy rooftop generation capacity that can meet the energy demand on campus. To improve accuracy of the research results, a drone could have been used to measure insolation across the study area to improve the spatial resolution. However, this was not possible due to various restrictions.
  • Thumbnail Image
    Item
    Mapping and monitoring land transformation of Boane district, Mozambique (1980 – 2020), using remote sensing
    (University of the Witwatersrand, Johannesburg, 2023) Dengo, Claudio Antonio; Atif, Iqra; Adam, Elhadi
    Although natural and environmental factors play a significant role in land transformation, human actions dominate. Therefore, to better understand the present land uses and predict the future, accurate information describing the nature and extent of changes over time is necessary and critical, especially for developing countries. It is estimated that these countries will account for 50% of the world's population growth in the next few years. Hence, this research was an attempt to assess and monitor land cover changes in Boane, Mozambique, over the past 40 years and predict what to expect in the next 30 years. This district has been challenged by a fast-growing population and land use dynamic, with quantitative information, driving forces and impacts remaining unknown. Through a supervised process in a cloud base Google Earth Engine platform, a set of five Landsat images at ten-year intervals were classified using a random forest algorithm. Seven land classes, i.e., agriculture, forest, built-up, barren, rock, wetland and water bodies, were extracted and compared through a pixel-by-pixel process as one of the most precise and accurate methods in remote sensing and geographic information system applications. The results indicate an active alternate between all land classes, with significant changes observed within agriculture, forest and build-up classes. As it is, while agriculture (-26.1%) and forest (-21.4%) showed a continuously decreasing pattern, build-up class (45.8%) increased tremendously. Consequently, over 69% of the forest area and 59% of the agricultural area shifted into build-up, i.e., was degraded or destroyed. Similarly, the conversion of barren land area (57.2%) and rock area (47.3%) into build-up indicates that those areas were cleaned. The overall classification accuracy averaged 90% and a kappa coefficient of 0.8779 were obtained. The CA-Markov model, used to assess future land uses, indicates that build-up will continue to increase significantly, covering 60% of the total area. From this finding, the land cover situation in the next 30 years will be critical if no action is taken to stop this uncontrolled urban sprawl. An adequate land use plan must be drawn, clearly indicating the locations for different activities and actions for implementation.