Electronic Theses and Dissertations (PhDs)
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Item A geographical analysis of the impacts of construction and demolition waste on wetland functionality in South Africa: a study of Gauteng province(University of the Witwatersrand, Johannesburg, 2024-09) Mangoro, Ngonidzashe; Kubanza, Nzalalemba Serge; Mulala, Danny SimateleThe purpose of this study was to investigate construction and demolition waste management processes in sub-Saharan Africa and how they affect wetland ecosystems, using South Africa as a case study. Construction and demolition (CDW) waste has become a massive urban environmental challenge on a global scale, but more so in developing countries found in sub-Saharan Africa. In the context of South Africa, construction and demolition waste is not a waste stream taken seriously by local and national authorities because it is ‘general waste that does not pose an immediate threat to the environment. This position is premised on the idea that construction and demolition waste is generally inert (chemically inactive) and therefore cannot cause an immediate environmental risk. In this study, it is argued that the environmental risk of waste goes beyond the embedded chemical constituencies because some waste streams can cause immediate environmental risk through their physical properties depending on the location of disposal. It is further argued that although CDW is generally inert, disposal in wetlands immediately disrupts the way wetland ecosystem’s function, causing several environmental risks. To mitigate the environmental threats posed by construction and demolition waste, this study proposes a change in the methodological approaches and strategies deployed to manage the waste stream, such as by introducing a hybrid of circular economy and industrial ecology to minimize or eliminate waste production. This study involved several data collection and analysis methods. Using a combination of qualitative and quantitative studies methods, data was collected with the goal to understand the perceptions of experts on how construction and demolition waste management in South Africa affects wetland ecosystems and what can be done to effectively manage the waste stream in the context of a developing country. Data informing this study were collected through semi-structured interviews and surveys in the province of Gauteng, specifically in the City of Johannesburg and City of Ekurhuleni Municipalities, where there is massive illegal dumping in wetlands for various reasons. Furthermore, apart from the use of semi-structured interviews and surveys, a digital elevation model was generated in ArcGIS Pro 10.1 software to measure the effects of construction and demolition waste on wetlands in the study area. The approach to this study using both qualitative and quantitative methods was crucial because it provided human perceptions which were accurately corroborated by GIS software. The study found that construction and demolition waste management in South Africa is affected by several challenges that lead to massive illegal dumping in critical ecological ecosystems such as wetlands. In a broad sense, the major challenge to sustainable construction and demolition waste management in South Africa is institutional failure at both the local and national levels. Local authorities such as municipalities are characterized by massive corruption, poor funding, and lack of strategic technologies among other things, while at the national level, there is massive interference with municipal affairs through bureaucratic delays in the disbursement of municipal funds. A combination of these and other factors leads to illegal dumping of construction and demolition waste across the Gauteng Province, particularly in wetlands in low-income areas. The data informing this study reveals that dumping construction and demolition waste in wetlands causes an immediate threat to the existence of wetlands through massive sedimentation with insoluble materials. It is ultimately found that construction and demolition waste destroy the ability of wetlands to offer ecosystem services such as flood attenuation, carbon sequestration, water filtration, and habitat provision, among other functions, leading to environmental events such as flooding. A combination of circular economy and industrial ecology can be one of the ways that can be deployed to effectively and sustainably manage construction and demolition waste in South Africa. The circular economy and its three principles of ‘reduce’, ‘recycle’, and ‘reuse’ has been successfully deployed in developed countries in the European Union, where recycling has topped 70% of the total construction waste generated. Industrial ecology with its analogy of industrial ecoparks has been deployed in the European Union with immense success, until more attention was directed to circular economy. With an increase in municipal funding and introduction of a construction waste information system, a combination of ‘circular economy’ and ‘industrial ecology’ can significantly help to reduce pressure on wetlands and the environment at large. Even though the methodological improvements suggested above could significantly reduce pressure on wetlands, the implementation could be faced with institutional challenges. Therefore, it is argued that urgent institutional transformation is required to make tangible changes in the field of construction and demolition waste management. It is recommended that there should be increased law enforcement to curb widespread illegal dumping in South Africa’s major cities. It is also recommended that, like in Europe, South Africa must introduce tailor-made legislation of policies for construction and demolition waste alone. Promulgation of dedicated legislation provides clear direction on how the waste stream is managed and who is responsible for specific roles. Furthermore, dedicated legislation can be a crucial tool to deliver sustainable construction and demolition waste management in South Africa because it can be used to encourage the use of recycled aggregates and limit the amount of illegal dumping or extraction of materials from the environment. Finally, dedicated construction and demolition waste legislation can be used to shift from the traditional view of pollution or contamination through toxicity, and so the value of this study is immediately apparent.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, ElhadiMangroves 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.Item Integrating Sentinel-1/2 and machine learning models for mapping fruit tree species in heterogeneous landscapes of Limpopo(University of the Witwatersrand, Johannesburg, 2024-10) Chabalala, Yingisani Winny; Adam, ElhadiFrom ancient times to this century, Africa has relied chiefly on agriculture for survival. Crop type maps are crucial for agricultural management, sustainable farming systems, and realizing food security. Agronomists, agricultural extension officers, policymakers, and the government rely on crop type spatial distribution information to make informed decisions and optimize resource allocation for sustainable agricultural management. Attaining food security for all is an urgent need in Africa. However, the farming landscapes predominately comprise fragmented smallholder heterogeneous farms. The farming systems include intercropping and cultivating different crops that require different management strategies. This results in within-class spectral similarities and intra-spectral variability due to similar canopy structures and different phenologies, which complicates the application of remote sensing in crop type mapping. The free availability of Copernicus products such as Sentinel 1 and 2 have high temporal, spectral, and spatial resolution suitable for mapping smallholder agriculture. Thus, this research aimed to integrate Sentinel-1/2 and machine learning models for mapping fruit tree species in heterogeneous landscapes of Limpopo. First, the research tested the applicability of sampling techniques and five mapping classifiers (i.e., Random Forest (RF), Support vector Machine (SVM), Adaptive Boosting (AdaBoost), Gradient Boosting (GB), and eXtreme Gradient Boosting (XGBoost) in mapping fruit trees and co-existing land use types. The original dataset was under-sampled randomly into two balanced datasets (i.e., Dataset 1 and Dataset 2) consisting of 100 and 150 sample points. Furthermore, the imbalanced ratio from the original dataset was reduced by applying different sampling strategies to extract four imbalanced datasets (i.e., at 40%, 50%, 60%, and 70%), which resulted in the formation of Dataset 3, Dataset 4, and Dataset 5, respectively. These samples, together with the original dataset (i.e., Dataset 7), were used as input to Sentinel‑2 (S2) data using adaptive boosting (AdaBoost), gradient boosting (GB), random forest (RF), support vector machine (SVM), and eXtreme gradient boost (XGBoost) machine learning algorithms. The results showed that reducing the amount of imbalanced ratio by randomly under-sampling the original imbalanced dataset could increase the classification accuracy to 71% using the SVM classifier and 60% of the original dataset. Individually, the majority of the crop types were classified with an F1 score of between 60% and 100%. Secondly, the research independently assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for fruit tree mapping using random forest (RF) and support vector machine (SVM) classifiers. Four models were tested using each sensor independently and fusing both sensors. From the fused model, features were ranked using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. The best fruit tree map with an overall accuracy (OA) of 0.91.6% with a kappa coefficient of 0.91% was produced using the RF MDA and FVS model and SVM classifier. The application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; A = 87.01%, Kappa coefficient = 87%, respectively. The green (B3), SWIR_2 (B10), and vertical horizontal (VH) polarization bands were identified as the optimal spectral features for S2 and S1 data, respectively. The third part of the research identified the optimal growth window period in which fruit trees can be detected with high accuracy. Phenological metrics were extracted from 12 months (i.e., January to December) of Sentinel-2 (S2) data and were used to classify fruit trees using a random forest (RF) classifier in a Google Earth Engine environment. The results showed that fruit trees can be detected and mapped with high accuracy during winter months (i.e., April-July) with an overall accuracy (OA) of 84.89% and a kappa coefficient of 83%. The user accuracy ranged from 62 to 100%, while the producer accuracy ranged from 60 to 100%. The fruit trees were mostly differentiated from co-existing land use types using the short infrared and the red-edge bands. The fourth part of the thesis attempted to increase fruit tree classification accuracy by classifying optimal Sentinel-2 images acquired during the fruit trees' critical growth stages using a Deep Neural Network (DNN) model. This was achieved by applying phenological metrics derived from Sentinel-2 images acquired during optimal crop-growing seasons (i.e., flowering, fruiting, harvesting). The DNN models were optimized by tuning the hyperparameters to achieve the best classification results. The DNN produced an OA of 86.96%, 88.64%, 86.76%, and 87.25% for April, May, June, and July images, respectively. The results indicate the DNN models were robust and stable across the selected fruit growth periods. This research has shown that earth observation (EO) data such as Sentinel 1 and 2 can be used to map fruit trees in fragmented sub-tropical horticultural landscapes characterized by different environmental conditions and different crop cultivars operating under different management practices. The research results will assist agricultural stakeholders (i.e., farm managers, agronomists, agricultural extension officers, and policymakers) in allocating agricultural resources, devising effective agricultural management strategies, and attaining sustainable agriculture and food security.Item Assessing the inter-annual and inter-seasonal climate-induced variation in caseload of respiratory diseases(University of the Witwatersrand, Johannesburg, 2024-06) Motlogeloa, OgoneIn 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.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, ChrisDue 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.Item Social vulnerability in the adaptation of rural communities to climate change in Imo State, Nigeria(University of the Witwatersrand, Johannesburg, 2024) Okoro, Franklin Chimaobi; Knight, JasperRural communities in developing countries such as Nigeria are faced with frequent extreme weather/climate events that impact their economy, health, and environment due to the combination of high social vulnerabilities, low social resilience, and low adaptive capacities. The aim of this study is to investigate the root causes of social vulnerability in rural communities in Nigeria and how rural households use their social capital and networks to adapt to the impacts of climate change. The study used ten (10) social vulnerability indicators (factors) to ascertain their influence on social resilience and adaptive capacity during climate related disasters. To achieve this purpose, three communities in Imo State, Southern Nigeria were selected, and distributed 240 structured questionnaires to rural household heads, interviewed 18 local stakeholders and climate change actors (government agencies), and conducted three (3) Focus Group Discussions (FGDs) with group of farmers from the three selected communities. The questionnaire survey, interview, and FGD guides contained open-ended questions that allowed participants to report freely. The quantitative data derived from the questionnaire survey were subjected to descriptive analysis using SPSS while the qualitative data were subjected to thematic analysis to derive relevant themes for discussions. The result of the study shows that social vulnerability is a function of age, gender, education, household size, income, sources of livelihood, disability, means of transport, access to healthcare, and alternative accommodation being available during climate emergencies. The study further shows that social vulnerability of rural residents was exacerbated by societal vulnerability influenced by political, economic, cultural, and social factors. Although there are other weather/climate extreme events (disasters), however, the most prominent is floods, constituting 48.3% of the weather/climate events experienced in the study area with its impacts requiring more efficient climate adaptation strategies other than the traditional measures like relocation/migration, use of early maturing crop varieties, early planting and harvesting. However, rural households drew support from government, NGOs, and oil companies but the help from family members, friends, neighbours, social group members (social networks) were more beneficial and helped more rural residents to improve their social resilience. The study recommends that rural residents be encouraged to join social groups since their memberships in such groups will help to improve their social resilience, and that government and its agencies should engage multi-stakeholders in their genuine efforts to develop more effective measures for climate change adaptation.Item Assessing livelihood vulnerability and adaptation to climate variability and change among farming households in Plateau State, north-central Nigeria(University of the Witwatersrand, Johannesburg, 2024) Hassan, Buhari; Knight, JasperIt has been projected that sub-Saharan Africa would be severely affected by climate change in form of persistent and increasing climate variability. Nigeria’s situation as a developing country coupled with the fact that agricultural activities are primarily rainfed, provides a suitable case study in which to assess the vulnerability of farming households to climate variability and change. Lack of data on the nature and extent of vulnerability to climate variability (particularly annual changes in rainfall and temperature patterns) on food production systems and livelihoods in Nigeria hinders the development of effective policies to mitigate the adverse impacts of climate change and variability. The study aims to improve understanding of the socio-economic, institutional, biological and physical factors that contribute to vulnerability of farming households to climate change and variability in Nigeria. By combining descriptive, participatory and statistical analysis as well as field observations, this research develops a holistic approach to assess the level of exposure, sensitivity and adaptive capacity of farming households. Multistage sampling was used to purposely select communities in Bokkos Local Government Area, Plateau State, for the study, while farming households were randomly selected for the household questionnaire survey within four communities. Purposive sampling was used to identify key informants for interviews. Observation and taking photographs of farmers’ activities were used to complement the other data collection methods. Qualitative data was analysed using descriptive and content analysis, while the quantitative data was analysed using the Statistical Package for Social Sciences (SPSS) (v 27) and Microsoft Excel (v2020). The level of vulnerability of farming households was determined using the Sustainable Livelihood Approach. Results show that farmers are exposed to climate variability in form of changing rainfall patterns which includes late onset of rains, dry spells, and early cessation of rains and crop loss due to pests and disease infestation. Results show that the vulnerability of farming households can be linked to access to household livelihood capital assets and that households are characterised by low levels of financial, social and physical capital. Smallholder farming households adopt a range of on-farm and off-farm adaptation strategies including changing planting time, crop diversification, engaging in irrigation farming, intensifying the use of fertilizers, manure and agro-chemicals to boost crop yield, and planting of disease-resistant and drought-tolerant crop varieties. Farming households experience a number of challenges which include a lack of financial resources which has a strong influence on enhancing other capital assets such as physical and natural capitals; poor access to mechanised agricultural equipment, lack of training on how to deal with climate change and variability, limited access to improved crop varieties as well as a lack of institutional support, which constitute serious barriers to adaptation to climate variability. In applying these results to climate change adaptation it is recommended that policymakers need to institute specific and implementable climate change adaptation policies that will enable farmers to utilize their capital assets on effective adaptation measures and also engage in viable alternative livelihood diversification strategies, enhance agricultural productivity and resilience and improve institutional support including access to information and trainingItem From Coal to Renewable Energy: Perspectives on South Africa's Energy Transition for a Sustainable Future.(University of the Witwatersrand, Johannesburg, 2024) Sebele, Temperance; Simatele, Mulala DannySouth Africa has been experiencing an unstable electricity supply for years, leading to periods of load shedding from 2007 up to the present date. The electricity shortages have been attributed to distinct reasons, ranging from inefficient coal supply, skills shortages, sabotage by employees and lack of maintenance for nearly sixteen years. In addition to the electricity supply shortages, coal-fired electricity generation is responsible for roughly 80 per cent of South Africa’s total greenhouse gas emissions due to fossil fuel dependence, leading to many health, climate, and environmental challenges. To address the challenges related to fossil fuel dependency, moving to Renewable Energy sources that are climate and environmentally friendly is a necessity. The aim of this study was to investigate the optimal approaches that South Africa can embark on for a successful transition from coal to renewables. The institutional, policy, and strategic frameworks that exist within which South Africa can embark on for a successful transition were explored. Furthermore, the study sought to identify the challenges, and opportunities that exist or hinder the transition in South Africa. Lastly, the study explored how developments in the international policy frameworks influence South Africa’s ambitions to transition to renewables. The study is best suited to the pragmatism approach, and data were collected through the reviewing of literature, key-informant interviews, and questionnaires. A mixed-methods strategy that involved gathering both qualitative and quantitative data was employed and primary and secondary sources of data were used. The primary data sources used included key informants from various private and public institutions with an interest in South Africa’s energy matters such as ESKOM, SANEDI, SANEA, SAREC, SAPVIA, SAWEA, SAIPPA and NECSA. The non-probability sampling method was used in the participants’ selection from the sampled study institutions, with a combination of judgmental, snowballing and convenience sampling procedures employed at distinct phases of the research. Data collected was analysed both quantitatively and qualitatively, with interviews text data transcribed and analysed through manual tabulation and thematic analysis, and presented in graphs generated from Microsoft Excel, and the data from questionnaires analysed through the IBM Statistical Package for the Social Sciences (SPSS) software. The study revealed that the government played mainly four leading roles in the energy transition, which were providing financial support, legislative direction, institutional direction, and project oversight. Financial support is provided through financing projects and setting up financing policies that promote renewable energy investment, and legislative direction is provided through policy development and ensuring efficient implementation. Providing institutional direction is ensured through ensuring coordination across all spheres of government and capacitating institutions involved in the transition, and project oversight is provided through setting out renewable energy capacity determinations. The study further identified key energy transition elements, namely infrastructure, governance, legislation, stakeholders’ perceptions, and skills and strategies for a successful transition, which included channelling adequate financial resources to the renewable energy sector, privatisation of the electricity utility, diversification, rolling out bid windows, improving the legislative framework, improving grid access and integration, skills development, localisation of RE components manufacturing, providing incentives, and increasing consumer awareness about renewables. Several barriers to the transition were also identified, which included political interference and corruption, lack of financial investment, policies/legislation inadequacy, inconsistency in rolling out bidding windows, ESKOM’s monopoly, high cost of renewables, deficiency of incentives, skills and technology, labour unions, and deficiency of awareness on alternatives. The study recommends multisector reskilling of employees, since not all employees in the coal value chain may be interested in or able to be absorbed in the Renewable Energy sector. Furthermore, the government should fund and support progressive technologies and business models, improve the quality of institutions through merit-based appointments and uprooting corruption, privatisation of ESKOM to create opportunities for new entrants in the electricity market and improve stakeholder engagement and community support programmes. The UNFCCC must develop and ensure the implementation of enforcement strategies for holding countries accountable for their climate commitments for the transition to be realisedItem Mapping and assessment of informal settlements using object-based image analysis, a case study of Mamelodi, Tshwane, South Africa(University of the Witwatersrand, Johannesburg, 2024) Mudau, Naledzani; Mhangara, PaidaThe social and environmental challenges faced by people living in informal settlements or slums are widely recognized by development agendas including United Nations Sustainable Development Goals, Agenda 2063 and National Development Plans. The study aims to investigate informal settlement dynamics and spatial characteristics to generate an understanding of housing informality and environmental conditions for designing innovative sustainable solutions. The study assessed the use of 12 spectral indices and textural measures, and object-based image analysis (OBIA) technique to detect informal settlements from WorldView 2 images. A growth indicator that uses informal settlement extent and impervious surface was developed and used to assess informal settlement growth patterns between 2005 to 2020. Unmanned aerial vehicle image products, and landscape metrics were used to assess the spatial characteristics and patterns of backyard shacks and free-standing informal settlement structures. In addition, a settlement surface ecological index was developed and used to assess the ecological conditions of informal settlements. Lastly, the assessment of the location characteristics of informal settlements was done using ancillary data. The results show that the use of built-up index, coastal blue index and first order statistics mean textural measures and OBIA technique detected informal settlements with producer and user accuracies of 95% and 82% respectively. The developed informal settlement growth assessment indicator shows that informal settlement in 2020 had a slightly lower density of impervious surfaces than in 2005. The Euclidean Nearest-Neighbour Distance, Aggregation Index and Cohesion Index show that backyard shacks are less connected, less dense, and more isolated than freestanding informal settlement structures. Some informal settlements have better surface ecological conditions than some of the formal settlements. A higher extent of informal settlements continued to develop closer to formal settlements, rivers and railway lines between 2015 and 2020. The information demonstrated in this study can be used by local authorities to better understand and manage informal settlement developments, prioritize settlement upgrade projects and improve the environmental conditions and resilience of informal settlementsItem Perspectives on the role of stakeholder engagement and participation in river basin management in South Africa: a study of the hennops river(University of the Witwatersrand, Johannesburg, 2024) James, Lucien; Simatele, Mulala DannyAs a country that already faces hydrological and climatological challenges, South Africa’s socio-economic situation further complicates River Basin Management. This is observable through the state of rivers in the Gauteng Province such as the Hennops River. Like other rivers across the country, the state of the Hennops River is alarming, being affected by multiple sources of pollution. The state of the Hennops River Basin is observably affected by Tembisa, a poor former township area that has contributed to the pollution of the upstream Kaalspruit tributary. While the community of Tembisa contributes to the Hennops’ degradation, the potential of stakeholder engagement and community participation in Integrated River Basin Management is yet to be harnessed. The aim of this study was to investigate in what ways stakeholder and community engagement, mobilisation, as well as participation can be harnessed to promote sustainable River Basin Management considering the Hennops River Basin as a case study. The objectives of this study were to (1) analyse existing policies and frameworks which promote stakeholder engagement and community participation in River Basin Management in South Africa, (2) identify challenges and opportunities that hamper and facilitate sustainable River Basin Management through stakeholder engagement and community participation in South Africa, taking the Hennops River Basin as a case study, (3) create a sustainable model through which stakeholder engagement and community participation can be harnessed towards effective River Basin Management, and (4) Contribute to the body of knowledge on the role of stakeholder engagement and community participation in River Basin Management. Through a research design involving key stakeholders and the community, new insight was gathered about their potential through engagement and participation. Data were gathered from Key Informants, interviews, focus group discussions, as well as clean-up campaigns, which included a campaign hosted by the researcher. Findings of this study suggest that although policy supports the engagement, participation, as well as the mobilisation of stakeholders and the community, implementation thereof has been challenged. At community level, implementation is further challenged through community disinterest, a lack of support or funding for disparate initiatives, and lack of political will to address community issues. Key stakeholders, namely NGOs have taken it upon themselves to address River Basin Management. However, their initiatives are self-reliant and therefore unsustainable. Several conceptual models to address River Basin Management in South Africa are proposed. These models address (1) the implementation of policy through the establishment of effective institutions, (2) the role of the NGO in River Basin Management, (3) the funding of small projects or initiatives, (4) an approach to wicked problems in the community, and (5) the relationship between government, stakeholders, and the community. Together, these models are argued as some of the ways the potential role of stakeholder engagement and community participation can be harnessed as part of a framework for sustainable River Basin Management in South Africa. Opportunities exist to better understand stakeholder engagement and community participation, particularly in the context of leadership and agency. The framework presented as the result of this study opens the doorway to new possibilities for the implementation of policy and new approaches to water governance