Electronic Theses and Dissertations (PhDs)

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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 Simatele
The 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.
A GIS framework for the integrated conceptualisation, analysis and visualisation of Gauteng's complex historic and contemporary post-mining urban landscape
(University of the Witwatersrand, Johannesburg, 2023) Khanyile, Samkelisiwe; Esterhuysen, Amanda; Kelso, Clare
This research study applies assemblage theory as a philosophical lens. It proposes a framework for integrating contemporary and historical landscape characteristics of post-mining and urban landscapes for an integrated conceptualisation, mapping, and analysis of Gauteng, South Africa. The study utilises a mixed methods approach, incorporating spatial and non-spatial (literature and survey) data of varying formats to identify landscape characteristics. Additionally, it applies three multicriteria decision analysis (MCDA) and GIS mapping techniques, employing a simplified rationale to keep its complexity low. Descriptive and inferential statistics were used to analyse the quantitative data, while the qualitative data was analysed using a thematic analysis. The literature and survey analysis findings were used to inform the development of a framework demonstrating the integration of Gauteng's post-mining and urban landscape characteristics using a fuzzy overlay, weighted overlay and random forest classification, along with an accuracy assessment of the mapped results. Based on the proposed framework, the mapped results' performance was evaluated through four methods: confusion error matrix, cross-evaluation, areal coverage comparison, and an image differencing assessment. The literature and survey analysis findings, used to inform the framework, reveal that the two landscapes consist of an assemblage of characteristics and highlight differences in the characterisation of post- mining and urban landscapes. Distinctions were also apparent between literature-derived characteristics and those identified from local experts. The local expert-derived characteristics demonstrate context- specific characteristics of Gauteng's post-mining and urban landscape. At the same time, those based on the literature emphasise a more distinct and separate portrayal of post-mining and urban landscape characteristics (pages 115-116). The characteristics identified from local experts were less conservative (pages 117-118). They included urban-related characteristics in the description of post-mining landscapes and mining-related characteristics in the description of urban landscapes, presenting some similarities in the characterisation of these two landscapes in Gauteng. Moreover, the findings from local experts also revealed that literature and other written or mapped work informed most definitions of post-mining and urban landscapes. The framework for integrating landscape characteristics (pages 121-123) was spatially represented through the three mapping methods, visually demonstrating several findings providing insight into the Gauteng landscape's uniqueness. First, it demonstrates that the differences in the characterisation of these landscapes also impact how they are spatially represented. The maps of post-mining and urban landscape characteristics based on the literature presented a similar pattern to the traditional mapping of mining and urban landscapes in Gauteng. These mapping techniques show the highest values across the mining belt and at the province's core. These findings highlight the influence of literature on the representation of these two landscapes, which is consistent with local experts' reports. In all three mapping methods, the maps generated from local expert characterisations of post-mining and urban landscapes presented a larger spatial footprint than those based on literature-derived characteristics. This distinction was attributed to incorporating additional post-mining and urban landscape characteristics in the maps based on expert input and applying the three mapping techniques - using representation methods not commonly used in mapping these landscapes. Second, the integrated maps of post-mining and urban landscape characteristics suggested a variance in the presence of post-mining and urban landscape characteristics across the province in the maps generated using fuzzy and weighted overlay techniques. This indicates that some parts of the province have a higher or lower presence of post-mining or urban characteristics (pages 125-132). These findings were visible in the maps generated from literature and local experts, indicating the diversity of both landscapes and the co-existence of post-mining and urban landscape characteristics in the local expert maps. This implies an intricate relationship between these landscapes, challenging the idea of them being strictly separate, as indicated in maps presenting characteristics identified from the literature. Furthermore, a closer inspection of the areas showing the intersection between post-mining and urban landscape characteristics also points towards the porosity of boundaries of these two landscapes and alevel of spatial overlap, organisation and arrangement, which are prevalent at varying levels (pages 164- 168). Third, the maps generated using literature-derived characteristics achieved higher accuracy scores, attributed to using reference data traditionally used to map the two landscapes under investigation. This reference data only comprised classes that characterised the physical mining and urban classes, consistent with those identified in the literature. Consequently, it lacked additional factors characterising the post-mining and urban landscape identified from local experts. The fuzzy overlay maps informed by literature demonstrated an accuracy exceeding 70% for post-mining and urban landscape characteristics. In comparison, those reported by local experts scored 64. The weighted overlay and random forest classification resulted in accuracy rates exceeding 50% for post-mining landscape characteristics maps, regardless of whether literature or expert-derived characteristics were used. Additionally, urban landscape characteristics maps achieved an accuracy of over 76%, regardless of the characteristics used to inform the mapping. These findings were attributed to the different mapping techniques employed, with fuzzy and weighted overlay using a gradual range scale, while random forest classification employed a binary scale. This highlights how different mapping methods affect the representation of space. Additionally, it demonstrates the versatility of these mapping techniques in mapping complex spaces such as post-mining and urban landscapes. In this study, the fuzzy overlay accuracies exceeded 60% for all maps and emerged as the most suitable choice for integrating landscape characteristics due to its ability to represent blurred and porous boundaries between Gauteng's post- mining and urban landscapes. In conclusion, the study challenges the notion of post-mining and urban landscapes as distinct landscapes, emphasising the importance of considering the varying levels of spatial intersection between these two landscapes. With the proposed framework and the alternative representation of these landscapes, including contextual information, this research provides insights into new conceptualisations of urban, post-mining landscapes and mineralised urbanisations as assemblages of different landscapes and characteristics with porous boundaries. This enables a better understanding of Gauteng's post-mining and urban landscapes, which could benefit the representation, communication and management of these landscapes. Recognising the potential applications and limitations of frameworks such as the one developed for this study, the high-level recommendation arising from this study suggests a need for ongoing research into the contextual representation of landscapes and their characteristics. This can be achieved by incorporating input from communities, conducting research on quantifying intangible landscape characteristics and developing tools that facilitate the automation and alignment of such data with development plans.
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, Jasper
It 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 training
Assessing the Impacts of Urbanisation on Land Use Change in Zambia: A Study of Lusaka Urban District
(University of the Witwatersrand, Johannesburg, 2024-10) Simooya, Steriah Monica; Kubanza, Nzalalemba Serge; Simatele, Mulala Danny
Urbanisation is a multifaceted, transformative process and a significant global trend that has impacted societies, economies and the biophysical environment. The process of urbanisation results in various challenges as it comes with profound positive and negative effects especially for developing countries. Most countries face insurmountable urbanisation challenges as their governance processes, systems and institutions are ideally not designed to deal and cope with urbanisation processes. Lusaka urban district has been urbanising at a fast pace and, just like many developing cities in Sub-Saharan Africa, has faced various challenges. Urbanisation in Lusaka has led to shifts in urban land use, consequently posing both challenges and opportunities to urban residents. Hence, this study was an assessment of the impacts of urbanisation on land use change in Zambia, a study that was conducted in Lusaka urban district. The aim of the study was to assess the impacts of urbanisation and land use change on the urban poor and vulnerable people in Lusaka whose livelihoods have been historically dependent on land. The study further sought to establish how the urban poor and vulnerable people negotiate their rights to the city in socially and economically productive ways considering the government’s policy on the economic growth and development of the city. This study was guided by pragmatism, which is concerned with what works in solving the problem and, the solution to the problem. Pragmatism posits that the nature of knowledge is not static while knowledge generation is achieved using various methods. Mixed methods research approach was used to assess the impacts of urbanisation and land use change on urban residents in Lusaka district. Both qualitative and quantitative methods were used to collect, analyse, and interpret the study findings simultaneously. Remote sensing (from 1990-2020 for selected areas of Lusaka urban), document analysis, questionnaires, and semi-structured interviews were used as data collection tools. Probability sampling was used to come up with households while non-probability sampling was used for key respondents. A total of 922 households were drawn from the selected residential areas and 12 key respondents from ministries and agencies, Non-Governmental and Civil Society Organisations. Qualitative data were analysed using themes and regular patterns derived from the study’s naturally occurring and emerging themes to derive meaning and interpretation expressed using words and not numbers. To generate frequencies and percentages, quantitative data were analysed using excel and the Statistical Package for Social Sciences (SPSS). Remote sensed imagery was analysed using ArcGIS 10.5. Documents such as maps, and policy documents were analysed for interpretation and meaning as they provided information on land use trends, management, and the regulations guiding the use and management of land in Zambia. Theoretically, the study employed the Hoyt Sector model of urban growth and expansion to explain the outward expansion of Lusaka district along the major transportation arteries of the city. The Hoyt sector model explains land use patterns from independence (1964) up to recent times. Lusaka’s initial development was along the major transportation artery, the British South African railway line and later, the major roads of the city. The Hoyt model also helps in explaining the location of residential areas and why industries are found in defined areas plus the role of the city’s major transportation arteries. The critical urban theory was used to explain the rapid urbanisation of Lusaka city, the emerging shifts in urban land use, and the resultant impacts on urban citizens and their livelihoods. This theory does not conform to mainstream urbanisation theory that explains urbanisation in relation to urban population growth. It emphasises that urbanisation is multifaceted and dynamic, a continuous construction of urban knowledge made up of political, cultural, historical, environmental and economic organisation of any given city. Most importantly, this theory advocates for understanding and explaining of urbanisation in socially inclusive, sustainable and democratic ways. The study findings revealed that Lusaka’s urbanisation has been characterised by the expansion of the built-up area at the expense of other land use and land cover classes. This has resulted in the mushrooming and expansion of informal settlements, diminishing agricultural land, the conversion of grass, crop, and bare land into mixed urban land uses particularly settlements and commercial use. The changes in urban land use are driven by urban population growth, economic growth and development policies and processes, rural-urban migration and the consumerism behaviour characterising most urban residents. The findings further indicate that urbanisation has brought about opportunities and challenges for urban residents. Urbanisation has come with various economic opportunities such as the creation and improved access to various goods and services, employment opportunities, the global exchange and fusion of ideas, cultures, food, and entertainment. Negatively, urbanisation has exacerbated corruption, social injustice and inequality consequently affecting the urban poor who have historically depended on land for agriculture and livelihoods. It has also created the urban divide in urban areas where Lusaka is now composed of the haves and have not, the poor and affluent, informal and overcrowded settlements, and gated communities. Various forms of pollution are now rampant, there’s widespread environmental degradation resulting in environmental ills such as deforestation, climate change, and shortage of resources. These have presented insurmountable challenges for the achievement of sustainable urban development. Furthermore, the diminishing agricultural land is a huge challenge impacting urban food security and urban livelihoods. This is further making it difficult to achieve Sustainable Development Goals particularly SDG no.11 on sustainable and inclusive cities and Africa’s Agenda 2063. The study concludes that significant changes in land use have occurred to urban land in the Lusaka district attributed mainly to urbanisation processes and urban population increase. The changes have mainly been from bare, crop, and grassland to built-up for settlements and commercial purposes, and various ecosystem goods and services have been lost in the process. This has greatly affected the urban poor and vulnerable whose livelihoods depended on agriculture and as such, are struggling to cope with the developments. The study concludes that human settlements are a key driver of urban land use change in Lusaka district. The study recommends that policy formulation, implementation, monitoring, and evaluation be prioritised to sustainably develop the district and manage its land use. The study also recommends the need to involve all stakeholders in the entire process so that policies reflect their various needs. All these challenges pose as infringements to urban livelihoods that are particularly felt by the urban poor and vulnerable people living in Lusaka urban district. The study contributes to the body of knowledge by providing insights into the impacts of urbanisation, land use change and management, urban population growth, urban food security, and urban livelihoods. These are all prerequisites to the achievement of SDGs particularly no.11 on sustainable cities and Africa’s Agenda 2063, the blueprint for the continent’s sustainable development. The study will provide insights that will help policy and decision makers and all concerned stakeholders in the re-planning of land use change in Lusaka district to allocate resources to where they are most needed. The study will help policy and decision makers to come up with environmentally sustainable land use and management policies that do not degrade the environment, expose and leave urban livelihoods vulnerable particularly the urban poor and vulnerable groups not just in Lusaka but in other Sub-Saharan African cities with similar but complex urban spatial landscapes.
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.
Capability of multi-remote sensing satellite data in detecting and monitoring cyanobacteria and algal blooms in the Vaal dam, South Africa
(University of the Witwatersrand, Johannesburg, 2024-03) Obaid, Altayeb Adam Alsafi; Adam, Elhadi M.I.; Ali, Khalid A.
Vaal Dam is a large dam in South Africa. It is the primary source of potable water for the metropolitan and industrial areas of Gauteng province and other surrounding areas. The dam's surface area is about 320 km². It’s the second biggest dam in South Africa in terms of surface area, and it drains a catchment area of approximately 38,000 km². The dam's total capacity is about 2.603 × 10⁶ m³ (Haarhoff and Tempelhoff, 2007). The dam catchment area holds various anthropogenic activities, including major agricultural activities, mining, and some industrial activities (Obaid et al., 2023, Du Plessis, 2017), as well as many formal and informal settlements. The dam water is strongly affected by such activities, releasing chemical, physical, and biological contaminants and dissolved urban effluents, most of which enrich the nutrients that reach the dam water in some way. Water resources assessment and monitoring are crucial practices due to their direct contribution to the effective use of such resources. They require precise information about the water quantity and quality. Monitoring of inland water resources has been conducted using in-situ sampling and in-vitro measurement of the water quality constituents. However, these methods have limitations such as high cost, labor-intensive limited spatial and temporal coverage, and time consumption. Over the last few years, remote sensing has been examined for water quality monitoring as a cost- effective system. This research has tested satellite remote sensing to detect some water quality parameters in the Vaal Dam of South Africa. The main objective of this research is to examine the recent generation multispectral satellite sensors, Sentinel-2 MSI, and Landsat-8 OLI data to detect and assess chlorophyll-a and cyanobacteria in the Vaal Dam, South Africa to be used as a cost-effective monitoring tool. To achieve the objective, the research first aimed to understand how the spatial and temporal dynamics of land use, and land cover (LULC) impact algal growth in the dam reservoir. Land use land cover classification was conducted in the catchment area of the Vaal Dam using a pixel-based classification method. Landsat data for the period from 1986 to 2021 were classified using a random forest (RF) classifier in seven-year intervals (1986, 1993, 2000, 2007, 2014, and 2021). Applying the RF classifier revealed that overall classification accuracies (OA) ranged from 87% in the 2014 classified image to 95% in the 2007 image. The change-detection analysis revealed the continuous increase of the settlement class owing to the continuous population growth. A lot of anthropogenic activities associated with population growth have been recognized to release contaminants into the surrounding environment and might end up reaching the water resources causing significant deterioration. As a result, Vaal Dam encounters significant nutrient input from multiple sources within its catchment. This situation raised the frequency of the Harmful Algal Blooms (HABs) within the dam reservoir during recent years. The study also performed a time series analysis for the potential nutrients expected to be the enhancing factors for algal blooms in the Vaal Dam. Using chlorophyll−a (Chl−a) as a proxy of HABs, along with the concentrations of potential nutrients, statistical measures, and water quality data were applied to understand the trend of selected water quality parameters. These parameters were: Chl−a, total phosphorus (TP), nitrate and nitrite nitrogen NO₃NO₂_N), organic nitrogen (KJEL_N), ammonia nitrogen (NH₄_N), dissolved oxygen (DO) and the water temperature. The results reveal that the HAB productivity in the Vaal Dam is influenced by the levels of TP and KJEL_N, which exhibited a significant correlation with Chl−a concentrations. From the Long- term analysis of Chl−a and its driving factors, some very high values of Chl−a concentrations and its driving factors TP and KJEL_N were recorded in erratic individual dates which suggested some nutrients rich in wastes find their way to the dam. Another important notice was that the average Chl-a concentration significantly increased during the period of the study (1986 to 2023) it increased from 4.75 μg/L in the first decade (1990–2000) to 10.51 μg/L in the second decade (2000–2010) and reaching 16.7 μg/L in the last decade (2010–2020). Additionally, Chl−a data extracted from Landsat-8 satellite images was utilized to visualize the spatial distribution of HABs in the reservoir. The satellite data analysis during the last decade revealed that the spatial dynamics of HABs are influenced by the dam’s geometry and the levels of discharge from its two feeding rivers, with higher concentrations observed in meandering areas of the reservoir, and within zones of restricted water circulation. These spatial distribution patterns of HABs are associated with spatial variations of algal species in term of domination through the seasons of the year. The research also examined the utility of remote sensing techniques for mapping algal blooms using the current generation Sentinel-2 and Landsat-8 data. The effectiveness of some band ratio indices in the blue-green and red-near infrared wavelengths was tested. The results suggested that the blue-green band ratio of Landsat-8 [Rrs(560)/Rrs(443)], and red/NIR of Sentinel-2 [Rrs(705)/Rrs(665)] were found to be the best indices for Chl-a retrieval in the Vaal Dam. Results for the Landsat OLI dataset showed R² = 0.89; RMSE = 0.36 μg/L, P < 0.05, and the Sentinel MSI dataset revealed R² = 0.75; RMSE = 0.48 μg/L, P < 0.05 which is a high degree of accuracy. As the potential toxicity comes from the cyanobacterial bloom, the study examines different models to assess and map cyanobacteria concentration in the dam reservoir. Sentinel-2 and in-situ hyperspectral data have been used. None of the Sentinel-2 band ratios showed a significant correlation with the laboratory-measured values of the cyanobacteria. The in-situ measured Hyperspectra showed strong correlations between the band ratios Rrs(705)/Rrs(655) and Rrs(705)/Rrs(620), and the measured cyanobacteria (R² = 0.96 and R² = 0.95 respectively). Chlorophyll−a concentration was retrieved using band ratio indices in the red-NIR region. The strongest correlation was found between the retrieved Chl−a of band ratio Rrs(705)/Rrs(665) and the laboratory-measured Chl−a concentrations for both reflectance datasets. This correlation resulted in an R² value of 0.78 for Sentinel-2 reflectance data and an R² value of 0.93 for in-situ hyperspectral data. A Semi-analytical algorithm for estimating the Chl−a and phycocyanin (PC) pigments has also been examined. The algorithm uses the ratio of the calculated Chl−a absorption at 665 and phycocyanin absorption at 620 nm to their specific absorption coefficients a∗ (655) and a∗ (620) to estimate the concentration of Chl−a and phycocyanin respectively. It resulted in a strong correlation with measured chlorophyll-a, R² = 0.95. The algorithm also strongly correlated with measured cyanobacteria using the absorption to specific absorption ratio at 620 nm (R² = 0.97). However, the estimated values of cyanobacteria using a Semi-analytical algorithm resulted in cyanobacterial concentration values a little bit higher compared to the measured ones, hence, some factors used by the model need to be adjusted to the Vaal Dam site for better estimations. This research revealed that using band ratio indices of Landsat-8 and Sentinel-2 data are valuable tools for mapping chlorophyll-a in the Vaal Dam, a key indicator of phytoplankton biomass. Furthermore, using the semi-analytical algorithm with hyperspectral data is key for estimating the cyanobacteria concentration in the dam water. Models developed in this research will significantly improve near-real-time and long-term chlorophyll-a monitoring of the Vaal Dam. It will effectively help researchers and environmental agencies monitor changes in algal biomass of the dam water to address public health issues related to water quality. It helps to identify areas of high nutrient input and assess the effectiveness of water quality management strategies. It is of prime importance that the developments within the catchment of the Vaal Dam be carefully considered as it is one of the primary sources of dam water. The research recommends implementing the existing regulatory policies for effluent dispersal within the catchment to protect ecosystem functioning and water resources from further deterioration in their quality. It also recommends regular monitoring to detect real-time changes in HABs using satellite remote sensing.
Cartographic History, the Post-Colonial Landscape and the Agricultural Settlement Scheme: A Case Study of Citizen-Based Mapping in Northeastern Ibadan Rural Hinterland
(University of the Witwatersrand, Johannesburg, 2023-10) Ogundiwin, Babatunde Adedayo; Wafer, Alex
Maps of economic imagination provide visual insights into alternative agrarian spatial thought. This thesis examines visual contribution to reconstituting agricultural subjectivity. It explores the potential of citizen-based mapping in consolidating alternative visions of the agricultural settlement scheme. Visualisations are integral in the discursive technologies of post-colonial state policies that produce modern agricultural subjectivity. On one hand, these state cartographic strategies involve othering practices of subaltern agriculture. On the other hand, there are resurgent ideas of community-based agricultural schemes verbalised amongst subaltern groups. Hence, there is an ongoing political-economic struggle of visions mediated by visualisation and verbalisation. Drawing upon theoretical literature in spatiality, postcolonialism and governmentality, the thesis explores taken-for-granted knowledge, sites of economic difference and silenced voices/visions on the post-colonial agricultural landscape. Using Northeastern Ibadan rural hinterland of Oyo State, Southwest Nigeria, as a case study, the thesis argues that visualisation offers insight into counter-narratives and alternative reframing of the agricultural settlement scheme. This study employed a multi-method qualitative approach involving the critical historical reading of state maps, ethnographic analyses and mapmaking techniques to visualise and summarise developmental concerns and aspirations. The thesis demonstrates that state imaginative geographies strive in shaping agricultural identities and subjectivities. Recently, these cartographic legacies of state rationalities seek the active consent of the citizenry in the drive toward state-sanctioned neoliberal imaginary. The study contends that the post-colonial state in Nigeria envisions a large-scale agricultural development rather than supporting smallholder subaltern agriculture. Hence, there is intentional and unintentional involvement in visual disinformation and engagement in anti-political economic imaginations of subaltern agriculture. However, the visualisation of verbalised counter-narratives contesting state developmental visions and alternative imaginations of the agricultural settlement scheme unveil anticipatory spatialities desiring a break from economic decline and stagnation in rural hinterlands. This transformation of imaginaries into visual images emphasises new perspectives and new insights renegotiating the political subjectivity of subalterns. This thesis demonstrates that visual geographies of subaltern aspirations offer alternative visions of the agricultural settlement schemes.
Climate Variability and Asset Adaptation of Small-scale Farmers in Zimbabwe's Gokwe South District:A Search for Knowledge Integration Approach
(University of the Witwatersrand, Johannesburg, 2023-05) Chatsiwa, Jaison; Simatele, Mulala Danny
Globally, climate change and variability threaten food production and security for an unforeseeable future leaving millions of people vulnerable to hunger and malnutrition related diseases. Climatic models are projecting that Zimbabwe’s climate will be hanging drastically with a high possibility of experiencing extreme weather patterns impacting the livelihoods of small-scale farmers who rely on rain-fed agriculture for their livelihoods. This study aims to investigate the role of asset portfolios in reducing the climate vulnerability of small-scale farmers of Gokwe South in Zimbabwe. Zimbabwe’s agricultural production both crop and livestock production has been negatively impacted due to the dwindling rainfall and increase in temperature and climate related risks and disasters. The quality and quantity of asset portfolios determine the adaptive strategies and their success against the challenges of climate variability. Despite these effects, small-scale farmers in the Gokwe South district are using their asset portfolios to increase their adaptive capacity and resilience to fight against the challenges of climate variability. Therefore, this thesis revealed a paradigm shift from asset vulnerability to pro-poor asset adaptation. The paradigm shift crafted the ‘Theory of Change’ which is useful for climate variability adaptation strategies in the Gokwe South district as the small-scale farmers change from asset vulnerability to asset adaptation. The Theory of Change encourages contextual analysis of the area and theme under study. A Theory of Change is a method that explains how a given intervention, or set of interventions, is expected to lead to specific development change, drawing on a causal analysis based on available evidence. This study used the Participatory Climate Change Adaptation Appraisal (PCCAA) as the primary data collection tool and the Participatory Rural Appraisal (PRA) known as the emancipatory methodology, to collect data in rural areas. A mixed methodological approach involving qualitative and quantitative was applied. We used thematic content analysis to analyse qualitative data collected during the data collection exercise. During the study period, computer-Aided Qualitative Data Software was used to store data in a sorted manner. The parametric variables were coded using the Predictive Analytic Software. This enabled to performance of statistical analysis and obtaining descriptive statistical outcomes were obtained. The assessment of the effect of the factors on climate adaptation strategies was done through the Likert scale. Indigenous knowledge remained widely used as a source of climate knowledge in the Gokwe South district. The research results showed that indigenous knowledge (IK) is unpredictable, productive assets and adaptive assets are inadequate, technoscience and institutional support are poor support to implement viable adaptation strategies is lacking, and poor distribution and dissemination of climate and weather information to small-scale farmers in the Gokwe South district is poor and asset portfolios and asset mix is poor. The available asset portfolios determine the adaptation strategies used in the Gokwe South district. Results show that climate vulnerability varies spatially and temporally across the Gokwe South district. The studied five constituencies for the Gokwe district have a mean vulnerability index of 3.04 with the highest index being 5 as being well adapted. Sengwa and Mapfungabutsi are highly vulnerable to the vagaries of climate variability in the Gokwe South district. The researchers recommend strong institutional support from the government. The fact that small-scale farmers should integrate their IK and modern science climate knowledge small-scale farmers in the Gokwe South district should adopt proactive or anticipatory adaptation, government climate-smart agricultural policies, and a bottom-up approach to climate variability. The quality and quantity of asset portfolios are key resources affecting the level of vulnerability to climate variability. The asset mix was seen to be significant in reducing the vulnerability of small-scale farmers in Sengwa and Mapfungabutsi, constituencies worst affected due to poor asset endowment of farmers in the Gokwe South district. The results have shown that the financial asset is the most important asset affecting vulnerability because it can be converted into other assets through buying. Weak institutional intervention renders many small-scale farmers helpless to climate variability, and the government is not fully supporting small-scale farmers to increase their adaptive capacity and resilience.
Compost-assisted phytoremediation of mine tailings and footprint areas using chrysopogon zizanioides (l) roberty enhanced with moringa leaf extract biostimulant in the Witwatersrand goldfields of South Africa: a sustainability initiative
(University of the Witwatersrand, Johannesburg, 2024) Mlalazi, Nkanyiso; Chimuka, Luke; Simatele, Mulala Danny
In the Witwatersrand goldfields of South Africa, mine tailings and footprint areas are significant environmental problems because they are major sources of toxic metals. These metals can leach into soils, and both surface and ground water, causing serious risks to human, animal, and plant life. In this study, the compost-assisted phytoremediation of tailing storage facilities (TSFs) and footprint soil using Chrysopogon zizanioides (vetiver grass) enhanced with moringa leaf extract (MLE) was investigated. A greenhouse experiment was conducted to identify the most favorable parameters, and was followed by a field study to test the optimized parameters under real-environment settings. For the greenhouse experiment, a 3×2×2 fully crossed factorial design was used to determine the optimum variables. Vetiver growth was assessed under three compost concentrations (0%, 30% and 60%), two types of MLE (laboratory extracted MLE and commercial MLE) and two application regimens (once a week and twice a week) were used. The biomass and metal concentrations in the vetiver grass roots and leaves were measured after sixteen weeks followed by a two-way ANOVA analysis and the post-hoc tests. All the vetiver that was planted in 0% compost died within four weeks regardless of the MLE treatment. Vetiver grass planted on the 60% compost amendments and sprayed with laboratory extracted MLE had the highest biomass production, followed by plants grown in 30% compost amendments and sprayed with commercial biostimulant. However, the heavy metal removal or uptake data by the plant was inconclusive, as most of the toxic metals were not removed by vetiver grass which was attributed to the effect of compost. Based on biomass data, the 30% compost amendment and commercial bio-stimulant was the ideal treatments for the phytoremediation of gold mine tailings using vetiver grass. Although metal accumulation by plants is one of the attributes considered in phytoremediation, it is not the most significant factor in the phytostabilisation process. Plant growth and biomass production are the most significant, therefore it is concluded that vetiver, MLE and compost can be used in the phytostabilisation of gold mine tailings, however reduction in compost may be considered in future to improve the accumulation of metals in the roots for improved results. Following the conclusion of the greenhouse study, a field study was conducted during the rainy season of 2021. Two field experiments were carried out concurrently at two sites: the footprint area (that was used as a rock dump) and the tailings storage facility (TSF 4). A split-plot design was used in this study. The experiment at each site assumed a 3×1×2 factorial design, with three levels of compost treatment (0%, 15% and 30%), 1 level of vetiver cultivar (Chrysopogon zizanioides), and 2 levels of MLE treatment (commercial MLE and tap water, both sprayed once a week). Three blocks measuring 1 m × 2 m, each with 20 holes filled with equal amounts of soil amended with the different compost levels were prepared in triplicates. A single vetiver grass slip was planted in each hole. The blocks were then divided into 2 sections, each with 10 holes, and commercial MLE was sprayed on one section, while only water was sprayed on the other section once a week. After sixteen weeks, three plants were harvested from each section and the number of leaves, leaf length, number of tillers, biomass for roots and leaves and element concentrations were measured. Data analysis was done using two-way ANOVA
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 Danny
South 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 realised
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, Elhadi
From 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.
Integration of Sustainable Development Principles and Climate Change Adaptation Measures in Energy Optimization in Gold Mining in South Africa
(University of the Witwatersrand, Johannesburg, 2023-08) Nadunga, Irene; Simatele, Mulala Danny
South Africa located in the sub-Saharan African region and being a mining-intense country, is reported to be affected by extreme weather events which are increasing the country’s vulnerability to climate change impacts and therefore reducing the chances of achieving sustainable development. In light of this, mining companies are being pressured to make strong commitments towards implementation of sustainable development principles for sustainable mining. This study therefore aimed at investigating how sustainable development principles and climate change adaptation measures are interlinked and structured; and embedded in a gold mining company’s policies and strategies, in an effort to build the mining operations’ adaptive capacity and resilience against the impacts of climate change and achieve energy optimization. The challenges that can potentially prevent the effective integration of the sustainability principles and adaptation measures were also explored. Using a case study approach, this study was centered on the gold mining operations located within the Witwatersrand Basin of South Africa. Research data was collected from multiple sources, therefore employing a mixed method approach by applying the concurrent triangulation technique. Different analytical tools of policy, content and inductive data analysis, and descriptive statistical data analysis were applied. The empirical evidence shows that the gold mining operations are faced with increasing operating costs associated with the increased energy consumption and implementation of costly mining practices in an effort to combat the impacts of extreme weather events caused by climate change. This affirms that a relationship exists between climate change and energy use in gold mining. In an effort to address climate related risks and energy security, gold mining operations are implementing energy efficiency measures and using renewable energy in their energy mix; which measures are seen to integrate sustainability principles, therefore adopted as sustainability adaptation measures. In addition, some mining company policies and strategies are also seen to integrate sustainability principles and adaptation measures, in an effort to guide the mining operations in effectively developing and implementing sustainability adaptation measures, designed to holistically address climate related risks and energy security. This affirms that a relationship exists between sustainable development principles, climate change adaptation measures and energy optimization. This therefore, implies that sustainability principles and adaptation measures can be integrated to form sustainability adaptation measures, and that gold mining companies have the potential to achieve sustainable mining and contribute to sustainable development, particularly achieving SDG 7 and SDG 13.
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, Paida
The 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 settlements
Mapping and monitoring the impacts of climate variability on rainfed agriculture in Semi-arid North Darfur, Sudan
(University of the Witwatersrand, Johannesburg, 2024-02) Altoom, Mohammed Bashar Adam; Adam, Elhadi
Rainfed agriculture is vital to food security and income in most parts of the world. However, one-third of the population of developing countries population lives in the less favoured rainfed agricultural regions. Around 75-82% of the total cropland areas in the world are under rainfed agriculture and produce more than 60% of the globe’s cereal grains. However, rainfed agriculture is most prominent in some regions of Africa, such as Sub-Saharan Africa, where more than 95% of the cropland is rainfed. This crucial agriculture sector usually depends on the physical environment and, most importantly, the variability and distribution of rainfall. Therefore, rainfed farming is vulnerable to climate-related hazards, and the crop yield is unreliable and difficult to predict. For instance, the spatio-temporal variability of precipitation extreme events often subjects crops to short-term water deficits, causing crop losses. Sudan heavily depends on rainfed agriculture—about 90% of arable land dominates rainfed cultivation, contributing one-third of the country’s gross domestic product (GDP). Rainfed agriculture is the primary source of livelihood for 65% of the population. Unfortunately, agriculture in North Darfur of the west Sudan is characterised by environmental hazards, e.g., frequent droughts and unpredictable low, poorly distributed, and highly variable monthly/seasonal rainfall. Therefore, using various Earth observation data, this study aimed to monitor the impacts of rainfall variability on rainfed agriculture in North Darfur State in Sudan. Firstly, the study aimed to determine the feasibility of estimating rainfall variability across North Darfur State at daily, monthly and annual timescales using six satellite precipitation products (SPPs), i.e., the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), African Rainfall Climatology (ARC), and Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) were evaluated using four categorical indices, i.e., probability of detection (POD), probability of false alarm (POFA), bias in detection (BID) and Heidke skill score (HSS), and four continuous indices, i.e., Pearson correlation coefficient (r), root mean square error (RMSE), per cent bias (Pbias), and Nash-Sutcliffe model efficiency coefficient (NSE) against ground rain-gauge observations. The other SPPs were Integrated Multi-satellitE Retrievals for Global Precipitation Measurements (GPM) Final Run (GPMIMERG), Precipitation Estimation from Remote Sensing Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT). Results of the statistical analysis demonstrated that 1) at the daily timescale, the SPPs underestimate daily rainfall by 6.53–17.61%, and CHIRPS was the best for detecting rainy days, while PERSIANN-CDR performed poorly; 2) monthly and annual scales performed better than daily timescale, and TAMSAT and CHIRPS portrayed better performance than the ther SPPs. Secondly, the study assessed the capability of optical Earth Observation Data (EOD), i.e., Sentinel-2 multispectral dataset, to map crop types in the heterogeneous semi-arid environment of North Darfur using machine learning classifiers in Google Earth Engine (GEE) platform. Five datasets were compared against random forest (RF) and support vector machine (SVM) classification algorithms: (1) 10 Sentinel-2 bands (comprising visible, near-infrared and shortwave infrared bands), (2) Sentinel-2 (10 bands) + 8 vegetation indices, (3) visible bands and near-infrared bands only, (4) visible and shortwave infrared bands only, and (5) 8 vegetation indices. The eight vegetation indices were normalised difference vegetation index (NDVI), enhanced vegetation index (EVI), soil-adjusted vegetation index (SAVI), green normalised difference vegetation index (GNDVI, weighted difference vegetation index (WDVI), red edge NDVI (NDVIre), ratio-vegetation index (RVI) and normalised difference infrared index (NDII). Results showed that the RF algorithm produced the highest classification overall accuracy (OA), i.e., 97% and Kappa coefficient (κ), 0.96, using 10 Sentinel-2 bands dataset. Producer’s (PA) and user’s accuracies (UA) were in the range of 40-97% and 40-100%, respectively. Thirdly, the spatiotemporal trend of drought events and their impact on millet production in North Darfur from 1981 to 2020 was analyzed using standardized precipitation index (SPI) and reconnaissance drought index (RDI) by employing different timescales, i.e., 3- month (June-August), 6-month (June-November), and 9-month (June-February) timescales. Drought-yield relationships were assessed using Pearson correlation coefficients (r). Results indicated that RDI is more sensitive to rainfall variabilities than SPI in detecting drought trends. Results revealed that drought events affected North Darfur over broad spatial extents, particularly in 1989, 1990, 1992, 1999, and 2001—an extreme drought event was in 2003. Correlation analysis between the SPI and RDI and the standardized variable of crop yield (SVCY) for millet grain yield showed a strong agreement between them. Moderate to extreme reductions in millet crop yield occurred in 1992, 1999, 2001, and 2003, corresponding to the moderate to extreme drought indicated by RDI. Severe crop losses were in Kabkabiya and Umm Kadadda. Fourthly, this study aimed to map and monitor spatio-temporal dynamics of rainfed agriculture in North Darfur State from 1984 to 2019 using multitemporal Landsat observation data using random forest (RF) classification algorithm. Overall, Landsat Operational Landsat Imageries (OLI) outperformed Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Mapper Plus (ETM+) in monitoring change in agricultural land and other land use land cover (LULC) classes. Overall accuracies ranged between 94.7% and 96.9%, while kappa statistics were greater than 0.90. Results showed that Goz land used for rainfed agriculture increased by 889,622.46 ha between 1994 and 999, while it decreased by 658,568.61 ha between 2004 and 2009. Rainfed cultivation of wadi lands expanded significantly by 580,515.03 ha over the 2014–2019 period and decreased by 182,701.8 ha over the 1994–1999 period. Overall, this study enhances the understanding of spatio-temporal rainfall patterns and current drought trends, aiding in developing more effective policies and resource management strategies. Additionally, it offers crucial spatial data that is currently scarce due to ongoing conflicts, empowering decision-makers to establish sustainable land use monitoring systems. The methodologies used in this study have proved successful in mapping crop types in a fragmented highly heterogeneous fine agricultural semi-arid landscape; such mapping approaches can be applied in other environments with similar characteristics.
Palynological insights into an 11,700-year sequence of vegetation change in mashishing, Mpumalanga, northeastern South Africa
(University of the Witwatersrand, Johannesburg, 2023) Olatoyan, Jerry O.; Schoeman, Alex; Neumann, Frank; Sievers, Christine; Orijemie, Emuobosa; Evans, Mary
In this thesis, the issue of distinguishing anthropogenic and climatic drivers of vegetation change was explored through the analysis of pollen, phytoliths and microcharcoal in core sediment records from Mashishing Fen in the Thaba Chweu Municipality, Mpumalanga province, northeastern South Africa, that date from ca. 11.2 – 11.7 ka BP to the present. In southern Africa, generally, the distinction between the contributions of anthropogenic and climatic factors to vegetation changes poses a complex challenge in palaeoenvironmental research. This difficulty often arises due to limited, well-dated palaeoenvironmental sequences suitable for correlations between archaeological and palaeoecological records. For the last 2000 years, there has been a scarcity of direct evidence for farming, such as grains and other domesticated plants, and pastoralism. A further difficulty is that some plant taxa may be indicators for intense droughts but also signify anthropogenic disturbances. At the centre of the thesis are three papers. The first comprises a synthesis of existing literature of archaeobotanical evidence that was done to evaluate the relationship between climate, anthropogenic activities, and vegetation change during the first millennium CE in southern Africa. I focussed on this context in the paper because it is a time in which the arrival of pastoralism and farming in the region makes it the most likely period during which distinct anthropogenic vegetation change occurred. The published data demonstrates that microfossil assemblages are potential indicators of anthropogenic activities of pre-European pastoralists and farmers of the region, with patterns including a decline in tree pollen and increases in microcharcoal, spores of coprophilous fungi, open land/disturbance indicators, and ruderal species. The second paper addresses some of the limitations of palynology as a method. A modern pollen- and phytolith-vegetation study was conducted on surface sediment samples linked to the botanical survey of five vegetation survey plots at and around Mashishing Fen to investigate the relationships between the modern pollen and phytoliths in the surface samples and the contemporary vegetation within the area. The results support the accepted view that pollen and phytoliths often do not track similar vegetation signals. The modern pollen assemblages clearly track forest and wetland vegetation, and the modern phytolith assemblages reflect grassland vegetation in the area. The study confirmed that differential phytolith and pollen production, dispersal and preservation substantially influence the proxy records and that combining phytolith and pollen data provides a more accurate basis for plant fossil interpretations in palaeoenvironmental studies. The results of this paper constrained my interpretation of the pollen data used in the third paper. Finally, pollen, spores and microcharcoal data from the core sediment records from Mashishing Fen (formerly the Lydenburg Fen) provide palaeoenvironmental records for approximately the last 11,2 to 11,7 ka years–most of the Holocene. The data is interpreted through the patterns identified in the first paper, including potential indicators of anthropogenic activities. The data of the earlier period provide a backdrop to possible anthropogenic change in the first millennium CE; the extended data illustrate paleoenvironmental changes that took place in a region occupied by hunter-gatherers but predate any possible anthropogenic influences by pastoralists or farmers. The core data suggests that the early Holocene began with moist and warm conditions that were followed by fluctuations between wet and dry conditions during the mid-Holocene and the decline of trees with the dominance of open-land indicators during the later Holocene, thereby providing the basis for correlating the palaeoecological records with the archaeological records in the region
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.
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 Danny
As 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
Reassessing the stratigraphy and formation of the basal deposits at Klasies River Main Site with a multiscale and multiproxy approach
(University of the Witwatersrand, Johannesburg, 2024) Morrissey, Peter; Wurz, Sarah; Mentzer, Susan
The basal deposits at Klasies River Main site, associated with the MSA I and II lithic cultural phases and dating from >120 ka to ~80 ka, have yielded highly significant archaeological assemblages and human fossils across multiple phases of excavation since the late 1960s. These finds have contributed to a growing understanding of the appearance and intensification of modern human behaviours and provide rare insight into Homo sapiens anatomy during the early parts of the Late Pleistocene. The three recesses occupied during this period represent distinct depositional environments with differing degrees of attractiveness for human activities. Significant climatic, environmental, and geomorphic changes, including large fluctuations in sea level, occurred, impacting formation processes within the site complex. Stratigraphic relationships across a space like this would always be complicated but understanding them here is even more difficult because there are not continuous deposits between the recesses for all or part of their respective sequences. Geoarchaeological research has taken place alongside all three phases of excavation at Klasies. Until Sarah Wurz began her field programme in 2013, this work entailed macroscopic descriptions of standing sections (at differing resolutions) and the sedimentological analysis of bulk samples. Given the finely laminated nature of many of the deposits, even higher resolution bulk sampling resulted in the incorporation of multiple visible deposits into individual samples in many cases. More recently, archaeological micromorphology and other microscale analyses have been applied to deposits in the site complex by Susan Mentzer and colleagues. This work has provided important new insights into human behaviour and the spatially and temporally variable impacts of different diagenetic processes. Here, field observations of standing sections and microcontextual analysis are used to provide greater insight into the formation of deposits in two areas of the site complex. This information is used, along with unpublished field notes and profile drawings and critical engagement with the extensive, but seldom detailed, literature to assess and refine stratigraphic correlations of the basal deposits both between different recesses and different stratigraphic systems (the layers used in the initial excavations and the excavation units grouped into members and sub-members in subsequent work). The results demonstrate that the formation of any particular deposit could involve any number of combinations and relative intensities of different depositional and post- depositional processes. Furthermore, the interplay between geogenic, biogenic, and anthropogenic processes is often significant. Anthropogenic deposition has long been recognised as being highly significant at Klasies, but it is now also clear that humans played a major role in reworking sediment through daily activities during occupations, very likely including trampling and site maintenance activities. Chemical diagenesis had a major impact on the preservation of anthropogenic features, but variations in the intensity and frequency of anthropogenic deposition also influenced how susceptible deposits were to diagenesis. It has proven possible to correlate between the two stratigraphic systems in Cave 1B, a particularly understudied area of the site complex, providing clarity on the cultural association of a highly significant human fossil. The overall stratigraphic system used at the site complex is now also better understood, both in terms of correlations and the nature of the system. Finally, this study highlights the utility of a multiscale geoarchaeological approach to site complexes like Klasies for understanding site formation and stratigraphy. It also highlights the vital, but often ignored or underplayed, connection between site formation processes and stratigraphy, especially in such a complicated context.
Remote sensing survey of archaeological sites in the Shashi- Limpopo Region
(2020) Thabeng, Olaotse Lokwalo
The African continent is rich with archaeological heritage, which needs to be preserved for the current and future generations. The majority of archaeological heritage sites in Africa are facing disappearance due to a number of challenges including looting, destruction from developments, expansion of agricultural land and natural hazards. Documentation and monitoring of archaeological heritage sites, therefore, is of paramount importance for effective site management and preservation. However, archaeological heritage sites in the continent are poorly documented and monitored due to a number of factors including lack of funds by heritage management institutions, lack of trained personnel and inaccessibility of some areas due to conflicts or land ownership rights. Traditionally, the documentation and monitoring of archaeological heritage sites in Africa have been done through fieldwork, which is costly, time-consuming and difficult to carry out over large areas. Remote sensing offers a relatively fast, cheap, systematic and reproducible method of surveying and monitoring archaeological sites over large and/or restricted areas. Remote sensing techniques are used to identify earth surface features based on their spectral signature, which is the variation of reflection or emittance of materials’ electromagnetic energy. Spectral signatures for identifying archaeological sites are not universal, and an assessment of the applicability of remote sensing techniques in different archaeological landscapes is needed. The aim of this study, therefore, was to investigate the potential of using remote sensing techniques to document archaeological sites previously occupied by farming communities, which are traditionally associated with the Iron Age period in Southern Africa, using the Shashi-Limpopo case study. The first part of this study gives a review of the use of remote sensing in the African archaeological context. Despite it being a fast, cost-effective and systematic method of survey, the results of this study have demonstrated that remote sensing is not widely used in archaeological applications in Africa. The aforementioned situation calls for studies investigating the potential of using remote sensing techniques to fast track archaeological site survey, documentation and monitoring in the continent. The chemical composition of materials characterising different features have more or less subtle variations that, in turn influence the spectral behaviour of soil. This is an important principle that can be used for distinguishing archaeological soils from non-archaeological soils and can potentially help in discriminating different archaeological signatures. As such, the second part of this study investigated the possibility of using field spectrometer measurements to discriminate middens, non-vitrified dung, vitrified dung and non-sites (natural soils) characterising archaeological landscapes previously occupied by farming communities. It then investigated the presence of differences in the chemical composition of elements between middens, non-sites, vitrified dung and non-vitrified dung. The findings indicated that there is a statistically significant difference in the concentration of soil elements between non-sites, middens, vitrified dung and non-vitrified dung byres. They also indicated that some bands in the visible and shortwave infrared regions of the electromagnetic spectrum important bands for predicting the aforementioned archaeological sites and non-archaeological sites. In the third part of this study, the ability of multispectral sensors to discriminate archaeological and non-archaeological features in Shashi-Limpopo confluence area was investigated using field spectral data resampled to the spectral resolutions of common multispectral satellites namely GeoEye, Landsat 8 OLI, RapidEye, Sentinel-2, SPOT 5 and WorldView-2. This is because the spectral and spatial resolutions of various multispectral sensors determine the size and the type of archaeological data a sensor can detect. As such, another goal of this study was to identify multispectral sensors with the optimum spectral resolutions for detecting middens, non-vitrified dung, vitrified dung and non-sites. Additionally, the performance of advanced classification algorithms (random forest and support vector machines) in discriminating middens, non-vitrified dung, vitrified dung and non-sites was also investigated. The results proved the possibility of using multispectral satellites in mapping middens, non-sites, vitrified dung and non-vitrified dung sites. These results initiated the need to upscale the test to actual satellite images. The fourth part of this study assessed the possibility of prospecting for archaeological sites previously occupied by farming communities in the Shashi-Limpopo Confluence Area, using a very high-resolution satellite WorldView-2 image. The findings have shown that WorldView-2 satellite images and advanced classification algorithms can be used in prospecting for archaeological sites previously occupied by farming communities in Shashi-Limpopo Confluence Area. Finally, the ability of geographic object-based image analysis (GEOBIA) based on random forest and support vector machines, to discriminate archaeological and non-archaeological features on a very high-resolution satellite WorldView-2 image was investigated. The results of this study demonstrated the robust ability of the GEOBIA to integrate spatial attributes into the classification model improves the chances of separating materials with limited spectral contrast. Generally, this study has shown that remote sensing techniques can be used to map archaeological landscapes characterised by middens, non-vitrified dung, vitrified dung and non-sites. This will help archaeological heritage managers and researchers to document and monitor sites in archaeological landscapes characterised by the aforementioned features in a fast, systematic, reproducible and cost-effective manner
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.