School of Geography, Archaeology and Environmental Studies (ETDs)
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Item 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 DannyUrbanisation 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.Item 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, ElhadiRainfed 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.Item The perceptions of Moretele residents of small scale agriculture: The case of Ga-Moeka village in the North-West Province(University of the Witwatersrand, Johannesburg, 2024-02) Malivhadza, Takalani; Pillay Gonzalez, SaritaIn South Africa, small-scale agriculture is hindered by various obstacles such as the lack of structural initiatives towards land reform, the dominance of agri-business, and related difficulties of penetrating and flourishing in the market. This research sought to understand perceptions of rural residents of Ga-Moeka (in the North-West province in South Africa) of small-scale agriculture for positive rural development. Small-scale agriculture in rural areas like Ga-Moeka is perceived and practiced as a leisure activity. While the economic potential of small-scale agriculture is recognised, it is not necessarily considered as a primary mechanism to drive positive rural development. Perceptions of small-scale agriculture in the area indicate there is a need to further explore the economic potential of rural areas in a non-binary manner. Additionally, a significant and unexpected finding was the need to also challenge the definition of rural areas and stray away from binary definitions of urban/rural. The findings in this research may support policy makers to assess and put strategies in place that are in alignment with the public’s interest, enhancing their participation in government initiatives and fast-tracking rural development.Item 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.Item Modelling and analysis of COVID-19 outspread at micro-levels using spatial autocorrelation: Case of eThekwini(University of the Witwatersrand, Johannesburg, 2024-09) Ngubane, Samukelisiwe; Chimhamhiwa, Dorman; Adam, ElhadiThe alarming effects of the COVID-19 pandemic on different socio-economic spheres have been felt across the globe. These destructive effects have prompted plenty of research to understand and control the coronavirus pandemic. Notably, one strategic method of mitigating the effects of the coronavirus epidemic has been the utilisation of spatial and geostatistical models to gain insights into the potential predictors of the prevalence of the coronavirus. Considering the above, it was the aim of this study to explore the use of advanced geospatial modelling and analysis techniques, including Moran’s I, spatial error models, spatial lag models, MGWR, and GWR for analysing and modelling the settlement level determining factors of COVID-19 incidence within the eThekwini Metro to inform effectual micro-level planning. Notably, the lack of micro-level modelling of COVID-19 prevalence predictors also motivated the undertaking of this study. To the above aim, the objectives of the research were to utilise spatial autocorrelation to map the granular level COVID-19 spatial distribution over the 3rd wave in the eThekwini Metro, compare the applicability of global and local models in analysing and modelling micro-level COVID-19 incidence, analyse the spatial dependence of the occurrence of COVID-19 on local level variables through Moran’s I and to spatially model the effects of significant local-level determinants on COVID-19. The incidence of COVID-19 cases for the 3rd wave, which was from the 2nd of May 2021 to the 11th of September 2021, was analysed and modelled. The Moran’s I result illustrated that COVID-19 incidence within the eThekwini settlement places had a positive spatial autocorrelation, with a Moran’s I value of 0.14 and a p-value of 0.00. Also, the MGWR model's local R2 value was greater (72.5%) as compared to the other models. Moreover, economic wellness score, the sum of TB cases and population density came out as the significant determining factors of settlement level incidence of COVID-19. This research report offers a great foundation for gaining insights into the applicability of advanced geospatial models in guiding targeted COVID-19 interventions at lower levels.Item Investigating the impact of the land reform policy on land use and land cover changes, in Ngaka Modiri Molema district of the North West province(University of the Witwatersrand, Johannesburg, 2024) Mmangoedi, Molebogeng Precious; Adam, ElhadiThe purpose of this study was to assess how land reform policies affected changes in land use and land cover in the province of North West's Ngaka Modiri Molema district municipality. The study employed remote sensing technologies to analyse changes in land use and land cover (LULC) resulting from the implementation of land reform programs between 1985 and 2015. The primary objective of the research was to systematically map Land Use and Land Cover types across five-year intervals spanning from 1985 to 2024, leveraging Landsat earth observation data in conjunction with a random forest classifier. These methodologies were employed to facilitate the identification of spatial patterns and trends associated with the implementation of land reform policies within the study area. Furthermore, the study utilized Landsat data and advanced change detection algorithms to quantitatively assess LULC changes over the specified timeframes. Through the application of spatial analysis techniques, the research aimed to elucidate the relationship between the implementation of land reform measures and corresponding shifts in LULC patterns across the research study area. The findings of the investigation indicated a noticeable expansion in built-up areas between the years 1985 and 2024 which was approximately 10.86%. This expansion was primarily attributed to the growth experienced by the municipality during this period. Additionally, more opportunities might have risen from the agricultural farming activities and also from the land reform policy being implemented. However, as the ownership changed due to land redistribution and more land was being acquired by black people through the land reform policy, agricultural farming decreased slightly throughout the years. The reduction was due to the factors that arose from inefficient policy implementation. The study also recommends that remote sensing techniques should be utilised to carry out studies to determine LULC changes that derive from land policies aiming at dealing with socio-economic factors and urbanisation. An incorporated agrarian reform sustainable programme has vast potential in cultivating the production of the projects, particularly if it involves packages in rural infrastructure, support services, and co-operatives. The major role of such an approach should be in the trainings conducted for the farmers, obtaining, and distributing agricultural resources and equipment to agrarian reform or beneficiaries of the land reform projects. Additionally, there should be an allowance for special grants which will be useful in supporting the government’s efforts.Item Spatiotemporal characteristics of surface water in Sua Pan, Botswana, using Earth Observation data: 1992–2022(University of the Witwatersrand, Johannesburg, 2024-10) Peplouw, Muchelene Tiara; Adam, Elhadi; Grab, StefanSurface water is a critical resource for sustaining both human and ecological health. However, climate change and human actions threaten its availability in semi-arid regions like Botswana. In addition, current research on monitoring and understanding surface water dynamics in Botswana lacks the application of remote sensing and machine learning. This highlights a crucial gap in knowledge that this study aims to address. This study investigates the spatiotemporal dynamics of land use/land cover (LULC) and surface water extent changes in Sua Pan, Botswana, from 1992 to 2022. Employing remote sensing, machine learning, and statistical techniques, the research offers valuable insights into the intricate relationships between land cover modifications, surface water variations, and climatic variables. Google Earth Engine (GEE) facilitated efficient analysis of Landsat imagery for LULC mapping. Random Forest (RF) effectively classified several land cover types within Sua Pan. To address the challenges of saline environments, a novel water index, the Saline Water Index (SWI), was developed specifically for Sua Pan. The McNemar statistical test compared the performance of SWI to established indices like the Modified Normalised Difference Water Index (MNDWI) and the Normalised Difference Salinity Index (NDSI). Surface water variations were analysed using homogeneity tests and the Mann-Kendall trend test. The relationships between hydro climatic data (rainfall, evapotranspiration, land surface temperature) retrieved from GEE and surface water area for both wet and dry seasons were evaluated using Pearson correlation coefficients and visualised by line and area graphs. Additionally, the influence of the El Niño Southern Oscillation (ENSO) on rainfall and surface water area was assessed using Analysis of Variance (ANOVA) to identify the specific ENSO phases that exert an influence. The findings demonstrate the effectiveness of GEE for LULC mapping with the RF algorithm, achieving moderate to high classification accuracy (65.2% - 90.69%) and Kappa coefficients (0.54 - 0.85). Surface water and bare area exhibited increasing trends (coefficients: 13.017 and 9.0609, respectively), whereas vegetation and salt hard pan showed decreasing trends (-16.786 and -5.3081, respectively). The newly developed SWI outperformed MNDWI and NDSI in detecting surface water, achieving the highest overall accuracy (94%) compared to MNDWI (64%) and NDSI (59%). The McNemar test confirmed no significant statistical difference between the SWI map and the validation dataset (p = 0.2673), while both MNDWI and NDSI maps showed significant differences (p < 0.0001). Utilising SWI, the study revealed that surface water was most prevalent in central and northeastern regions, with an average coverage of 33%. Seasonal homogeneity tests indicated a non-homogenous distribution of surface water area in wet seasons, with abrupt changes in 1994 and 2003. Conversely, dry seasons exhibited a homogenous distribution. The Mann-Kendall trend test identified a statistically significant (p-value = 0.01) but weak positive trend (tau = 0.329) for surface water areas in wet seasons. In contrast, the dry seasons displayed a non-significant (p-value = 0.734) and a very weak positive trend (tau = 0.043). Surface water area, rainfall, evapotranspiration, and temperature consistently increase during the wet seasons compared to the dry seasons. Notably, increased evapotranspiration significantly impacted surface water presence. ENSO exhibited no significant influence on either rainfall or surface water extent (p-value > 0.05 for both). These findings highlight the potential of earth observation data for real-time surface water monitoring in salt pans. The developed techniques offer valuable insights for policy decisions regarding environmental management and conservation efforts in Sua Pan. In addition, the study emphasises the importance of cost-effective approaches for water change assessment, particularly appropriate for under-resourced regions.Item Optically stimulated luminescence dating of Kalundu and Urewe tradition ceramics(University of the Witwatersrand, Johannesburg, 2024-03) Haupt, Rachel Xenia; Schoeman, Maria; Evans, MaryOptically stimulated luminescence (OSL) dating is a method of providing the direct age of artefacts. While radiocarbon and seriation dating provide indispensable insight into archaeological sites, the direct dating of artefacts is beneficial in entangled contexts. The Lydenburg Heads Site is significant to the beginning of the Early Farming Communities (EFCs) sequence within the Mpumalanga province. The site has been occupied multiple times, as can be seen from the presence of the two major ceramic traditions of the age, Urewe and Kalundu. The site was originally excavated and analysed by Evers (1982) in the 1970s, with a reanalysis of the ceramic assemblage by Whitelaw (1996) and organic residue analysis on the ceramics by Becher (2021). The use of OSL dating on twelve ceramic sherds allowed for new insights into the chronological intricacies within the study site. To determine the age of the ceramics, the OSL quartz dating technique was used. The adjustments to the technique involved the use of a less destructive means of sample extraction. A slightly altered version of the standard means of sample extraction was used to create a comparison and allow the dating of the ceramics to be reliable. The minimal destruction technique (MET) combined with the bulk sampling proved useful to the dating of the ceramics. The use of previously excavated ceramics meant that some aspects of age determination required estimation and analysis. The major obstacles from such were the water content, the depth of burial, and the lack of in situ soil samples. In light of the elements of ambiguity for the site, the OSL dating considered these variations and how they affected the age. The Urewe tradition ceramics were determined to be in 6th and 8th century AD. The finding creates the alignment with the range of the radiocarbon ages done within previous work and the assumptions made by Evers (1982) and Whitelaw (1996). The Kalundu tradition ceramics ages were determined to be between the 7th and 10th century AD, conflicting with previous assumptions on the occupation. The result is the possibility the ceramic assemblages could be considered to be contemporaneous. The work in this thesis has, in part, been presented at the Luminescence and Electron Spin Resonance Dating conference in Copenhagen (LED2023) and at the Association of Southern African Professional Archaeologists 2024 Biennial Meeting (ASAPA 2024).Item The Influence of Climate Change on the Speed of Movement of Tropical Cyclones in the South Indian Ocean(University of the Witwatersrand, Johannesburg, 2024-07) Mahomed, Aaliyah; Fitchett, JenniferRecent studies on the speed of movement of tropical cyclones indicate that anthropogenic warming has resulted in a 10% global decrease of tropical cyclone translation speeds over the period 1949-2016. The recent increase in high intensity storms could severely impact Southern Hemisphere regions which are considerably more vulnerable than their Northern Hemisphere counterparts. High intensity storms occurring at a lower speed would worsen the impacts of tropical cyclones resulting in prolonged periods of flooding, storm surges, and winds. This would subsequently lead to a loss of lives, economic loss and infrastructural and agricultural damage. However, studies have challenged this slowdown, suggesting that the transition to the geo-stationary era, introduces heterogeneity to tropical cyclone data. Additionally, imprecise estimates of tropical cyclone frequency influences the average speed of tropical cyclones, thereby impacting trend analysis. Using tropical cyclone data from National Oceanic and Atmospheric Administration (NOAA) International Best Track Archive for Climate Stewardship (IBTrACS), this study explores the current translation speed debate for the South Indian Ocean, over the period 1991-2021. The results of this study indicate that the translation speed of tropical cyclones has increased at a rate of 0.06km/h/yr over the 30-year period (r = 0.06 p = 0.19). Whilst the translation speed debate remains at an aggregated global scale, a comprehensive understanding of the influence of climate change on tropical cyclones is crucial for generating forecasts as this enables vulnerable regions to plan and adjust to evolving tropical cyclones.Item A geographical analysis of the impacts of construction and demolition waste on wetland functionality in South Africa: a study of Gauteng province(University of the Witwatersrand, Johannesburg, 2024-09) Mangoro, Ngonidzashe; Kubanza, Nzalalemba Serge; Mulala, Danny SimateleThe purpose of this study was to investigate construction and demolition waste management processes in sub-Saharan Africa and how they affect wetland ecosystems, using South Africa as a case study. Construction and demolition (CDW) waste has become a massive urban environmental challenge on a global scale, but more so in developing countries found in sub-Saharan Africa. In the context of South Africa, construction and demolition waste is not a waste stream taken seriously by local and national authorities because it is ‘general waste that does not pose an immediate threat to the environment. This position is premised on the idea that construction and demolition waste is generally inert (chemically inactive) and therefore cannot cause an immediate environmental risk. In this study, it is argued that the environmental risk of waste goes beyond the embedded chemical constituencies because some waste streams can cause immediate environmental risk through their physical properties depending on the location of disposal. It is further argued that although CDW is generally inert, disposal in wetlands immediately disrupts the way wetland ecosystem’s function, causing several environmental risks. To mitigate the environmental threats posed by construction and demolition waste, this study proposes a change in the methodological approaches and strategies deployed to manage the waste stream, such as by introducing a hybrid of circular economy and industrial ecology to minimize or eliminate waste production. This study involved several data collection and analysis methods. Using a combination of qualitative and quantitative studies methods, data was collected with the goal to understand the perceptions of experts on how construction and demolition waste management in South Africa affects wetland ecosystems and what can be done to effectively manage the waste stream in the context of a developing country. Data informing this study were collected through semi-structured interviews and surveys in the province of Gauteng, specifically in the City of Johannesburg and City of Ekurhuleni Municipalities, where there is massive illegal dumping in wetlands for various reasons. Furthermore, apart from the use of semi-structured interviews and surveys, a digital elevation model was generated in ArcGIS Pro 10.1 software to measure the effects of construction and demolition waste on wetlands in the study area. The approach to this study using both qualitative and quantitative methods was crucial because it provided human perceptions which were accurately corroborated by GIS software. The study found that construction and demolition waste management in South Africa is affected by several challenges that lead to massive illegal dumping in critical ecological ecosystems such as wetlands. In a broad sense, the major challenge to sustainable construction and demolition waste management in South Africa is institutional failure at both the local and national levels. Local authorities such as municipalities are characterized by massive corruption, poor funding, and lack of strategic technologies among other things, while at the national level, there is massive interference with municipal affairs through bureaucratic delays in the disbursement of municipal funds. A combination of these and other factors leads to illegal dumping of construction and demolition waste across the Gauteng Province, particularly in wetlands in low-income areas. The data informing this study reveals that dumping construction and demolition waste in wetlands causes an immediate threat to the existence of wetlands through massive sedimentation with insoluble materials. It is ultimately found that construction and demolition waste destroy the ability of wetlands to offer ecosystem services such as flood attenuation, carbon sequestration, water filtration, and habitat provision, among other functions, leading to environmental events such as flooding. A combination of circular economy and industrial ecology can be one of the ways that can be deployed to effectively and sustainably manage construction and demolition waste in South Africa. The circular economy and its three principles of ‘reduce’, ‘recycle’, and ‘reuse’ has been successfully deployed in developed countries in the European Union, where recycling has topped 70% of the total construction waste generated. Industrial ecology with its analogy of industrial ecoparks has been deployed in the European Union with immense success, until more attention was directed to circular economy. With an increase in municipal funding and introduction of a construction waste information system, a combination of ‘circular economy’ and ‘industrial ecology’ can significantly help to reduce pressure on wetlands and the environment at large. Even though the methodological improvements suggested above could significantly reduce pressure on wetlands, the implementation could be faced with institutional challenges. Therefore, it is argued that urgent institutional transformation is required to make tangible changes in the field of construction and demolition waste management. It is recommended that there should be increased law enforcement to curb widespread illegal dumping in South Africa’s major cities. It is also recommended that, like in Europe, South Africa must introduce tailor-made legislation of policies for construction and demolition waste alone. Promulgation of dedicated legislation provides clear direction on how the waste stream is managed and who is responsible for specific roles. Furthermore, dedicated legislation can be a crucial tool to deliver sustainable construction and demolition waste management in South Africa because it can be used to encourage the use of recycled aggregates and limit the amount of illegal dumping or extraction of materials from the environment. Finally, dedicated construction and demolition waste legislation can be used to shift from the traditional view of pollution or contamination through toxicity, and so the value of this study is immediately apparent.