Theses and Dissertations (Geography, Geoinformatics and Meteorology)

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Assessing the correlation between malaria case mortality rates and specific socioeconomic factors
(University of Pretoria, 2019-08) Adeola, Abiodun M.; rynocoetzer11@gmail.com; Coetzer, Ryno Harm
Background Various local villages in the Vhembe district of South Africa have experienced high malaria infection rates together with a high variability of malaria case mortality rates over the past 20 years. This research project sets out to determine if socioeconomic factors, (specifically the location of medical facilities and a geographical aspects) have a significant influence on the varying malaria case mortality rates. The data from this study could assist societies and authorities in mitigating the negative effects of malaria infections on human life expectancies through improved socioeconomic development. Methods The study used existing medical records of all reported malaria cases in the Vhembe district between 1998 and 2017. The data comprised malaria cases recorded at 263 medical facilities that reported 57 974 infections from 850 source locations across the villages and formal neighbourhoods. The data set was sampled using maximum variation sampling combined with a stratified sampling approach to select the 30 source locations with the highest reported variations in malaria case mortality. The number of medical facilities used, distances to the medical facilities, and proximity to significant water sources were subsequently spatially and statistically analysed for the sample source locations to determine potential correlations between these factors and the malaria case fatality rates of the source locations. Results The statistical analysis indicated a significant negative correlation between the case mortality rates and the number of medical facilities used by the sample source locations, the number of infections reported, and the maximum and mean distances travelled to the medical facilities used. This suggested that malaria patients from larger communities, those who had financial or other means to consult more advanced facilities or those with a larger variety of services had a significantly lower risk of mortality. In addition, the analysis indicated a positive correlation between the minimum distances travelled to the medical facilities used and the case mortality rates, indicating that, although maximum and average travelling distances had a negative correlation, medical facilities situated within the vicinities of communities could have a positive impact on reducing case mortality rates. The spatial analysis supported the majority of the findings from the statistical analysis, except for a small cluster of source locations that need further investigation. Proximity to significant water bodies was not found to have any significant impact on case mortality rates.
Exploring the relationship between ambient air pollution and adolescents in South Africa
(University of Pretoria, 2024-07-12) Wright, Caradee Y.; Garland, Rebecca; d.ann.millar@gmail.com; Millar, Danielle Ann
Air pollution is a significant health concern in South Africa, with a growing population contributing to the sustained industrial activities, vehicle emissions, and residential energy use. Outdoor air pollution remains high from industrial processes, mining, and historical urban planning. Despite the implementation of National Ambient Air Quality Standards (NAAQS), many regions in South Africa frequently experience exceedances of these standards. Short- and long-term exposure to air pollution presents an increased risk in developing adverse health effects in adults and children. Adolescence is a period of rapid physical, emotional, and social growth and change. Adolescents are a vulnerable and under-research sub-population group. Research is limited in considering the health effects of air pollution exposure on adolescent health, particularly in low- and middle-income countries (LMICs). This study aimed to explore the relationship between ambient air pollution and adolescent health and wellbeing in areas where air pollution is a public health concern, and, drawing together this information, provide meaningful insight and recommendations for policy. These aims were addressed by 1) examining the existing literature and research outcomes on adolescent health and wellbeing in LMICs, 2) conducting a health risk assessment on an air pollution hotspot in the Highveld Priority Area (HPA) in South Africa, establishing the risk of developing adverse health outcomes by continued exposure to poor air quality, and 3) quantify the self-reported effects of air pollution exposure on adolescents living in two adjacent towns in the HPA. A comprehensive literature review was conducted and explored the effects of exposure to criteria air pollutants on adolescent health and wellbeing in LMICs. After screening, sixty articles were included in the review. Multiple adverse health outcomes were described in the literature, and these were grouped into five main categories: pulmonary and respiratory effects; cardiovascular, cardiopulmonary, and haematology effects; metabolic effects; inflammation and cytogenotoxic effects; and miscellaneous health effects. The results of these studies showed that exposure to air pollution – particularly particulate matter (PM) – results in the onset of adverse health conditions, typically in a dose-responsive manner. Adverse health effects included decreased pulmonary function, increased blood pressure, increased prevalence of obesity, and increased risk in developing neurodegenerative conditions. These results highlight the increased susceptibility and vulnerability of adolescents to the development of adverse health outcomes in relation to air pollution exposure. To address the second objective of this study, using the United States Environmental Protection Agency framework considering hazard identification, exposure assessment, concentration-response analysis, and risk characterization, a comprehensive health risk assessment (HRA) was carried out PM2.5, SO2, and NO2 in the Mpumalanga HPA. Ambient air quality data were obtained for six air quality monitoring sites, from 2009 to 2020. The region is plagued by poor ambient air quality due to intensive mining, industrial, and agricultural activities. It is also an area that experiences a dry and dusty winter climate. Results from the study showed that PM2.5 concentrations frequently exceed the SA NAAQS across all six sites considered, indicating increased risk of respiratory and cardiovascular diseases. A hazard quotient (HQ) is calculated by dividing the measured ambient air quality concentrations for specific averaging periods by existing NAAQS or World Health Organization (WHO) Air Quality Guidelines (AQG) for the same averaging period. HQs > 1 indicate an increased risk in developing non-cancerous health effects. The HQs measured for PM2.5 for the time period considered frequently exceeded one. By contrast, SO2 and NO2 HQs were less than one for the period studied. While this information is invaluable, there were large gaps in the data due to data unavailability over the time period considered. Irrespective of the gaps, the data depicted an alarmingly poor state of air quality in the HPA which deserves immediate attention. Lastly, the self-reported health effects of adolescents living in a town and adjacent community in the HPA were observed. The town of Secunda and the adjacent community of eMbalenhle were historically established to serve an area of intense mining, coal-burning power plants, and a coal liquefaction plant. Historical (2009 – 2019) ambient air quality data were obtained from proximal air quality monitoring stations. Four local high schools were approached by the researchers for willing participants (233 participants, aged 13 – 17 years old). Once assent and consent were obtained, a socio-economic-demographic questionnaire was filled in by each participant including questions pertaining to other health risk factors such as indoor air pollution (use of biomass as a cooking and heating fuel source in the household), environmental tobacco smoke exposure, pets, and nutritional status. Anthropometric measurements were taken by field assistants. Results from the study showed that, in keeping with the results from the HRA, the ambient air quality in the area frequently exceeded the NAAQS. Adverse respiratory outcomes were reported by adolescents, and this relationship was statistically positively associated with increased number of years living in the area. These results indicate that prolonged exposure to poor ambient air quality is associated with adverse health outcomes in adolescents living in an air pollution hotspot in South Africa, and highlights the need for intervention from policymakers to protect communities from air pollution. This thesis offers important insights for policymakers and researchers, highlighting the importance of focusing research and preventative efforts on air pollution and health, particularly in the under-researched sub-population of adolescents. By increasing the focus on adolescents and addressing health concerns timeously, the knock-on effect will result in a healthy workforce and healthier population in coming years. The research presented in this thesis is in keeping with the United Nations’ Sustainable Development Goals (SDG), specifically SDG 3 (Good Health and Well-being) and SDG 7 (Affordable and Clean Energy).
A proposed risk assessment framework for public health responses : a case study of Melusi, an informal settlement in Gauteng, South Africa
(University of Pretoria, 2023-10-30) Davis, Nerhene; Rautenbach, Victoria-Justine; Coetzee, Serena Martha; sempenhlanhla@gmail.com; Sempe, Nhlanhla Pheletso Suzan
This study focused on Melusi, an informal settlement in Pretoria. The COVID-19 risk assessment framework in this study was developed from existing risk assessment frameworks which were reviewed in the context of COVID-19. Based on this evaluation the study proposes a COVID-19 risk assessment framework that was applied in the context of Melusi. Data was collected through a mixed method approach where primary data (qualitative) was collected from focus group discussions held with 21 community health workers stationed in the settlement, and the secondary data (quantitative) was retrieved from the University of Pretoria Community Oriented Primary Care (UP COPC) unit’s household data. Through the adoption of the mixed method approach, it was found that, in the context of COVID-19 in Melusi, the greatest exacerbators of the community’s vulnerability were the physical structure of the dwellings; household size; access to water and handwashing facilities; and the cleanliness of the communal bucket (portable) toilets. The community’s attitude towards masks, sanitizers and social distancing compromised the settlement’s overall preparedness. Lastly, the community’s resilience scores were lowered by the overall reliance on public transport for most community members and the nature of employment for most community members. These findings provide an indication of the need for more risk assessments at the informal settlement scale, which would facilitate in streamlining health responses in informal settlements.
Dust storms over South Africa : synoptic weather patterns and evolution of meteorological variables associated with significant dust storm events
(University of Pretoria, 2024-06) Garland, Rebecca; Dyson, Liesl L.; malia.age@gmail.com; Maliage, Mbavhalelo
Dust storms (DS) are common in semi-arid and arid regions, with the majority of the natural dust source regions located in the Northern Hemisphere. Although there are some significant source regions in the Southern Hemisphere, South Africa is not a major contributor to dust emissions. Consequently, very little research has been conducted on DS in South Africa. However, there has been an increase in anthropogenic source regions linked to agricultural activities over the central parts of South Africa. With the expected increase in DS frequency over South Africa, it is therefore important to understand the meteorological factors associated with these DS. The study aims to first identify the main synoptic weather systems that produce DS over the country, separating the findings according to DS along the coast and DS over the interior of the country. Secondly, the study aims to identify how meteorological variables evolve before, during, and after a DS. Ten DS are selected for analysis, five from coastal regions and five from the interior. The weather systems associated with coastal DS are similar for all five DS: a surface trough extending along the west or adjacent interior. This often results in offshore flow along the west coast, also known as berg wind conditions. For interior DS, three are a result of thunderstorm activity, with one DS associated with a cut-off low. Two DS were triggered by cold fronts, one being a prefrontal dust storm and the other a post-frontal dust storm. The meteorological variables analysed are temperature, focussing on the diurnal temperature range (ΔT) and the maximum temperature (Tmax), wind speed and direction, relative humidity (RH), dew point temperature (Td), rainfall, and soil moisture. All coastal DS had an easterly component to the wind direction, which is caused by the location weather systems that caused the DS. The DS that lasted the longest, did not have the lowest RH, Td, or temperature, but had the strongest wind gusts and strongest high-pressure system. The results indicate how DS are associated with drier atmospheric conditions, which are depicted by low RH and Td. This is observed with synoptic scale-induced DS, where the RH and Td gradually decrease, being the lowest on the day of the DS. However, the opposite was observed for mesoscale-induced DS. The presence of thunderstorms associated with the mesoscale-induced DS meant that there was enough moisture in the atmosphere for their development, indicated by higher Td and RH values. The results also show that the behaviour of the meteorological variables is influenced by several factors such as whether it is a synoptic-scale or mesoscale weather system, the duration, and strength of the weather system associated with the DS, the season in which the DS occurred, as well as the location or source region of the DS. Overall, this study is a base study for DS over South Africa, to contribute to the research necessary for a decision tree for forecasting DS in the future.
Land use and climate change implications for biodiversity and habitat loss within the public and private reserves of the Southern Waterberg district, Limpopo
(University of Pretoria, 2024-04-24) Archer, Emma; Ramoelo, Abel; longhurstmiles@gmail.com; Longhurst, Miles
The planet is facing a range of environmental issues related to and caused by anthropogenic activities. Biodiversity loss constitutes one of the most significant environmental tragedies of modern times. Climate change and land use changes may have severe consequences for biodiversity, ecosystem services, and habitat loss globally. The impacts of land use change and climate change may also differ between protected areas, and those areas surrounding protected areas. This can occur due to factors such as differences in management and conservation plans, as well as differing land use practices and development. Due to such factors, climate change and land use changes may cause the rate of biodiversity loss to be greater in areas surrounding protected areas, as opposed to within protected areas. The mountainous area known as the Waterberg Biosphere, located in the Southern Waterberg, has rich biodiversity, including more than 5,500 species of plants, 43% of which are endemic to South Africa. The dominant biome in the Southern Waterberg is the Savanna Biome. To investigate these impacts (land use and climate changes) in the Southern Waterberg, a range of mapping and visualisation methods have been implemented and used as well as statistical analysis (Chi-square analysis and linear regression). Two specific locations were the focus of this study, namely the Grootwater Nature Reserve (3.32 ha) and the Welgevonden Game Reserve (28.57 ha), which are located within the Waterberg Biosphere. The Grootwater Nature Reserve (an example of a public reserve), and the Welgevonden Game Reserve (an example of a private reserve) were compared in terms of the extent of habitat/vegetation loss within and surrounding the protected areas. Further, the extent of habitat/vegetation loss within the protected areas in comparison to the surrounding areas (5km buffer) was assessed between 1990 and 2020. Climatic changes (rainfall and temperature trends) were also assessed for the area from 1990 to 2020. Landcover maps (SANLC), Chi-square analysis, and linear regression analysis illustrated this comparison. Landcover data and maps were also used to illustrate the extent of land use changes in the study areas. Statistical analysis was then also introduced to confirm the difference in habitat and vegetation loss within and surrounding the two protected areas, as well as to gauge the relationship between the climatic changes in the area and habitat/vegetation loss within the study sites. The results indicated that both protected areas experienced habitat/vegetation loss to a lesser extent than the surrounding areas. Further, the Welgevonden Game Reserve experienced more habitat/vegetation loss than the Grootwater Nature Reserve. Trend analysis indicated that there was a general increase in average temperatures and decrease in average rainfall from 1990 to 2020 in the area. Statistical analysis suggested that habitat/vegetation loss was most likely due to climatic changes (particularly a decrease in total annual rainfall and increase in monthly maximum temperatures) rather than land use changes.
Site selection for rainwater harvesting : a case of KwaZulu-Natal, South Africa
(University of Pretoria, 2024-05-07) Adeleke, Adedayo; u20765780@tuks.co.za; Nunu, Masimthembe
The rapid growth of the world’s population has placed an increased strain on water resources globally, particularly in sub-Saharan Africa, where communities rely on rainfall for their day to day activities. Water scarcity in KwaZulu-Natal, South Africa, is high because of unevenly distributed rainfall and limited water resources. There is a need for suitable site selection for rainwater harvesting structures in KwaZulu-Natal, which has the potential to address shortage of water currently experienced in the province. Access to adequate water supply and sanitation is crucial for poverty alleviation and addressing the problems faced by vulnerable groups, such as those affected by HIV/AIDS and other diseases. Rainwater collection is a procedure in which rainwater is gathered and stored for a multitude of objectives. This practice encompasses the capture of precipitation either at its point of descent or via the accumulation of runoff from various surfaces such as rooftops, roadways, or landmasses. By facilitating the optimal utilization of rainfall, rainwater collection endorses a diminished reliance on conventional water sources and the minimization of water dissipation. It contributes to the conservation of water resources and ensures their sustainable management. This study aimed to select suitable sites for rainwater harvesting using geographic information systems (GIS) and multi-criteria decision analysis (MCDA) techniques in the province of KwaZulu-Natal, South Africa. Geospatial data on precipitation, soil, slope, runoff curve number and land use were combined to develop a multi-criteria ranking system. Using the Analytical Hierarchical Process (AHP), weights were assigned with rainfall assigned (17), soil texture (39.1), slope (11.3), land cover (5.6) and Runoff curve number (27). The selection of these specific factors for this study areas was based on a review of literature. The study identified moderately to highly suitable sites for rainwater harvesting structures, covering 38% of the study area. Approximately 10% of the study area was considered to be less suitable for rainwater harvesting (RWH). The research findings could facilitate the wider adoption of rainwater harvesting in KwaZulu-Natal to meet irrigation demands and promote sustainable water resource management. The developed methodology can be implemented and adopted by any city or country. This study could be expanded by collecting and analysing various parameters (such as distance to roads, groundwater discharge, and geology and lineaments density, expertise and decision-makers preference value for pairwise matrix comparison). The development of a graphical user interface and improved approach in MCDA in relation to relative weight calculation while integrating the water balance model may also be considered for future research.
Automatic building footprint extraction using remote sensing data within the City of Cape Town
(University of Pretoria, 2023-11-30) Adeleke, Adedayo; khumelenimakungo5@gmail.com; Makungo, Khumeleni
In the City of Cape Town Metropolitan (CoCT), South Africa, GIS analysts currently delineate building footprints by digitizing aerial imagery and stereo-aerial images. This approach requires a lot of manual work. It takes a long time, is expensive, and inefficient. Recent studies have explored automatic and semi-automatic methods for extracting building footprints. Automatic extraction of building footprints from remotely sensed data is useful for urban planning, service delivery, and humanitarian efforts. However, there is currently no readily available method that can automatically extract footprints while considering the unique characteristics of the landscape, such as formal residential areas, industrial zones, and informal settlements. Therefore, the main goal of this research is to find a suitable and efficient spatial analysis method that accurately extracts building footprints of different sizes and shapes within the City of Cape Town, South Africa, using high-resolution aerial imagery and LiDAR-derived nDSM. To achieve this goal, a literature review is conducted to explore different building footprint extraction algorithms. The review identified Mask Regional Convolutional Neural Network (R-CNN) as an effective algorithm for instance segmentation and object extraction. Thus, an experiment is conducted to implement Mask R-CNN models that extract building footprints from aerial imagery and LiDAR-derived normalized Digital Surface Model (nDSM) for each of the three areas: formal residential, industrial, and informal settlements. The training focused on the Blaauwberg district, which includes formal residential areas, industrial zones, and informal settlements. Each trained model is separately tested on testing datasets for formal residential, industrial areas, and informal settlements. Evaluation metrics such as precision, recall, F1-score, and Average Precision (AP) score are calculated for each model to assess their performance in extracting building footprints from aerial imagery and LiDAR-derived nDSM in formal residential, industrial areas, and informal settlements. The Mask R-CNN algorithm proved to be very effective in extracting building footprints from high-resolution aerial imagery and LiDAR-derived nDSM in formal residential areas, achieving satisfactory precision, recall, F1-score, and AP score. In industrial areas, the Mask R-CNN algorithm is found to be highly effective in extracting footprints from LiDAR-derived nDSM. However, when extracting shacks in densely populated settlements, the Mask R-CNN algorithm performed inadequately, with an AP score of 0.28 and 0.31 from aerial imagery and LiDAR-derived nDSM, respectively. Nevertheless, the fusion of footprints extracted from LiDAR-derived nDSM and high-resolution aerial imagery improved the AP score to 0.52. Hence, this study concludes that the Mask R-CNN algorithm is highly effective in extracting building footprints in formal residential areas from both aerial imagery and LiDAR-derived nDSM, as well as industrial building footprints from LiDAR-derived nDSM. For optimal performance in informal settlements, the fusion of footprints extracted from aerial imagery and LiDAR-derived nDSM is necessary. Overall, these trained Mask R-CNN models demonstrated satisfactory performance. To enhance the existing 2D building footprint layer, these models can supplement by extracting building footprints. This updated layer will be more comprehensive and current. Various departments within the CoCT can utilize this layer for infrastructure planning, service delivery planning, land use planning, and change detection. For better performance, it is recommended to add more informal and industrial training datasets with sufficient roof variability. Fine-tuning the Mask R-CNN models will ensure accurate extraction of shacks and industrial building footprints by allowing the models to learn effectively.
Developing a Water-Energy-Food nexus-based approach for sustainable climate change adaptation interventions : a case study of Mpumalanga province
(University of Pretoria, 2023) Ramoelo, Abel; Tsele, Philemon; wongalethusilwana640@gmail.com; Silwana, Wongalethu
The challenge of meeting the growing demands for water, energy, and food is further complicated by the impact of climate and land use and land cover (LULC) change. The Mpumalanga Province where agricultural production compete with coal mining for land and water consumption is a prime example of challenges involved in sustaining the water, food, and energy. A more holistic understanding of LULC can help in managing competing land use objectives, leading to improved climate change adaptation strategies. The Water-Energy-Food (WEF) nexus is an effort to address challenges affecting WEF sectors by taking into consideration the inter-relatedness and interdependencies between these sectors to balance their perspectives and management. As a result, this study aimed to undertake a pragmatic approach that is based on geospatial analytical methods to support WEF nexus climate change adaptation in South Africa’s Mpumalanga Province. To achieve this, the study investigated the impact of LULC change on WEF resources by analyzing South African National Land Cover (SANLC) data from 1990, 2014, 2018 and 2020 using Geographical Information Systems (GIS) and remote sensing techniques. The study also located the recently completed and ongoing adaptation projects that contribute to the WEF nexus in the study area. As such, the logistic regression model was implemented using three scenarios to understand the drivers of the location of the WEF nexus-based climate change adaptation interventions or actions spanning from environmental to socio-economic drivers. Scenario 1: Model based on environmental variables only; Scenario 2: socio-economic variables only and scenario 3: combining environmental and socio-economic variables. Based on the understanding of the drivers and spatial estimation, a framework or model was developed to synthesize and prioritize potential areas of climate change adaptation intervention or action in Mpumalanga Province. The results of LULC change over the study period (1990 – 2020) show that the LULC areas under agriculture, built-up areas, mines and quarries increased from 18.84%, 2.33%, 0.61% in 1990 to 23.73%, 3.41% and 0.79% in 2020, respectively. While grasslands have decreased from 37.36% in 1990 to 30.39% in 2020. All of these changes have a direct impact on water supplies, energy sources, and food production. It was evident that more interventions were associated with areas of extreme climatic variables (e.g., drought related). All models were statistically significant, with Area Under the Curve (AUC) = 72% for scenario 1; 67% for scenario 2 and 73% for scenario 3. The results of the spatial estimation revealed that the northeastern region and northwestern region of the Mpumalanga Province should be prioritized for adaptation interventions. This work provided a broader view of the impact of resource use and management on the overall environment and societal well-being. The results obtained from this study indicate that the use of geospatial tools can be beneficial in the planning and prioritization of activities related to climate change adaptation.
Phytoremediation potential and growth response of pasture species used in the revegation of coal mine substrates
(University of Pretoria, 2024-02-28) Truter, Wayne F; beschmidhuber@gmail.com; Schmidhuber, Barbara Ernestine
This paper focuses on the hyperaccumulation potential and plant stress of pasture species, in an attempt to remediate soils contaminated by coal mine activities, for alternative end land uses.
The analysis of tropical temperate trough-associated rainfall onsets and their influence on maize yields in the Maize Triangle, South Africa
(University of Pretoria, 2024-02-27) Ndarana, Thando; Mathole, Kelebogile Ruth; nxumalo.mthobisi@gmail.com; Nxumalo, Mthobisi Percival
Tropical temperate troughs (TTTs) that were associated with rainfall onsets in the Maize Triangle, South Africa, were analysed during the period from 1979 to 2018. Maize yields for agricultural regions within the Maize Triangle were also investigated to determine if the association of the above-mentioned variables had any influence on their trend. Various datasets which included observed TTT cases, daily rainfall, outgoing longwave radiation (OLR) and maize yields were obtained from various providers. These datasets were processed, merged and analysed accordingly using various tools and methods to address the study objectives. The study analysed the climatology of TTTs over southern Africa and found that their activity is highest during the early period of the rainy season (September to November), when the Intertropical Convergence Zone (ITCZ) is at its lowest latitude, and they retreat mid-season while the significantly disappear during the latter part of the season. The study found that almost all rainfall onsets were associated with TTTs, implying the importance of TTTs, particularly for early rainfall onsets in the study area. The study also found that early occurring TTT-associated rainfall onsets were responsible for much of the rainfall that was concentrated over the eastern parts of the Maize Triangle while that which occurred mid-season was almost evenly distributed over the study area. Final analysis indicated that maize yields were not affected by subsequent TTT-associated rainfall onsets which can be attributed to the large number of non-meteorological activities that occur during the planting, growing and harvesting periods.
Exploring the potential of using unmanned aerial system imageries in managing the Miombo woodlands of Zambia
(University of Pretoria, 2023-12-05) Ramoelo, Abel; Chirwa, Paxie W.; Syampungani, Stephen; Hudak, Andrew; hshamaoma@gmail.com; Shamaoma, Hastings
The efficient implementation of REDD+ programs and local sustainable forest management needs reliable data on species composition and distribution, forest biomass, and carbon storage, which are presently lacking in the majority of African vegetation formations. The study explored the use of unmanned aerial systems (UAS) imagery and associated processing tools in the management of the Miombo woodlands in Zambia. Four different studies were undertaken to meet the overall objective of this study. In order to have an overall understanding of the global application of UAS in forestry and the implications for its application to the Miombo woodlands, the first study was based on a review of the application of UAS in forest management and monitoring with a focus on challenges and opportunities for use in the Miombo woodlands. UAS technology, key attributes of the Miombo woodlands, and applications of UAS in forestry at the global and sub-Saharan African levels were reviewed, which enabled us to identify key prospects and challenges for UAS applications in the Miombo region. As a demonstration of potential applications of UAS technology for managing the Miombo woodlands, the second study was focused on the use of multi-date and multi-spectral UAS imagery to classify dominant tree species in the wet Miombo woodlands in the Copperbelt Province of Zambia. Multi-date, multispectral UAS images taken at key phenological stages (leaf maturity, transition to senescence, and leaf flushing) and object-based image analysis (OBIA) with a random forest algorithm were utilized to classify the five dominant canopy species of the wet Miombo woodlands. The research found that combining multi-date raw band multi-spectral data with derived spectral indices produced better classification results (87.07% overall accuracy (OA), 0.83 Kappa) than using the best single-date multi-spectral data (80.12% OA, 0.68 kappa). The results from this study demonstrated the potential of using multispectral UAS imagery and phenology to map individual tree species in the Miombo woodlands of Zambia. The third study was based on the application of UAS-Lidar to estimate forest structural attributes, which are critical to the management of the Miombo woodlands. UAS-Lidar data was used to estimate above-ground biomass, basal area, diameter at breast height, and volume, using multiple linear regression. The results indicate that the UAS-Lidar estimations provide the requisite degree of precision (relative root mean square error (RMSE): 3.40 - 20.89%) required for fulfilling international carbon reporting requirements and local forest management objectives. Furthermore, the use of unmanned aerial systems (UAS) equipped with Light Detection and Ranging (Lidar) technology offers a significant enhancement to the already utilized approaches for assessing Forest Structural Attributes (FSA) in the Miombo woodlands. The fourth study was focused on bridging the spatial data gap that exists between detailed field inventory methods and satellite-based remote sensing methods that are required for wall- to-wall mapping of the Miombo woodlands. This study conducted a two-phase sampling design for wall-to-wall forest structural attributes estimation, where areas covered by a UAS-lidar were sampled by field plots and areas covered by wall-to-wall satellite imagery were sampled using a UAS-lidar. The results revealed that using UAS-lidar as reference data for predicting AGB using Sentinel-2 image metrics produced better results (Adj-R2 = 0.70 Mg/ha, RMSE = 27.97 Mg/ha) than using direct field estimated AGB and Sentinel-2 image metrics (R2 = 0.55 Mg/ha, RMSE = 38.10 Mg/ha). The results obtained demonstrated a practical solution to managing the Miombo woodlands using the available technology at multiple spatial scales. The synthesis of these studies provides a holistic contribution for utilization of UAS technology and its accompanying processing tools in improving the acquisition of inventory data for the purpose of managing the Miombo woodlands in Zambia. This is a crucial necessity in effectively managing the diverse forested landscapes in the region.
Efficacy and biases In inspections for biosecurity threats In South Africa
(University of Pretoria, 2024-02-13) Robertson, Mark P.; Faulkner, Katelyn T.; freedoms8310@gmail.com; Shabangu, Freedom R.
Trade in agricultural commodities is beneficial economically, but it carries risks, as alien agricultural pests can be imported into new regions. To manage this challenge, inspections of agricultural produce are performed at South Africa’s ports of entry. This study aims to evaluate the efficacy and identify biases in agricultural inspections on fresh fruit imports to South Africa. Pest interception data for quarantine and non-quarantine insects from fresh fruit imports between 2008 and 2018 from the South African Department of Agriculture, Land reform and Rural Development was analysed. For this analysis, trade pathways were analysed to have three components: the country of origin (o); agricultural commodity (c); and insect species (i). For each trade pathway, the trade volume to be inspected (TV) and the trade volume to be inspected per interception (TVPI) were calculated using import data and host distribution data. TV is an indicator of the risk of importing a particular organism on a given pathway. TVPI can be used to identify pathways where the expected risk is high (high TV), but where the number of interceptions is lower than expected based on risk. During the assessed period there were 399 interceptions on 13 fruit types imported from 22 countries. Only 48% of interceptions were identified to the species level, with quarantine species accounting for far fewer interceptions (45 individuals of 12 species) than non-quarantine species (354 individuals of 75 species). Control bias was observed in quarantine species, indicating the need to improve inspection strategies and sampling efforts to increase the effectiveness of border controls in South Africa. To promote good biosecurity, further studies should be conducted to analyse control bias based on sampling effort data than interceptions relative to TV, to improve phytosanitary controls on agricultural imports, especially fresh fruit.
Historical and future changes in climate records and extremes in South Africa
(University of Pretoria, 2024-02-15) Kruger, Andries C.; Dyson, Liesl L.; charlotte.mcbride@weathersa.co.za; McBride, Charlotte May
Extreme climate events, by definition, are rare. However, due to climate change, the frequency and intensity of these events are changing, with many regions across the globe experiencing an increase in the occurrence of these. It is unequivocal that these types of events are expected to continue to increase into the future. Their impacts are expected to affect societies differently depending on various social-economic, political, and environmental factors. However, no matter where a particular society finds itself, there will be a need to respond to these changes to lessen the negative impacts of these types of events. With scientific knowledge about how our climate is changing, formulating mitigation and adaptive interventions becomes more accessible, especially if that knowledge is at a national or local level. Accordingly, the main objective of this research is to determine the historical and projected changes in the likelihood of occurrence of climate records and extremes over South Africa and the possible consequences of these changes on relevant socio-economic sectors. The research focused on using statistical methods to understand the changing landscape of probabilities of weather and climate extremes. Therefore, the magnitude of the values to be investigated was on the scale of record-breaking observations and extreme values associated with multiple-year return periods. The warming trend at individual stations, specifically the positive (right) tails of the distributions, was considered in the study. Consequently, extreme value theory was applied to study temperature and precipitation extremes changes. Various statistical approaches were pursued depending on the nature of the variable under consideration. For example, the Peak-Over-Threshold (POT) method was applied in the precipitation study because extreme can occur multiple times in wet years and not in dry years, and thus, using threshold values rather than the highest annual value becomes applicable. Threshold and critical values were also considered in the projections of temperature extremes and daily rainfall extremes to analyse changes in the distribution of these values. Considering that the research focuses on both changes from a historical and future perspective, both observational data and model projections were analysed, focusing on daily temperature and precipitation extremes. Key findings of the study were an increase in the expected number of record-breaking daily maxima of maximum and minimum temperatures compared to a stationary climate. For example: On average, the highest maximum to lowest minimum records ratio was 1:1 in 1951, increasing to 9:1 in 2019. In addition, different spatial patterns in terms of breaking daily high temperature records were observed, with stations in the interior of South Africa presently experiencing the highest probability of breaking daily maximum temperature records. For daily highest minimum temperature records, the present probabilities are less defined on a regional basis. In contrast, the number of daily lowest maximum and minimum temperature records decreased below the expected in a stationary climate, so much so that in some locations, no records were broken in the last decade. The average warming trend was able to predict the occurrence of records to an extent. When considering the projected occurrence of high-temperature extremes into the far future (2036-2095), it was found that most stations showed a decrease in return periods and, therefore, a consequent increase in return period values (RPVs). The most significant changes were expected to occur under the RCP8.5 scenario compared to RCP4.5, with these changes most evident at the end of the century. Even after bias correction, the models underestimated the extent of the warming in the right tails of the temperature distributions, and thus, the projected changes found in the study are seen as a conservative estimation of potential changes in extreme temperatures in the future. In terms of daily rainfall extremes across South Africa, this study found that most stations experienced an increase in the probability of receiving more than 50mm per day, considered to be significant, over the last century. The same applies to values greater than 75mm, i.e. heavy rainfall, and 115mm, defined as very heavy rainfall. Maximum values expected for relevant return periods have also increased. In summary, the research quantitatively confirms the widely held expectation that under an anthropogenically caused non-stationary climate, the probabilities of climate extremes are changing towards a situation of higher-than-expected probabilities of records and extremes, specifically with regards to daily values of temperature and rainfall. Therefore, the research contributes to the quantification of the changing probabilities in records and extremes and, if used, may contribute to the development of climate change-relevant adaptation measures in climate-sensitive sectors, e.g. agriculture, health, disaster management and the insurance and building industries. In addition, the estimations of changes in extreme events can assist in the spatial allocation of resources to mitigate specific weather and climate hazards.
Automating exploratory spatial data analysis (ESDA) for vector and raster data : development and evaluation of the autoESDA Python library
(University of Pretoria, 2023-11-20) Rautenbach, Victoria-Justine; Fabris-Rotelli, Inger Nicolette; u17198021@tuks.co.za; De Kock, Nicholas
autoESDA is a Python library developed with the aim of automating the Exploratory Spatial Data Analysis (ESDA) process. This is done by generating a HTML report made up of various ESDA graphs and statistics calculated according to the input dataset, requiring no other inputs from the user. ESDA (local spatial autocorrelation specifically) in Python has been a challenge for raster datasets, with software support lagging behind alternative platforms such as R. This dissertation documents the improvements made to the original library. These improvements include the support for raster datasets, an updated architectural design, and other minor, cosmetic improvements. The performance of the updated version of autoESDA is evaluated by investigating how its processing time varies according to vector and raster datasets that differ in size and complexity. These results are then discussed as a measure of how well the library has achieved its goal of automating the ESDA process. Finally, a roadmap for further improvements to the library is discussed.
Improved trail usability and information accessibility for the nature reserves of Tshwane - a geoinformation science approach
(University of Pretoria, 2024-02-08) Hansen, Christel; melandriesmit96@gmail.com; Smit, Melandrie
The usability of the nature reserves in the City of Tshwane, which is located in the province of Gauteng, South Africa, is a consequence of the information accessibility that the users of these areas have. Although maps have been produced for some of the nature reserves, these maps do not provide information on the level of difficulty of the trails. By incorporating information such as the difficulty level associated with each trail, users can better understand the physical requirements associated with the given trail, which in turn increases the usability of these areas. Importantly, this directly relates to SDG 11 which states that cities and communities must be, amongst other, more sustainable, and inclusive. This study aims to improve the information accessibility of the nature reserves in the City of Tshwane, by creating resources that better inform users of the relevant features of the reserves, more specifically the physical characteristics of the available trails. Various known algorithms were used to model the physical parameters needed to grade the trails. These algorithms included The Modified Hiking Function, Pandolf’s Metabolic Rate Function, as well as Epstein’s Function. By using these algorithms, results were obtained that reflected each trails’ distance, estimated travel time, and energy expenditure, which were then subsequently used to grade the trails. Fieldwork data, as well as Volunteered Geographic Information were used to verify the modelled results. Lastly, these results were disseminated through infographics, hardcopy maps, and an online resource. This study successfully modelled the various relevant physical parameters of each trail, which were subsequently used to assign a difficulty level to each trail. Infographics, hardcopy maps, and an online resource were then created that reflected the relevant information of each trail. These informational products are available to the public, either in hardcopy format available at the nature reserves or via a QR code (printed on the hardcopy maps and/or infographics) that directs them to the online resources. By providing the public with adequate information regarding each nature reserve’s trails, as well as its added amenities, users can now be in a position where they can make more informed decisions, which improves the usability of these areas, as well as incorporates the intentions of SDG 11. Keywords: Epstein’s Function, FAIR data use principles, information accessibility, Modified Hiking Function, Pandolf’s Metabolic Rate Functions, Target 11.7, Volunteered Geographic Information
Linking biophysical models with LiDAR-based vegetation mapping to evaluate thermal refugia at a landscape scale in the Kruger National Park
(University of Pretoria, 2024-01-24) McKechnie, Andrew E.; Greve, Michelle; Conradie, Shannon Rose; Smit, Isak P J; lara.strydom@gmail.com; Strydom, Lara Heleen
Increases in global air temperatures have provided the impetus for extensive research into how thermal constraints impact species behaviour and vulnerability to climate change, with recent heat-related mortality events underscoring the need for such research. The role of vegetation in creating cooler microsites that buffer organisms against high temperatures has received attention in the past, yet few studies have assessed the availability of cool, shaded microsites for small animals at a landscape level. Here, I combined tree canopy height and density values derived from remote sensing (LiDAR) products with biophysical models to predict operative temperatures for black bulbs within tree canopies at a landscape scale in the Kruger National Park, South Africa. The accuracy of the biophysical models was evaluated by comparing the outputs to the operative temperatures (Te) recorded by deploying Te thermometers across the thermal landscape. For most of the trees (64%), Te values predicted by the biophysical models were not significantly different (p > 0.05) to those measured by black bulbs. I mapped values of Te predicted by the biophysical model to quantify thermal refuges potentially available to different-sized model organisms that approximate the size of different bird species, using the canopies while inactive on hot days. My results reveal that exposure to extreme heat events (defined as Te > 40 °C) varies with canopy height and density. Of the subset of trees sampled during this study, Kigelia africana provided the greatest degree of buffering from high temperatures, whereas Combretum hereroense provided the least protection against exposure to high Te. For example, organisms seeking refuge in Kigelia africana can experience ~ 50 fewer days per summer where they are exposed to high daily maximum Te, compared to those making use of exposed sites. Furthermore, tree canopies can reduce the intensity and frequency of animals’ exposure to sustained heat events by up to 10-fold per summer, when compared to exposed microsites. This study demonstrates how combining remote-sensing technology and biophysical models can provide a better understanding of thermal landscapes and inform decisions regarding the vegetation management in protected areas.
Finding the safest paths in Khayelitsha township, Western Cape province, South Africa
(University of Pretoria, 2023) Breetzke, Gregory; u18006273@tuks.co.za; Theron, Kayla
Crime is significant in Khayelitsha, a township located near Cape Town in South Africa. Moreover, residents in Khayelitsha constantly walk to get around the township placing them at increased risk of victimisation during their commute. To address this, three methods were proposed to determine the safest walking routes between two points in Khayelitsha. Method 1 used historical crime incidents to identify high crime streets, Method 2 used the location of ‘risky facilities’ to determine risk while Method 3 used both historical crime and ‘risky facilities’ to evaluate risk along a route. Total walking distance, historical crime incidents, number of risky facilities, or type of risky facilities can each act as pedestrian preferences when selecting a route to walk. Each of these aspects impact the resultant ‘safest’ walking route in Khayelitsha. Future work should test these safe navigation methods in other geographical contexts with alternative modes of transport, crime data and types of facilities. It is encouraged that these methods be included in mobile navigation applications so that residents in Khayelitsha can be advised on the safest walking routes.
A remote sensing-based assessment of gullies along main roads in Emakhazeni, Mpumalanga Province, South Africa
(University of Pretoria, 2023) Loubser, M.J.; Beckedahl, H.R.; marissa26.swart@gmail.com; Swart, Marissa
Soil erosion is a critical problem in the Southern African environment and often manifests through gully erosion. Such gullies are visible in many regions of South Africa. Various factors increase gully development. These may be broadly classified into natural factors (like rainfall characteristics, geology, soil, and hillslope gradient) and anthropogenic (human) factors (like population size and land use management practices). Road construction, an anthropogenic factor, changes the runoff characteristics of the surface by significantly reducing permeability, potentially reducing it to zero. Roads can thus contribute to accelerated soil erosion, frequently manifesting in gully formation at outlets of road culverts, where runoff concentration is maximised. This study investigated whether it is possible to assess gully characteristics remotely. Gullies adjacent to national or regional armoured (tarred/paved) roads of the Emakhazeni Local Municipality of South Africa’s Mpumalanga Province were identified on Google EarthTM. Gullies were further digitised on Google EarthTM, sampled, and checked against field data to indicate if the two sets of data demonstrate similarities (i.e., ground-truthing). Gullies were sparsely distributed but tend to be more located on the R540 motorway between eMakhazeni and Dullstroom as well as the R33 motorway between eMakhazeni and Carolina. The approximate volume of material excavated from each gully was calculated. The average overall volume of gullies in the study area is 24,04 m3. Data collection took place between 15 March 2022 and 12 June 2022. Rainfall data for the past 30 years were collected from weather stations owned by Agricultural Research Council (ARC) and the South African Weather Service (SAWS) in the study area. The hillslope gradient was determined from Digital Elevation Models (DEMs) and compared against field data. Furthermore, the aerial extent (surface area) of gullies calculated using LiDAR (overall average of 173,68 m2) and Google EarthTM imagery (overall average of 65,18 m2) were also assessed. Statistical analyses were done with the computer language “R” in R-studio. This study found that gullies of the type investigated cannot be readily identified on Google EarthTM due to the identification of false positives and that ground truthing is essential. Google EarthTM could, however, be used to measure the aerial extent of gullies. The hillslope gradient of gullies could also not be measured accurately using a DEM possibly because an even finer spatial resolution DEM is required for the size gullies studied. Furthermore, it was found that rainfall gauges ought to be installed at the gullies itself when assessing the gullies to obtain more accurate data. Finally, it was also found that LiDAR cannot be used to measure the excavated volume of gullies. Using proper LiDAR equipment (such as the Leica BLK 360 Mark 1 LiDAR device) and assessing a greater number of gullies using LiDAR might, however, change this finding.
Rock weathering and ultrasonic pulse velocity : an analysis using South African cemeteries as time-series laboratories
(University of Pretoria, 2023) Bumby, Adam; Sumner, Paul Douglas; michael.loubser@up.ac.za; Loubser, Michael John
The study of rock weathering poses unique challenges due to the operation of weathering processes on small spatial and large temporal scales. Many, although not all, studies that focus on a specific weathering process tend to confine themselves to regional climates in which the processes are expected to function most efficiently; for example, thermal weathering studies tend to take place predominantly in arid or polar regions and many chemical weathering studies are in tropical regions. The aim of this study is to develop and assess an experimental measurement technique for the quantification of weathering in different regions. This technique, which makes use of state of the art ultrasonic technology, can potentially be used to quantify weathering rates in a manner that allows results to be compared for different environmental or climatic regions. Ultrasonic Pulse Velocity (UPV) measurements were recorded in six cemeteries at different locations across South Africa using a variety of field measurement protocols and apparatus configurations. The results show that rock weathering can be assessed in this way, but the weathering signal is extremely small. This method thus requires a high degree of measurement precision from the field operator when data are being gathered. Overall, the results show that climate does exert a general influence on the weathering regime of a specific region, but that the rock properties of any specific tombstone can cause weathering to occur very differently to what may be regarded as typical for a region. The specific weathering regime for a given area is, therefore, not determined by either climatic forcings or rock properties, but rather is the result of tension between these two elements, the nature of which will be unique to each regional environment.
The human dimensions of restoring degraded forests and lands : case of Cameroon
(University of Pretoria, 2023) Nsubuga, F.W.N. (Francis Wasswa Nkugwa); Chirwa, Paxie W.; lohchia@gmail.com; Chia, Eugene Loh
Forest and land degradation are persistent and are perceived as global problems whose impacts are felt at multiple levels in terms of food insecurity, livelihoods, and biodiversity loss. In response, efforts to restore degraded forests and lands is gaining momentum at the global and regional levels through ambitious commitments. However, the challenge is to translate these commitments to concrete large-scale actions on the ground. Many countries are currently developing national and subnational strategies and plans for forest and land restoration. Understanding the human dimension of restoration, which has been recently dominated by ecological dimension assessments is important for strategic planning. Therefore, the objective of this study was to assess the human dimension of forest and land restoration in Cameroon with the view to generating knowledge and information to inform policymakers, practitioners and local communities, involved in restoration. The study employed a mix of qualitative and quantitative research methods in the data collection and analysis process. The whole study was guided by two conceptual sets of thinking – the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) and the Human dimension frameworks. Data for the study were collected from the tree-growing restoration policy process at the national level and from tree-growing restoration activities at the landscape and farm levels. The study dealt with the policy level factors relevant for enhancing tree-growing restoration actions (Chapters 3 and 4), farm level tree-growing decision-making drivers and behavioural persistence (Chapters 5 and 6) and the diverse viewpoints of restoration stakeholders regarding strengths, weaknesses, threats, interests, and priorities (Chapter 7). The study found that the policy and governance related conditions are currently weak and insufficient to enable large-scale restoration and efforts towards improving these conditions have been insufficient. A strong political will is required to improve these conditions. The provision of tree-growing incentives, a key policy instrument for enhancing restoration needs to build on key good governance features such as accountability, transparency, monitoring and performance evaluation, collaboration, and coordination. Farmers decisions to involve in tree-growing restoration practices were influenced by a combination of socio-economic and biophysical factors. Furthermore, farmers decision to continue restoration practices on their farm plots after the end of support programs were influenced by a mix of factors, among which positive attitude and perception of farmers, constant motivation, financial profitability, community influence, played an important role. The design and implementation of restoration plans, and programs needs to take into consideration the lessons from past tree-growing restoration efforts where - source of additional income for families, tenure insecurity, improvement of livelihoods and natural resource base of communities and inadequate supply of quality inputs for restoration emerged as key factors in terms of strength, weakness, opportunity, and threat respectively. The study concludes that factors that influence the role of human actions in tree-growing restoration practices are crucial to support large-scale restoration endeavours and the achievement of national and international restoration objectives.

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