Research Articles (Geography, Geoinformatics and Meteorology)

Permanent URI for this collectionhttp://hdl.handle.net/2263/1936

A collection containing some of the full text peer-reviewed/ refereed articles published by researchers from the Department of Geography

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Skin cancer prevention and sunscreens
(BMJ Publishing Group, 2025-07) Nicholson, Anna; Abbott, Rachel; Wright, Caradee Yael; Kamali, Perdy; Sinclair, Craig
A parent visits their general practitioner with their 1 year old child, who is due to receive several vaccinations. During the appointment, the parent asks whether it is OK to start using infant sunscreen formulations, as they have heard there is a risk that sunscreens can be unsafe for infants, and that they can cause skin reactions. You observe that the infant has fair skin. The parent notes their child has sensitive skin, which is easily irritated, and asks for your recommendation. WHAT YOU NEED TO KNOW • The global burden of disease from melanoma is high and increasing; it occurs predominantly as a result of exposure to ultraviolet (UV) radiation (from sunlight or sunbeds) most commonly in people with fair, sun sensitive skin. • The World Health Organization recommends sun protection measures when the UV index is forecast to reach 3 and above. • Regular use of sunscreen can prevent melanoma and squamous cell carcinoma; however, the effectiveness of sunscreen is dependent on the amount applied, coverage of exposed skin, and reapplication. • Opportunistic behavioural counselling from healthcare professionals can increase sun protection behaviours and is recommended for parents of young children, adolescents, and groups at high risk. • Tailor sun protection recommendations to individual risk factors, considering skin pigmentation, concurrent risk of vitamin D deficiency, immune system status, and UV radiation exposure.
Camera trap-based estimates reveal spatial variability in African clawless otter population densities and behaviour
(Cambridge University Press, 2025) Lewis, Candice B.; Majelantle, Tshepiso Lesedi; Haussmann, Natalie S.; Mcintyre, Trevor
Estimating the population size of shy and elusive species is challenging but necessary to inform appropriate conservation actions for threatened or declining species. Using camera-trap surveys conducted during 2017–2021, we estimated and compared African clawless otter Aonyx capensis population densities and activity times in six conserved areas in southern Africa. We used two different models to estimate densities: random encounter models and camera-trap distance sampling. Our results highlight a general pattern of higher estimated densities and narrower confidence intervals using random encounter models compared to camera-trap distance sampling. We found substantial variation in densities between study areas, with random encounter model estimates ranging between 0.9 and 4.2 otters/km2. Our camera-trap distance sampling estimates supported the relative density estimates obtained from random encounter models but were generally lower and more variable, ranging from 0.8 to 4.0 otters/km2. We found significant differences in otter activity patterns, with populations either being nocturnal, mostly nocturnal or cathemeral. As all study areas experience little human disturbance, our results suggest that there are large natural variations in otter densities and activity patterns between regions. When densities are converted to metrics that are comparable to previous studies, our estimates suggest that African clawless otter population numbers are generally lower than previously reported. This highlights a need for broader spatial coverage of otter population assessments and future studies to assess potential environmental drivers of spatial, and potentially temporal, variation in population numbers and activity patterns.
SCALE-up - a new framework to assess the effectiveness of climate change adaptation interventions for human health and health systems
(BioMed Central, 2025-07) Wright, Caradee Yael; Naidoo, Natasha; Anand, Nalini; Kapwata, Thandi; Webster, Candice
Climate change is a grave threat to human health and wellbeing. Adaptation is one mechanism (the other is mitigation) by which we can intervene to increase adaptive capacity and preparedness to protect people. Adaptation interventions (evidence-based adjustment of programs/practices that lead to improved response and resilience to climate change) are being conducted around the world. However, existing conceptual frameworks to assess the effectiveness of these interventions, especially with respect to improving health outcomes and systems are not readily applied in areas where these are needed. This is applicable to both interventions intended to improve health as well as those without a health-focus but which may have health co-benefits. To address this gap, we conducted a multi-vocal review comprised of a scoping review and key informant interviews, which informed the development of an initial assessment framework. We included 21 academic articles and 12 reports (from the grey literature) for data collation and synthesis. Of the 21 articles analyzed, only seven presented primary evidence of health improvement outcomes, such as reduction in neo-natal care unit admissions was partially attributed to moving the maternity ward to the cooler, lower floor of the hospital. From the 10 interviewees, we learnt that most existing tools to assess the effectiveness of adaptation are for country or regional (several countries sharing borders within a large section of a continent) scales (e.g., Notre Dame Global Adaptation Initiative Index) and none focused specifically on health / health co-benefits. From these learnings together with a guiding concept, we crafted the first iteration of an assessment framework, SCALE-up, comprising six steps that prompt a researcher to consider the effectiveness of their adaptation intervention at a project-scale, including from a health benefit perspective. We apply the framework in four scenarios: hot days-heat; floods; droughts; and vector-borne diseases, to illustrate how the framework may help guide the researcher to think about effectiveness from project proposal stage. The next steps are to implement and pilot the framework in the four proposed scenarios and refine the framework.
Sustainability of the linkages between water-energy-food resources based on structural equation modeling under changing climate : a case study of Narok County (Kenya) and Vhembe district municipality (South Africa)
(MDPI, 2024-11-07) Zwane, Nosipho Ntombani; Botai, Joel Ongego; Botai, Christina M.; Mabhaudhi, Tafadzwanashe
Due to the current and predicted increase in the global demand for water–energy–food (WEF) resources, as well as the inevitable linkages between the WEF sectors and sustainable development, the WEF nexus is rapidly being recognized as a method to effectively manage sustainable development. Many African countries still face challenges in terms of the demand for and accessibility of WEF resources. For this reason, a comparative study of two sites (Narok County and Vhembe District Municipality), which exhibit similar socio-economic, environmental, and technological circumstances, was undertaken. In the present study, we considered 218 questionnaire responses, which we analyzed using partial least squares structural equation modeling (SEM) based on the WEF nexus constructs. This study is anchored on the null hypothesis (H0), whereby no interdependencies exist between the state of the climate and WEF resources, as constrained by sustainable development options. The results show that the proposed hypothesis does not hold, but rather, an alternative hypothesis (Ha)—there exist linkages between climate change and WEF resources—holds. This is demonstrated by the descriptive statistics indicating p values < 0.05 for both the t-test and the Bartlett test. Furthermore, analysis from the multi-regression, particularly for the model where we combined the sites, showed p values < 0.05 and higher adjusted r-squared values, which denoted a better fit. The communities in both study sites agree that the regions have experienced a scarcity of WEF resources due to climate change. The results show that climate change is an intrinsic part of the developmental options for the sustainable livelihood of both study sites, which aligns with the 2030 UN agenda on sustainable development goals targets. Moreover, the sustainable management of natural resources that are people- and planet-centric is crucial to climate change adaptation and mitigation, social justice, equity, and inclusion. The SEM results showed with significant confidence that the water, energy, and food sectors are closely interconnected; however, their impact on climate and sustainability is significantly different. Food has a direct positive impact on climate and sustainability, while both water and energy have an indirect negative impact. Moreover, the climate construct indicated a significant direct link to sustainability for all the relationships explored. This is particularly true because, in most underdeveloped countries, sustainable development and societal wellbeing heavily rely on goods and services derived from natural resources and the environment. This study contributes to the nexus modeling research field by introducing SEM as an innovative methodology over a single equation modeling framework in analyzing variables that have complex interrelationships, facilitating advanced WEF nexus resource governance.
The impact of climate change on agricultural nonpoint source pollution in the Sand River Catchment, Limpopo, South Africa
(MDPI, 2025-06) Chuene, Tlhogonolofatso A.; Akanbi, Remilekun Temitope; Chikoore, Hector
Understanding the impact of climate change on agricultural nonpoint source (NPS) pollution is crucial for developing effective adaptation strategies and reducing vulnerabilities where such challenges exist. This study evaluated the impact of precipitation and temperature variations on Total Inorganic Nitrogen (TIN), Total Inorganic Phosphorus (TIP), and sediment loads in the Sand River Catchment (SRC) using the Soil and Water Assessment Tool plus (SWAT+). One-way analysis of variance (ANOVA) was used to determine the significance (p < 0.05) of the relationships (R2) between precipitation and temperature on sediment, TIN, and TIP loads in the SRC. SWAT+ calibration and validation demonstrated that the statistical indices (NSE and R2 ≥ 0.72; −17.30 ≤ PBIAS ≤ 14.74) fell within an acceptable range. Results indicated a significant influence of average monthly precipitation (p < 0.0001) and temperature (p ≤ 0.004) on sediment, TIN, and TIP loads. In addition, a decrease in average annual precipitation led to a decline in sediment, TIN, and TIP loads (R2 ≥ 0.55), with the average annual temperature increasing in the same period (R2 ≤ 0.23). This study confirms that climate change contributes to agricultural NPS pollution in the SRC and highlights the need to employ suitable adaptation strategies for pollution control in the catchment.
Analysis of the projected climate impacts on the interlinkages of water, energy, and food nexus resources in Narok County, Kenya, and Vhembe District Municipality, South Africa
(MDPI, 2025-05) Zwane, Nosipho Ntombani; Botai, Joel Ongego; Nozwane, Siyabonga H.; Jabe, Aphinda; Botai, Christina M.; Dlamini, Lucky; Nhamo, Luxon; Mpandeli, Sylvester; Petja, Brilliant; Isaac, Motochi; Mabhaudhi, Tafadzwanashe
The current changing climate requires the development of water–energy–food (WEF) nexus-oriented systems capable of mainstreaming climate-smart innovations into resource management. This study demonstrates the cross-sectoral impacts of climate change on interlinked sectors of water, energy, and food in Narok County, Kenya, and Vhembe District, South Africa. This study used projected hydroclimatic extremes across past, present, and future scenarios to examine potential effects on the availability and accessibility of these essential resources. The projected temperature and rainfall are based on nine dynamically downscaled Coupled Model Intercomparison Project Phase 5 (CMIP 5) of the Global Climate Models (GCMs). The model outputs were derived from two IPCC “Representative Concentration Pathways (RCPs)’’, the RCP 4.5 “moderate scenario”, and RCP 8.5 “business as usual scenario”, also defined as the addition of 4.5 W/m2 and 8.5 W/m2 radiative forcing in the atmosphere, respectively, by the year 2100. For the climate change projections, outputs from the historical period (1976–2005) and projected time intervals spanning the near future, defined as the period starting from 2036 to 2065, and the far future, spanning from 2066 to 2095, were considered. An ensemble model to increase the skill, reliability, and consistency of output was formulated from the nine models. The statistical bias correction based on quantile mapping using seven ground-based observation data from the South African Weather Services (SAWS) for Limpopo province and nine ground-based observation data acquired from the Trans-African Hydro-Meteorological Observatory (TAHMO) for Narok were used to correct the systematic biases. Results indicate downscaled climate change scenarios and integrate a modelling framework designed to depict the perceptions of future climate change impacts on communities based on questionnaires and first-hand accounts. Furthermore, the analysis points to concerted efforts of multi-stakeholder engagement, the access and use of technology, understanding the changing business environment, integrated government and private sector partnerships, and the co-development of community resilience options, including climate change adaptation and mitigation in the changing climate. The conceptual climate and WEF resource modelling framework confirmed that future climate change will have noticeable interlinked impacts on WEF resources that will impact the livelihoods of vulnerable communities. Building the resilience of communities can be achieved through transformative WEF nexus solutions that are inclusive, sustainable, equitable, and balance adaptation and mitigation goals to ensure a just and sustainable future for all.
Ecohydrological differences in peatlands under contrasting land use management systems in Eswatini
(Springer, 2025-06) Ndlela, Thandeka; Beckedahl, Heinz; Grundling, Piet-Louis; Glatzel, Stephan; Butler, Mike; u11264889@tuks.co.za
Peatlands are vital ecosystems that regulate water flow, sequester carbon and support biodiversity. They are indispensable to many rural communities in southern Africa, providing essential ecosystem goods and services. However, their ecohydrological balance is vulnerable to both anthropogenic and natural disturbances. This study compares two peatlands in Eswatini, Malolotja (within a protected area) and Motjane (a community-managed site), to assess differences in peat stratigraphy, ecohydrological dynamics and water chemistry. By utilising groundwater wells, piezometers, stable isotope ratios and hydrochemical analyses across multiple transects, the study evaluates how land use, geomorphology and site history influence peatland ecohydrological functioning under similar climatic conditions. Findings indicate that Motjane, affected by drainage and grazing, experiences greater peat decomposition, fluctuating water tables and hydrochemical signs of disturbance. In contrast, Malolotja maintains a more stable water table and shows less peat degradation. Despite the contrasting land use contexts, both peatlands are primarily sustained by groundwater inputs, highlighting the critical role of subsurface hydrology in maintaining peatland function under pressure. The findings contribute towards understanding the complex interactions driving peatland ecohydrology and offer insights for targeted restoration and conservation strategies in Eswatini and the broader southern African region.
“Our struggle with addressing in South Africa” – capturing public stakeholder perspectives
(Academy of Science of South Africa, 2025-05) Laldaparsad, Sharthi; Davis, Nerhene; Coetzee, Serena Martha
Addresses are important for socio-economic gains and good governance in cities and municipalities. However, some countries, including South Africa, experience deficiencies in their address infrastructure. As a result, stakeholders who need addresses and address data to perform their respective mandates need to manoeuvre to find workarounds to overcome these deficiencies. In this paper, we explore the challenges and responses within the South African address infrastructure from the vantage point of governance stakeholders. Findings from semi-structured interviews reveal ambiguity about the need for addressing and uncertainty about its implementation. Adaptive strategies are deployed to overcome governance deficiencies, but these come at a significant cost. To resolve the struggle for an address infrastructure in South Africa, a congruent and coordinated governance approach informed by clear definitions, mandates and responsibilities is recommended. This study represents the first of its kind in capturing insiders’ perspectives on governance-related challenges from the vantage point of addressing stakeholders. The improved understanding of addressing governance challenges paves the way for further research into a transformative way forward for addressing in the country. SIGNIFICANCE : This deeper understanding of the governance challenges in the struggle for an effective and efficient address infrastructure in South Africa can inform the way forward to a congruent and coordinated governance framework based on clear mandates and responsibilities.
Quantifying informal public transport using GPS data
(Elsevier, 2025-10) De Beer, Lourens Retief; Venter, Christoffel Jacobus; Snyman, Lourens Fourie; lourens.snyman@up.ac.za
Informal public transport modes transport the largest number of passengers in most developing countries. Despite its significance, limited information is available on the extent of its operations, and passenger counts alone do not provide sufficient insight into network coverage or passenger turnover. GPS tracking has emerged as a valuable tool, yet its potential for understanding minibus taxi operations at the road segment level remains underexplored. GPS studies of informal operators have rarely been extrapolated to volume counts per time period, due to statistical problems (non-representative sampling) and small sample sizes. This paper addresses this gap by developing a methodology to determine the minibus taxi vehicle trip count per street segment from GPS data, to map routes, and identify high-traffic corridors, with an illustrative application in the City of Tshwane, South Africa. The methodology includes data inspection, addressing limitations, and counting trips per street segment using a database and QGIS visualisation. Additionally, the paper outlines detailed steps in QGIS for processing GPS data. We show that the method delivers plausible results at the segment level. The methodology can help to address the global South's need for data-driven interventions in its predominant public transport mode.
Research progress in the application of Google Earth engine for grasslands based on a bibliometric analysis
(MDPI, 2024-06) Mashaba-Munghemezulu, Zinhle; Nduku, Lwandile; Munghemezulu, Cilence; Chirima, Johannes George
Grasslands cover approximately 40% of the Earth’s surface. Thus, they play a pivotal role in supporting biodiversity, ecosystem services, and human livelihoods. These ecosystems provide crucial habitats for specialized plant and animal species, act as carbon sinks to mitigate climate change, and are vital for agriculture and pastoralism. However, grasslands face ongoing threats from certain factors, like land use changes, overgrazing, and climate change. Geospatial technologies have become indispensable to manage and protect these valuable ecosystems. This review focuses on the application of Google Earth Engine (GEE) in grasslands. The study presents a bibliometric analysis of research conducted between 2016–2023. Findings from the analysis reveal a significant growth in the use of GEE and different remote sensing products for grassland studies. Most authors reported grassland degradation in most countries. Additionally, China leads in research contributions, followed by the United States and Brazil. However, the analysis highlights the need for greater involvement from developing countries, particularly in Africa. Furthermore, it highlights the global distribution of research efforts, emphasizes the need for broader international participation.
Evaluation of rainfall distribution based on the Precipitation Concentration Index : a case study over the selected summer rainfall regions of South Africa
(MDPI, 2025-06) Botai, Christina M.; Botai, Joel Ongego; Mukhawana, Mxolisi B.; De Wit, Jaco; Masilela, Ndumiso S.; Zwane, Nosipho Ntombani; Tazvinga, Henerica
The Precipitation Concentration Index (PCI) is considered a powerful tool that can be used to analyse the spatial and temporal distribution and variability of precipitation over a region. It plays a significant role in planning and managing water resources, including monitoring and forecasting drought and flood risks. As such, the present study used the PCI to investigate the spatio-temporal distribution of precipitation in summer rainfall regions covering six selected South African provinces. Specifically, this study analysed monthly precipitation data from 49 rainfall districts spanning from 1979 to 2023 and assessed the spatio-temporal variability patterns of annual, seasonal and supra-seasonal PCI values and their trends based on the Mann–Kendall trend test. Pearson’s correlation was used to evaluate the relationship between the PCI values and precipitation across the provinces. Moderate annual PCI values were observed mainly in KwaZulu-Natal and the eastern regions of the Free State and Mpumalanga provinces. A large portion of the study site exhibited irregular annual precipitation concentrations. The PCI decreased by −1.5 and −1.2 magnitudes of change during 1979–1989 and 2000–2011 and increased by 2.1 and 2.8 magnitudes between 1990–2000 and 2012–2023, respectively. Uniform precipitation concentration was mostly recorded during the December–January–February (DJF) season. The entire study area recorded moderate precipitation concentration during the March–April–May (MAM) and September–October–November (SON) seasons (with exceptions for KwaZulu-Natal (KZN)). In addition, irregular precipitation concentration dominated during the June–July–August (JJA) rainy season. All provinces except KZN recorded positive trends in annual PCI. Also, positive trends in PCI were observed during the supra-wet season across the provinces, except KZN and in parts of the Free State. Furthermore, negative trends in seasonal PCI were mostly dominant during DJF and MAM, while positive trends were mostly observed during SON and JJA rainy seasons. The annual PCI values were positively correlated with annual precipitation in KZN, Free State and Limpopo, while negative correlations were observed in Mpumalanga and North West provinces. The results presented in this study contribute to drought and flood monitoring in support of water resource management and planning.
Geospatial data quality training for the South African spatial data infrastructure - lessons learnt from training geospatial data custodians
(CONSAS Conference, 2025-02) Cooper, Antony Kyle; Fourie, Nicolene; Coetzee, Serena Martha; Blom, Marinet; Chauke, Maroale; Ndlovu, Vutomi
Standards play an important role in achieving the objectives of a spatial data infrastructure. However, standards can be difficult to understand and implement for those with limited exposure to them. The South African Spatial Data Infrastructure (SASDI) aims to facilitate the capture, management, maintenance, integration, distribution and use of spatial information. To decide whether a SASDI data set is fit for a specific purpose, users need information about its quality. SANS 19157:2014, Geographic information – Data quality, specifies how the quality of geospatial data can be described and assessed. The Committee for Spatial Information (CSI), responsible for implementing SASDI, identified the need to train geospatial data custodians in implementing SANS 19157. While custodians were eager to learn, several barriers prohibited presentation of training in a ‘traditional’ classroom setting. These barriers included the costs and time to travel from remote areas of the country to a training venue and challenges with scheduling the training at a time suitable to all participants. Online training was therefore delivered − however, structured in a way to overcome general ‘online fatigue’ after the pandemic. In this paper we present our experiences in presenting training on SANS 19157 to professionals responsible for geospatial data sets. We also share the lessons learnt from the novel structure for online training.
Achieving the global biodiversity framework under climate change
(Wiley, 2025-05) Archer, Emma Rosa Mary; Arneth, Almut; Leadleay, Paul; Mori, Akira; Obura, David; Smith, Pete; emma.archer@up.ac.za
We have committed to ambitious targets under the Global Biodiversity Framework, but projected climate change makes the achievement of many of these targets extremely difficult and will effectively require a significant rethinking in how to achieve multiple targets. In this Opinion, we have chosen to focus on selected targets, considering how their achievement is likely to be compromised by climate change but also what the possibility of real response options might be. We focus on restoration (Target 2), spatial planning and integration (Targets 1, 2, 3 and 10), sustainable use and sustainable benefits to people (Targets 5, 9 and 10) and, finally, equity and social justice (Targets 13, 20–23 and Goal C). Now more than ever, the window for effective action on climate change and biodiversity is closing, requiring rapid and, most importantly, collective action.
Suburban transformation in post-apartheid South Africa : socio-economic mobility and neighbourhood change in ‘in-between’ spaces
(Publikon Kiadó, 2024) Sekonyela, Boniswa Kelebogile; Gregory, James J.; Rogerson, Jayne M.; jj.gregory@up.ac.za
Since democratic change in 1994 South Africa’s cities have experienced major physical and social changes. Johannesburg, South Africa’s major city, has been at the leading edge of the changes occurring in the landscape of the country’s cities and therefore has generated a substantial scholarly literature. Geographical writings are concentrated mainly on the inner-cities and townships. Less research has been pursued on South Africa’s suburban spaces and particularly in what has been described as the ‘in-between’ middle-class suburban areas. The objective in this article is to investigate the dynamics of suburban transformation in post-apartheid South Africa. The case study is situated in the south of Johannesburg and centres on neighbourhood change in former ‘white’ designated suburbs. The study discloses resident motivations driving change, issues of socio-economic mobility, and the shifts occurring in the nature of residential property development in these spaces.
Comparison of machine learning and statistical approaches for digital elevation Mmodel (DEM) correction : interim results
(International Society of Photogrammetry and Remote Sensing, 2024-06) Okolie, Chukwuma; Adeleke, Adedayo; Smit, Julian; Mills, Jon; Maduako, Iyke; Ogbeta, Caleb; adedayo.adeleke@up.ac.za
The correction of digital elevation models (DEMs) can be achieved using a variety of techniques. Machine learning and statistical methods are broadly applicable to a variety of DEM correction case studies in different landscapes. However, a literature survey did not reveal any research that compared the effectiveness or performance of both methods. In this study, we comparatively evaluate three gradient boosted decision trees (XGBoost, LightGBM and CatBoost) and multiple linear regression for the correction of two publicly available global DEMs: Copernicus GLO-30 and ALOS World 3D (AW3D) in Cape Town, South Africa. The training datasets are comprised of eleven predictor variables including elevation, slope, aspect, surface roughness, topographic position index, terrain ruggedness index, terrain surface texture, vector ruggedness measure, percentage bare ground, urban footprints and percentage forest cover as an indicator of the overland forest distribution. The target variable (elevation error) was derived with respect to highly accurate airborne LiDAR. The results presented in this study represent urban/industrial and grassland/shrubland/dense bush landscapes. Although the accuracy of the original DEMs had been degraded by several anomalies, the corrections improved the vertical accuracy across vast areas of the landscape. In the urban/industrial and grassland/shrubland landscapes, the reduction in the root mean square error (RMSE) of the original AW3D DEM was greater than 70%, after correction. The corrections improved the accuracy of Copernicus DEM, e.g., > 44% RMSE reduction in the urban area and >32% RMSE reduction in the grassland/shrubland landscape. Generally, the gradient boosted decision trees outperformed multiple linear regression in most of the tests.
Paired eddy covariance site reveals consistent net C sinks over three growing seasons in an African arid and grassy shrubland
(Elsevier, 2025-09) Maluleke, Amukelani; Feig, Gregor Timothy; Brümmer, Christian; Jaars, Kerneels; Hamilton, Tamryn; Midgley, Guy
Please read abstract in the article. HIGHLIGHTS • African arid and grassy shrubland site reveals consistent net C sinks over three growing seasons. • Savanna site more productive but has lower and more variable water use efficiency than Nama-Karoo site. • Soil moisture observed as a key factor in modulating the relationship between nighttime respiration and soil temperature at both sites.
Suitable sites for fog water collection in Cape Town, South Africa
(Springer, 2025-04) Adeleke, Adedayo; Mnikathi, Sandile; adedayo.adeleke@up.ac.za
The worldwide shortage of fresh water is a critical issue, with two-thirds of the world’s freshwater being inaccessible, as it is locked up in frozen glaciers. Additionally, arid areas such as South Africa are experiencing increased water scarcity, with regions such as Cape Town having already announced “day zero”, the day when the city’s dams will run out of water. Fog water collection provides a sustainable and alternative source of fresh water. Nevertheless, existing methods for identifying suitable locations rely on manual and trial-based approaches. This study focuses on finding suitable locations for fog harvesting in Cape Town via geographic information system (GIS)-based multicriteria decision analysis. To accomplish this, relevant factors for fog harvesting were identified in the literature and then transformed into spatial data layers. Next, weights were assigned to criteria layers via the analytical hierarchy process method, ultimately creating a final suitability map through a weighted overlay of these criteria layers. The findings of this study indicated that regions near coastlines, with low temperatures and strong winds, elevations above 1000 m or below 200 m, and steep slopes facing the ocean are the most favourable locations for harvesting fog water. This approach could be replicated in other regions, but caution is necessary when determining criteria and thresholds because of the localised nature of fog.
A refreshing take on the inverted Dirichlet via a mode parameterization with some statistical illustrations
(Springer, 2025-03) Otto, Arno F.; Ferreira, Johannes Theodorus; Bekker, Andriette, 1958-; Punzo, A.; Tomarchio, S.D.; arno.otto@up.ac.za
The inverted Dirichlet (IDir) distribution is a popular choice for modeling multivariate data with positive support; however, its conventional parameterization can be challenging to interpret. In this paper, we propose a refreshing take on the IDir distribution through a convenient mode-based parameterization, resulting in the mode-reparameterized IDir (mIDir). This new parameterization aims to enhance the use of the IDir in various contexts. We provide relevant statistical illustrations in robust and nonparametric statistics, model-based clustering, and semiparametric density estimation, all benefiting from this novel perspective on the IDir for computation and implementation. First, we define finite mIDir mixtures for clustering and semiparametric density estimation. Secondly, we introduce a smoother based on mIDir kernels, which, by design, avoids allocating probability mass to unrealistic negative values, thereby addressing the boundary bias issue. Thirdly, we introduce a heavy-tailed generalization of the mIDir distribution, referred to as the contaminated mIDir (cmIDir), which effectively handles and detects mild outliers, making it suitable for robust statistics. Maximum likelihood estimates of the parameters for the parametric models are obtained using a developed EM algorithm as well as direct numerical optimization. A parameter recovery analysis demonstrates the successful application of the estimation method, while a sensitivity analysis examines the impact of mild outliers on both the mIDir and cmIDir models. The flexibility and advantages of the proposed mIDir-based models are showcased through several real data analyses and illustrations.
A web-based decision support tool for multifarious renewable energy systems
(Elsevier, 2025-09) Ramafikeng, Montseng; Ajayi, Oluibukun; Adeleke, Adedayo; adedayo.adeleke@up.ac.za
Current global electricity demand is unprecedented, and it has perpetuated severe energy shortages and an increased reliance on and use of unsustainable non-renewable sources, particularly in countries across Africa. In South Africa, the growing energy demand, coupled with ageing coal-based electricity infrastructure, has fuelled interest, discourses, and research on the potential use of renewable energy. Therefore, this study aimed to use Geographic Information Systems (GIS) and Remote Sensing techniques to create a web-based interactive decision-making tool to measure and assess the availability and potential of wind, solar, and biomass energy sources, as well as to identify the most suitable sites for wind farms in the Atlantis area of South Africa’s Western Cape. This was achieved by implementing a map mashup using JavaScript and Hypertext Mark-up Language (HTML) to retrieve information about wind, solar, and biomass potential together with suitable areas to locate wind farms. The maximum solar radiation received by rooftops was approximately 1499 kWh/m2, which could potentially generate 287.9 kilowatts of electricity using a solar panel efficiency of 15% and a performance ratio of 86%. Similarly, the urban wind energy potential via building-integrated wind turbines was 102.3 kilowatts, utilising a nominal power of 10% and a minimum area of 24m2. Additionally, the biomass estimation was around 586.4 Mg/ha, potentially generating 7.5 kilowatts of electricity using a conversion efficiency of 20% and a heating value of 4.5. Consequently, the web-based platform provides a one-stop resource for investors, planners, and policymakers to access and make well-informed decisions about multifarious renewable energy potentials.
Evaluation of GEDI footprint level biomass models in Southern African Savannas using airborne LiDAR and field measurements
(Elsevier, 2024-12) Li, Xiaoxuan; Wessels, Konrad; Armston, John; Duncanson, Laura; Urbazaev, Mikhail; Naidoo, Laven; Mathieu, Renaud; Main, Russell
Savannas cover more than 20% of the Earth and account for the third largest stock of global aboveground biomass yet estimates of their above ground biomass density (AGBD) are very inaccurate. The Global Ecosystem Dynamic Investigation (GEDI) sensor provides near-global full-waveform LiDAR data with 25 m footprints, from which various structural metrics are derived that are used to predict footprint level AGBD. The current GEDI L4A AGBD product uses a comprehensive Forest Structure and Biomass Database (FSBD) to develop models for specific plant functional types and geographic regions, but southern African savannas have been underrepresented in the reference data. The objectives of this study were to (i) validate GEDI L4A AGBD in South African savannas using field measurements and ALS datasets and (ii) develop and evaluate local GEDI footprint-level AGBD estimates from multiple L2A and L2B metrics. The local GEDI AGBD models outperformed GEDI L4A AGBD (R2 = 0.42, RMSE = 12 Mg/ha, %RMSE = 79.5%) with higher R2 and smaller error measures. The local GEDI AGBD using a random forest model (RF) had the highest R2 of 0.71 and lowest %RMSE of 53.3%, while the generalized linear model (GLM) results provided the lowest Relative Mean Systematic Deviation (RMSD) of 9.2%, which was half that of RF model. L4A significantly underestimated AGBD with an RMSD up to − 37%. This highlights the importance and benefits of local calibration of biomass models to unlock the full potential of GEDI metrics for estimating AGBD. The field and ALS data have subsequently been contributed to the GEDI FSBD and should be used in calibration of future versions of GEDI L4A AGBD product. This research paves the way for the integration of the local GEDI AGBD estimates with other sensors, notable the eminent NISAR mission,

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