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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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,
Standing vegetation and seed bank patterns paint a bleak picture for urban grassland restoration
(Springer, 2025-04) Malherbe, Misha; Le Roux, Peter Christiaan; Haussmann, Natalie S.; peter.leroux@up.ac.za
Urbanisation and urban sprawl are major drivers of global habitat transformation and biodiversity loss. Natural vegetation in urban areas is confined to remnant patches and, as a result, the conservation of these patches of vegetation is becoming increasingly important for biodiversity conservation. Globally grasslands experience high rates of transformation and are threatened by expanding urban areas, causing fragmentation, and facilitating the spread of invasive species. This study explores how above- and belowground vegetation communities within remnant grassland patches vary as a function of patch connectivity and patch size in the City of Tshwane, Gauteng, South Africa. We sampled twelve sites from eleven nature reserves within Tshwane to investigate the relationships between urbanisation and vegetation characteristics. Tshwane’s grassland patches have high levels of invasion, with alien species making up a considerable portion of both standing (13% richness and a third of cover) and seed bank vegetation (31% richness and 26% abundance). Furthermore, we found low similarity between standing vegetation and the seed bank (mean ± SD = 0.25 ± 0.06). Neither road density nor reserve size were related to the total cover or richness of vascular plants, nor the cover or richness of alien species. Similarly, neither variable predicted above-belowground similarity. This suggests that the connectivity of remnant grassland patches does not have any significant effect on vegetation characteristics in this disturbed urban environment. Our results indicate that restoration relying only on natural revegetation from the seed bank is unlikely to be effective and we suggest that active restoration interventions, such as reseeding and invasive species control, may be needed to restore these grasslands and improve their long-term conservation value.
Exposure to outdoor aerospora and associated respiratory health risks among adults in Potchefstroom, North-West province, South Africa
(Frontiers Media, 2025-04) Gharbi, Dorra; Neumann, Frank Harald; Podile, Keneilwe; Mcdonald, Marinda; Linde, Jo-hanne; Frampton, Megan; Liebenberg, Jennifer Leigh; Cilliers, Sarel; Mmatladi, Tshiamo; Nkosi, Phumelele; Paledi, Keamogestswe; Piketh, Stuart; Staats, Jurgens; Burger, Roelof P.; Havenga, Henno; Garland, Rebecca M.; Bester, Petra; Lebre, Pedro Humberto
BACKGROUND : Data on allergic rhinitis and respiratory health metrics are limited for South Africa, with grass pollen as a key outdoor aeroallergen. Exotic trees such as plane trees and ragweed produce highly allergenic pollen, dominating indigenous trees and weeds. Pollen allergy prevalence data is lacking in cities of North-West province such as Potchefstroom. OBJECTIVES : This study aimed to (i) assess the prevalence of allergies to major aeroallergens, including Poaceae (grasses), Cupressus/Hesperocyparis (cypresses), Platanus (plane tree), Ulmus (elm), Quercus (oak), Betula (birch), Olea (olive), Artemisia (sagebrush), Amaranthus (amaranth), Plantago (plantain), Morus (mulberry), and Ambrosia (ragweed), along with fungal spores such as Alternaria, Cladosporium, and Penicillium/Aspergillus, and (ii) investigate the monthly incidence of major aeroallergens and reactivity levels in sensitized adults in Potchefstroom. METHODS : Skin prick tests (SPTs) were performed on 202 adults aged 18–64 years with confirmed allergic symptoms during a field campaign at North-West University (NWU)'s Potchefstroom campus. A test panel of grass, weed, tree, and fungal spore extracts previously identified via aerobiological monitoring was used. Symptom scores were recorded using ISAAC questionnaires; Spearman's statistical correlation between symptom frequency and monthly aeroallergen concentrations were analyzed. RESULTS : Among the participants, 184 (91%) exhibited positive SPT reactions: 104 (57%) are monosensitized to pollen, 45 (24%) to fungal spores, and 35 (19%) are polysensitized. Aeroallergen prevalence was higher in females (73%) than in males (27%). The most common pollen allergens were Cynodon dactylon (Bermuda grass) (85%), Zea mays (maize) (46%), Platanus spp. (plane tree) (35%), and Ulmus campestris (field elm) (33%). Among fungal spores, Alternaria was the most common (93%), followed by Cladosporium (27%). A significant and positive statistical correlation was found between allergic rhinitis symptoms and monthly pollen concentrations of Betula, Morus, Platanus, and Quercus. DISCUSSION AND CONCLUSION : This pilot study linked aeroallergens detected in Potchefstroom with allergy profiles of local residents. The findings highlight the need for more comprehensive regional studies that integrate allergen testing with aerobiological data. Raising awareness and implementing health strategies are essential for managing allergic rhinitis in South Africa. More affordable and available SPTs kits, adapted to allergy prevalence in South Africa, are strongly suggested.
Ensuring Africa’s food security by 2050 : the role of population growth, climate-resilient strategies, and putative pathways to resilience
(MDPI, 2025-01) Simane, Belay; Kapwata, Thandi; Naidoo, Natasha; Cisse, Gueladio; Wright, Caradee Yael; Berhane, Kiros
Africa is grappling with severe food security challenges driven by population growth, climate change, land degradation, water scarcity, and socio-economic factors such as poverty and inequality. Climate variability and extreme weather events, including droughts, floods, and heatwaves, are intensifying food insecurity by reducing agricultural productivity, water availability, and livelihoods. This study examines the projected threats to food security in Africa, focusing on changes in temperature, precipitation patterns, and the frequency of extreme weather events. Using an Exponential Growth Model, we estimated the population from 2020 to 2050 across Africa’s five sub-regions. The analysis assumes a 5% reduction in crop yields for every degree of warming above historical levels, with a minimum requirement of 225 kg of cereals per person per year. Climate change is a critical factor in Africa’s food systems, with an average temperature increase of approximately +0.3 °C per decade. By 2050, the total food required to meet the 2100-kilocalorie per adult equivalent per day will rise to 558.7 million tons annually, up from 438.3 million tons in 2020. We conclude that Africa’s current food systems are unsustainable, lacking resilience to climate shocks and relying heavily on rain-fed agriculture with inadequate infrastructure and technology. We call for a transformation in food systems through policy reform, technological and structural changes, solutions to land degradation, and proven methods of increasing crop yields that take the needs of communities into account.
Blue carbon at the southern tip of Africa : current knowledge and future perspectives for dynamic estuarine environments
(Elsevier, 2025-09) Adams, Janine B.; Buttner, Daniel; Hawkes, Sarah; Human, Lucienne R.D.; Machite, Anesu; Mfikili, Athi N.; Ndhlovu, Andrew; Smit, Leigh-Ann; Rajkaran, Anusha; Riddin, Taryn; Rishworth, Gavin M.; Van Deventer, Heidi; Van Niekerk, Lara; Von der Heyden, Sophie; Whitfield, Emily C.; Raw, Jacqueline L.
Blue Carbon Ecosystems (BCEs), specifically salt marsh, seagrass, mangroves, occur in South Africa's relatively small, sheltered estuaries that are often disconnected from the ocean. These are dynamic environments where shifts between BCEs and other habitats along ecotones occur in response to mouth changes, floods and droughts, as well as anthropogenic pressures. Although Blue Carbon is becoming well established in South Africa, critical knowledge gaps remain; these are summarised under seven themes and future research and management actions identified. A holistic approach is recommended for Blue Carbon studies in estuaries to measure across elevation gradients (rather than focusing on individual vegetation types) and to include reeds, sedges and forested wetlands. Additionally, quantifying data deficient carbon stocks and processes, modelling future climate change impacts, instilling a sustainable long-term monitoring program, incorporating relevant emerging blue carbon stocks, realizing nationally inclusive restoration and protection co-management plans, and aligning local approaches with global frameworks of reporting are advocated as future recommendations with respect to South African BCEs. South Africa has high biodiversity and unique pressures influencing BCEs and is well positioned to inform the global research agenda. While the limited spatial extent of BCEs restricts the feasibility of carbon credit opportunities, high biodiversity values of these ecosystems hold potential under emerging ‘nature credit’ frameworks.
Building volume per capita : a crowding metric of housing disparities in Gauteng, South Africa
(Sage, 2025) Naidoo, Laven; Ballard, Richard; Naidoo, Yashena; Maree, Gillian; Khanyile, Samkelisiwe; Palacios-Lopez, Daniela; Esch, Thomas
In South Africa’s largest city region, located in the province of Gauteng, a key condition of inequality is that high-income households live in large houses while low-income households live in much smaller accommodation. Innovations in earth observation have enabled the modelling of building volumes in cities and this allows for new ways of assessing housing inequalities in Gauteng. This study calculates building volume per capita (BVPC) for the province as an indication of the volume of residential space in which individuals live. It offers five analyses using this data. First, mapping this metric illustrates that townships, informal settlements and inner city high-rise areas have cramped conditions of less than 10 cubic metres per person, while suburbs have a much higher building volume per capita. Second, the article shows that this metric complements traditional calculations of crowding, such as the number of people per room. Third, it calculates the relationship between BVPC and income and shows that the lower-earning three-fifths of households in the province occupy just 13% of the province’s residential building volume, while the higher-earning two-fifths occupy 87% of the province’s building volume. Fourth, it calculates that 51% of residential hexagons in the province fall below the threshold of adequately sized housing as defined by South African housing standards. Finally, it shows that areas that fall below the threshold have a higher proportion of informal housing.
Weather related disasters in South Africa from 1980 to 2023
(Elsevier, 2025-09) Bopape, Mary-Jane Morongwa; Keebine, G.; Ndarana, Thando; Mbokodo, I.L.; Hlahane, K.; Motshegwa, T.; Amha, Y.; Ogega, O.M.; Mfopa, C.; Mahlobo, D.D.; Engelbrecht, F.A.; Chikoore, H.; thando.ndarana@up.ac.za
This study presents an analysis of weather-related disasters in South Africa (SA), during the period 1980 to 2023. The data used includes the Emergency Events Database (EM-DAT) disaster list, the fifth generation European Centre for Medium Range Weather Forecasting reanalysis (ERA5), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) satellite imagery as well as the South African Weather Service synoptic charts for weather systems identification. Floods and storms emerge as the most prevalent disasters, particularly affecting KwaZulu-Natal (KZN) province (in the east of SA), with the eThekwini metropolitan municipality (metro) recording the most events. Although KZN receives substantial rainfall, no evidence suggests eThekwini experiences more rainfall than other districts in the province, suggesting human influences associated with urbanisation in disaster patterns. Cape Town metro reports the highest number of disasters in the western part of the country, associated with more rainfall, yet human factors may also contribute. Cut-off low systems and upper troughs which classify as mid-troposphere mid-latitude systems triggered the most floods and storms, while ex-tropical cyclones (ETCs) caused only four disasters during the study period. Upper Perturbations also resulted in floods and storm disasters indicating a need for forecasters to also pay attention to smaller scale processes. These findings enhance our understanding of weather-related disaster risks in South Africa, providing valuable insights for climate resilience and proactive disaster management. Given the reliance on the EM-DAT database, the potential for unrecorded disaster events introduces a limitation that may influence the conclusions drawn from this analysis.
Groundwater-vegetation interactions in rangeland ecosystems : a review
(MDPI, 2025-04) Rapiya, Monde; Ramoelo, Abel
Water scarcity is a growing global issue, especially in arid and semi-arid rangelands, primarily due to climate change and population growth. Groundwater is a crucial resource for vegetation in these ecosystems, yet its role in supporting plant life is often not fully understood. This review explores the interactions between groundwater and vegetation dynamics in various rangeland types. Groundwater serves as a critical water source that helps sustain plants, but changes in its availability, depth, and quality can significantly impact plant health, biodiversity, and ecosystem stability. Research indicates that groundwater depth affects vegetation types and their distribution, with specific plants thriving at certain groundwater levels. For instance, in grasslands, shallow groundwater can support diverse herbaceous species, while deeper conditions may favor drought-tolerant shrubs and trees. Similarly, in forest ecosystems, extensive root systems access both groundwater and soil moisture, playing a vital role in water regulation. Savanna environments showcase complex interactions, where trees and grasses compete for water, with groundwater potentially benefiting trees during dry seasons. Climate change poses additional challenges by altering rainfall patterns and temperatures, affecting groundwater recharge and availability. As a result, it is crucial to develop effective management strategies that integrate groundwater conservation with vegetation health. Innovative monitoring techniques, including remote sensing, can provide valuable information about groundwater levels and their impact on vegetation, enhancing water resource management. This review emphasizes the importance of understanding groundwater–vegetation interactions to guide sustainable land and water management practices. By enhancing our knowledge of these connections and utilizing advanced technologies, we can promote ecosystem resilience, secure water resources, and support biodiversity in rangeland systems. Collaborative efforts among local communities, scientists, and policymakers are essential to address the pressing issues of water scarcity and to ensure the sustainability of vital ecosystems for future generations.
Response of the global ITCZ to ENSO and how the ITCZ determined from maximum precipitation compares with the surface tropical wind convergence
(Elsevier, 2025-07) Ramotubei, Teke Solomon; Landman, Willem Adolf; Mateyisi, Mohau J.; Nangombe, Shingirai S.; Beraki, Asmerom Fissehatsion
Shifts in the position of the intertropical convergence zone (ITCZ) may lead to amplification of climate extremes such as droughts and flooding. Its spatio-temporal variations respond to well-established oscillation processes like the El Niño Southern Oscillation (ENSO). This research establishes the global and regional response of the ITCZ position to ENSO. It also explores the alignment between the ITCZ as determined from two methods: the surface tropical wind convergence, and maximum precipitation. The ERA5 reanalysis data, 1990–2020, are used in this study. Each longitude is scanned for latitude of maximum precipitation, during each El Niño/La Niña/Neutral year, within the 20°N/S latitude range to identify the ITCZ position. An overlay of surface tropical wind convergence and the ITCZ position is employed for comparison of the two methods. The study concludes that the position established by the maximum precipitation aligns with the surface tropical wind convergence over the global oceanic areas. On seasonal average, the La Niña ITCZ position is consistently southward of its El Niño position over Africa and Central Pacific Ocean. Furthermore, the extreme cases of El Niño/La Niña leads to further north/south shifting of the ITCZ position from its normal El Niño/La Niña positions. The continental and Atlantic Ocean ITCZ is more persistent and shows a minimal fluctuation, in comparison to Oceanic ITCZ, during the El Niño/La Niña. Cross-wavelet analysis was explored as an African case study and it shows common high-power features between the Oceanic Niño Index (ONI) and ITCZ signals over a four-year periodicity, mirroring the ENSO periodicity albeit with slowly varying time lag across the years. The cross-correlation of the two signals is strongest in Austral summer (DJF), corresponding to the peak of ENSO. This study contributes to the understanding of the overall description of the global and regional (with Australia and South America as new additions) ITCZ along with its response to the ENSO phases using the latest ERA reanalysis data. The global/regional spatio-temporal ITCZ shifts open an opportunity for improved interpretation of seasonal forecasts of hydroclimatic events, especially under climate change conditions that reflect a possibility of an increase in the frequency of ENSO events in the future.

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