School of Geography, Archaeology and Environmental Studies (ETDs)
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Item Investigating the impact of the land reform policy on land use and land cover changes, in Ngaka Modiri Molema district of the North West province(University of the Witwatersrand, Johannesburg, 2024) Mmangoedi, Molebogeng Precious; Adam, ElhadiThe purpose of this study was to assess how land reform policies affected changes in land use and land cover in the province of North West's Ngaka Modiri Molema district municipality. The study employed remote sensing technologies to analyse changes in land use and land cover (LULC) resulting from the implementation of land reform programs between 1985 and 2015. The primary objective of the research was to systematically map Land Use and Land Cover types across five-year intervals spanning from 1985 to 2024, leveraging Landsat earth observation data in conjunction with a random forest classifier. These methodologies were employed to facilitate the identification of spatial patterns and trends associated with the implementation of land reform policies within the study area. Furthermore, the study utilized Landsat data and advanced change detection algorithms to quantitatively assess LULC changes over the specified timeframes. Through the application of spatial analysis techniques, the research aimed to elucidate the relationship between the implementation of land reform measures and corresponding shifts in LULC patterns across the research study area. The findings of the investigation indicated a noticeable expansion in built-up areas between the years 1985 and 2024 which was approximately 10.86%. This expansion was primarily attributed to the growth experienced by the municipality during this period. Additionally, more opportunities might have risen from the agricultural farming activities and also from the land reform policy being implemented. However, as the ownership changed due to land redistribution and more land was being acquired by black people through the land reform policy, agricultural farming decreased slightly throughout the years. The reduction was due to the factors that arose from inefficient policy implementation. The study also recommends that remote sensing techniques should be utilised to carry out studies to determine LULC changes that derive from land policies aiming at dealing with socio-economic factors and urbanisation. An incorporated agrarian reform sustainable programme has vast potential in cultivating the production of the projects, particularly if it involves packages in rural infrastructure, support services, and co-operatives. The major role of such an approach should be in the trainings conducted for the farmers, obtaining, and distributing agricultural resources and equipment to agrarian reform or beneficiaries of the land reform projects. Additionally, there should be an allowance for special grants which will be useful in supporting the government’s efforts.Item Modelling for Rainwater Harvesting Structures Using Geospatial Techniques(University of the Witwatersrand, Johannesburg, 2024-10) Makaringe, Precious Nkhensani; Atif, IqraClimate change poses a significant threat, leading to droughts, floods, and hindering sustainable development. Water scarcity is a growing concern, particularly in developing countries like South Africa, where limited freshwater resources are further strained by climate variability. This research explores the potential of rainwater harvesting (RWH) as a strategy to address water scarcity in such regions. This study aims to model potential rainwater harvesting sites in Lynwood Park, Pretoria, South Africa, utilising geospatial techniques. Object-Based Image Classification (OBIC) was employed to extract building footprints from high-resolution satellite imagery. Microsoft and Google building footprints were utilised to determine the suitable automated building footprints for Lynnwood Park. ArcGIS Pro software served as the primary platform for spatial data analysis and mapping potential RWH sites. Data integration included high-resolution satellite imagery, a Digital Elevation Model (DEM), building footprints, and rainfall data. Additionally, questionnaires were distributed to estimate population and water demand within the study area. The research demonstrates the efficacy of geospatial tools in identifying suitable locations for RWH systems. Indicating that steeper slopes in the southern region of Lynnwood Park have limited collection from large rooftops, while the flatter north offered greater potential. Rainfall graphs and PRWH results suggest that over half of Lynwood Park's annual water demand could be met through rooftop rainwater collection. However, factors such as system losses due to evaporation, inefficiencies in collection and storage, and variability in rooftop sizes across different buildings would need to be incorporated into more detailed models, as well as water quality analysis for rooftop harvested water in future studies. This study highlights the potential of RWH as a viable water security strategy in water-scarce regions. The findings contribute to the development of geospatial approaches for RWH implementation, promoting water security and sustainability in a changing climate.Item Integrating Sentinel-1/2 and machine learning models for mapping fruit tree species in heterogeneous landscapes of Limpopo(University of the Witwatersrand, Johannesburg, 2024-10) Chabalala, Yingisani Winny; Adam, ElhadiFrom ancient times to this century, Africa has relied chiefly on agriculture for survival. Crop type maps are crucial for agricultural management, sustainable farming systems, and realizing food security. Agronomists, agricultural extension officers, policymakers, and the government rely on crop type spatial distribution information to make informed decisions and optimize resource allocation for sustainable agricultural management. Attaining food security for all is an urgent need in Africa. However, the farming landscapes predominately comprise fragmented smallholder heterogeneous farms. The farming systems include intercropping and cultivating different crops that require different management strategies. This results in within-class spectral similarities and intra-spectral variability due to similar canopy structures and different phenologies, which complicates the application of remote sensing in crop type mapping. The free availability of Copernicus products such as Sentinel 1 and 2 have high temporal, spectral, and spatial resolution suitable for mapping smallholder agriculture. Thus, this research aimed to integrate Sentinel-1/2 and machine learning models for mapping fruit tree species in heterogeneous landscapes of Limpopo. First, the research tested the applicability of sampling techniques and five mapping classifiers (i.e., Random Forest (RF), Support vector Machine (SVM), Adaptive Boosting (AdaBoost), Gradient Boosting (GB), and eXtreme Gradient Boosting (XGBoost) in mapping fruit trees and co-existing land use types. The original dataset was under-sampled randomly into two balanced datasets (i.e., Dataset 1 and Dataset 2) consisting of 100 and 150 sample points. Furthermore, the imbalanced ratio from the original dataset was reduced by applying different sampling strategies to extract four imbalanced datasets (i.e., at 40%, 50%, 60%, and 70%), which resulted in the formation of Dataset 3, Dataset 4, and Dataset 5, respectively. These samples, together with the original dataset (i.e., Dataset 7), were used as input to Sentinel‑2 (S2) data using adaptive boosting (AdaBoost), gradient boosting (GB), random forest (RF), support vector machine (SVM), and eXtreme gradient boost (XGBoost) machine learning algorithms. The results showed that reducing the amount of imbalanced ratio by randomly under-sampling the original imbalanced dataset could increase the classification accuracy to 71% using the SVM classifier and 60% of the original dataset. Individually, the majority of the crop types were classified with an F1 score of between 60% and 100%. Secondly, the research independently assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for fruit tree mapping using random forest (RF) and support vector machine (SVM) classifiers. Four models were tested using each sensor independently and fusing both sensors. From the fused model, features were ranked using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. The best fruit tree map with an overall accuracy (OA) of 0.91.6% with a kappa coefficient of 0.91% was produced using the RF MDA and FVS model and SVM classifier. The application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; A = 87.01%, Kappa coefficient = 87%, respectively. The green (B3), SWIR_2 (B10), and vertical horizontal (VH) polarization bands were identified as the optimal spectral features for S2 and S1 data, respectively. The third part of the research identified the optimal growth window period in which fruit trees can be detected with high accuracy. Phenological metrics were extracted from 12 months (i.e., January to December) of Sentinel-2 (S2) data and were used to classify fruit trees using a random forest (RF) classifier in a Google Earth Engine environment. The results showed that fruit trees can be detected and mapped with high accuracy during winter months (i.e., April-July) with an overall accuracy (OA) of 84.89% and a kappa coefficient of 83%. The user accuracy ranged from 62 to 100%, while the producer accuracy ranged from 60 to 100%. The fruit trees were mostly differentiated from co-existing land use types using the short infrared and the red-edge bands. The fourth part of the thesis attempted to increase fruit tree classification accuracy by classifying optimal Sentinel-2 images acquired during the fruit trees' critical growth stages using a Deep Neural Network (DNN) model. This was achieved by applying phenological metrics derived from Sentinel-2 images acquired during optimal crop-growing seasons (i.e., flowering, fruiting, harvesting). The DNN models were optimized by tuning the hyperparameters to achieve the best classification results. The DNN produced an OA of 86.96%, 88.64%, 86.76%, and 87.25% for April, May, June, and July images, respectively. The results indicate the DNN models were robust and stable across the selected fruit growth periods. This research has shown that earth observation (EO) data such as Sentinel 1 and 2 can be used to map fruit trees in fragmented sub-tropical horticultural landscapes characterized by different environmental conditions and different crop cultivars operating under different management practices. The research results will assist agricultural stakeholders (i.e., farm managers, agronomists, agricultural extension officers, and policymakers) in allocating agricultural resources, devising effective agricultural management strategies, and attaining sustainable agriculture and food security.Item Study of the influence of gust fronts and topographical features in the development of severe thunderstorms across South Africa(University of the Witwatersrand, Johannesburg, 2024) Mofokeng, Puseletso Samuel; Engelbrecht, Francois A.; Bopape, Mary-Jane M.; Grab, Stefan W.South Africa experiences a variety of severe thunderstorms which occasionally leads to a large quantity of small-sized or large-sized hailstones, heavy rain and flash flooding, strong damaging straight-line winds, and/or even tornadoes. For the base period, June 2016 to June 2021, a significant percentage of these severe storms was triggered by topographic features. The Unified Model (UM) at 4 km horizontal grid resolution was used and found to be unable to predict topography-generated vertical wind shear and the associated severe thunderstorms. This inability of the model necessitated the development of a conceptual model by relating the rapid cooling of the cloud-top temperatures with high resolution topographic maps. This means, satellite images were used to deduce the connection of atmospheric fluids (gust fronts) with near linear, concave and/or downslope topographical features. Severe thunderstorms included those connected to the large amounts of vorticity advection (e.g. 500 hPa level), development of low-level mesoscale circulations within the synoptic settings and the resultant vertical wind shear in the lower tropospheric levels. Large amounts of negative vorticity advection are typical with strong horizontal shear and curvature; they are often correlated with trough axes that lean from the south-west to north-east. The usage of large amounts of negative vorticity advection transcends to whether discrete severe thunderstorms will be characterised by heavy rain and flash-flooding or hail with damaging winds. Moreover, the interaction of topography with gust fronts of the upwind thunderstorms linked with large amounts of negative vorticity advection is also investigated. The impacts of storms studied in this dissertation posed a major threat to property, livelihood, agriculture, human and animal lives or even immediate to residual economic loss. This research is aimed at improving the service level for the benefit of disaster management agencies and the public at large. An in-depth study of microscale events such as tornadoes and landspouts was also conducted to improve lead-time for their nowcasting.Item Assessing the effectiveness of wetlands in the Krugersdorp Game Reserve in attenuating pollution from mines on the West Rand, South Africa(University of the Witwatersrand, Johannesburg, 2023) Sawuka, Noluthando Thulisile; Evans, Mary; Masindi KhulisoIn South Africa, 48% of the country’s wetlands are critically endangered because of anthropogenic activities. Wetlands are an important part of the landscape and play a critical role including but not limited to improving water quality, habitat provision, and water storage. This research aimed to assess the effectiveness of wetland systemsin attenuating pollution from water discharged from abandoned gold mines in the Krugersdorp Game Reserve (KGR), West Rand. Eight (8) water samples were collected in the study site. Physico-chemical parameters were measured in situ, and chemical parameters were measured in the lab. The measured physico–chemical parameters from the majority of the sampled wetlands exceeded at least one of the stipulated water quality legislations, which included the General Authorization Limit Section 21f and h, 2013; Unit for TWQGR; Mine Health and Safety Act; and WUL wastewater in terms of the recorded pH, total dissolved solids, and salinity variables. Overall, a decreasing trend in pH level was observed from wetlands sampled upstream of the KGR to wetlands sampled downstream of the KGR, with the highest recorded pH level (Alkalinity: 8.9) obtained from the sampled wetland that was closest to the adjacent mining site upstream of theKGR whilst the lowest recorded pH level (Acidity: 3.9) obtained from a wetland sampling point that was further from the adjoining mine and downstream in the KGR. A weak and positive correlation (r=0.040) was obtained between the measured total dissolved solids and pH levels from the sampled wetlands, indicating minimal spatial variability. However, a strong positive correlation (r=0.999, Correlation is significant at the 0.01 level) was obtained between the measured total dissolved solids and salinity from the sampled wetlands. At least one of the limits stipulated by the water quality legislation was exceeded in terms of the analysed inorganic constituents from the sampled wetlands. The dominant ions recorded in the wetlands in increasing order are F, K, Cl, Mg, Na, Ca, and SO4. Mn and Si were the dominant metal concentrations recorded in most wetlands, with the former also showing exceedances when compared to the stipulated water quality guidelines. The recorded data from the measured physico–chemical parameters and analysed chemical variables indicated poor water quality in wetlands sampled downstream of the KGR and upstream of the KGR. Stringent measures in water quality monitoring need to be implemented to mitigate the environmental impacts associated with wastewater discharge into the receiving environment.Item Assessment of disposal methods of construction and demolition waste: A case study of south-eastern industrial and residential areas in Johannesburg, South Africa(University of the Witwatersrand, Johannesburg, 2024) Jager, Vasti de; Kubanza, Nzalalemba SergeIn a world where all strive for further development, construction and demolition play alarge role in that process. The waste generated in construction and demolition projects is of great magnitude and needs to be dealt with and disposed of appropriately, however, is this truly the case? Gauteng is a province where landfills are easily accessible and a cheap disposal option. This study set out to assess disposal methods of construction and demolition waste in south-east Johannesburg, South Africa. Landfills and recycling were the prevalent disposal methods, and these were compared to other countries’ disposal methods. Policy and legislation regarding solid waste management were analysed and a gap between written documents and implementation was identified. The question of sustainability also played a role in the synthesis of the studyItem Monitoring and evaluating urban land use land cover change using machine learning classification techniques: a case study of Polokwane municipality(University of the Witwatersrand, Johannesburg, 2023) Funani, Tshivhase; Mhangara, PaidaRemote sensing is one of the tools which is very important to produce Land use and land cover maps through the process of image classification. Image classification requires quality multispectral imagery and secondary data, a precise classification technique, and user experience skill. Remote sensing and GIS were used to identify and map land-use/land-cover in the study region. Big Data issues arise when classifying a huge number of satellite images and features, which is a very intensive process. This study primarily uses GEE to evaluate the two classifiers, Support Vector Machine, and gradient boosting, using multi-temporal Landsat-8 images, and to assess their performance while accounting for the impact of data dimension, sample size, and quality. Land use/Landcover (LULC) classification, accuracy assessment, and landscape metrics comprise this study. Gradient Tree Boost and SVM algorithms were used in 2008, 2013, 2017, and 2022. Google Earth Engine was used for supervised classification. The results of change detection showed that urbanization has occurred and most of the encroachments were on agricultural land. In this study, XG boost, and support vector machine (SVM)) were used and compared for image classification to oversight spatio-temporal land use changes in Polokwane Municipality. The Google Earth Engine has been utilized to pre-process the Landsat imagery, and then upload it for classification. Each classification method was evaluated using field observations and high-resolution Google Earth imagery. LULC changes were assessed, utilizing Geographic Information System (GIS) techniques, as well as the dynamics of change in LULCC were analysed using landscape matrix analysis over the last 15 years in four different periods: 2008–2013, 2018 and 2022. The results showed that XGBoost performed better than SVM both in overall accuracies and Kappa statistics as well as F-scores and the ratio of Z-score. The overall accuracy of gradient boosting in 2008 was 0.82, while SVM showed results of 0.82 overall accuracy and kappa statistics of 0.69. The average F-score for SVM in 2008 was from 0.58- 1.00, in 2013 an average of 0.86-0.97, and in 2022 it was 0.76. Z values were not statistically significant as all values were below the z score of 1.96. The ratios for the two classifiers were also taken to know which classifier performs the best. The results showed 212:212 which indicates that during 2008 SVM and XG boost performed the same way as they classified the same number of cases. During 2013 the ratio was 345:312 which shows that XGBoost performed better than SVM. The results of 2017 show 374:316 which shows that XGBoost performed better than SVM. Lastly, in 2022 the ratio was 298:277 which shows that XGBoost performed better than SVM. Overall zscores result show that XGBoost performs better than SVM. Overall, this study offers useful insight into LULC changes that might aid shareholders and decision makers in making informed decisions about controlling land use changes and urban growthItem Towards the co-management of natural resources in protected areas in South Africa: a study of the Silaka nature reserve, in Eastern Cape province(University of the Witwatersrand, Johannesburg, 2024) Kostauli, Mzwabantu Richard; Mokotjomela, Thabiso Michael; Simatele, Mulala DannyThe pressure in the management of South Africa’s natural resources in protected areas has led to the development of land policy and the process has undergone important changes since the dawn of democratic rule in 1994. This process started when land claimants were expected to interact with the Department of Rural Development and Land Reform to submit land claims based on land dispossession since 1913. The Silaka Nature Reserve as a research site is one of the protected areas on the Wild Coast Region of the Eastern Cape Province that has seen the land restitution process completed. Considering the land being claimed, the study aimed to investigate the management effectiveness as a protected area while promoting sustainable community development. A combination of different ethnographic methods was applied to collect data for this study. The study largely followed a qualitative research approach for data collection. The research questions were aligned with the community involved in the land restitution processes, applicable legislative frameworks, co-management activities, roles and responsibilities of key stakeholders and the alternative strategies suitable to promote sustainable use of natural resources, and community development to reduce conservation conflicts. This study applied a purposeful and snowball sampling strategy to acquire primary data to select research participants from the relevant government institutions, traditional leadership, local community structures and specific individuals who gave specific views or opinions on specific issues relevant to the study. Interpretivism research philosophy has then been used to demonstrate the application of qualitative research approaches for improving complex and controversial issues and to highlight some land reform and natural resource co-management challenges. Interpretivism was used to demonstrate the present understanding of complex and controversial issues. The findings revealed several gaps and deficiencies in the land restitution processes including the implementation of co-management activities pursued. The uncertainties with the neighbouring communities are a result of the limited involvement of the key stakeholders during the land restitution process. The findings also pointed to partial implementation of co- management activities. Simultaneously, the participants also viewed the protected area as an important community asset from which benefits can be derived. The significance of this study was aimed at influencing South Africa’s policies on land restitution and co-management of natural resources in protected areas. The limitations of the study were that it only focused on land restitution processes and co-management of natural resources at Silaka Nature Reserve. It is recommended that the natural resource management plans need to be reviewed to create reasonable access to natural resources by local communities, and the inclusive co-management agreement must be developed and implemented. It is also recommended that the reserve should venture into a Community Public Private Partnership with a private investor for commercial activities to reinforce capital to diversify mechanisms for income generation and job creation for local people. For future research studies, it is recommended that further investigation on socio-economic impacts of protected areas on adjacent local communities be pursuedItem Compost-assisted phytoremediation of mine tailings and footprint areas using chrysopogon zizanioides (l) roberty enhanced with moringa leaf extract biostimulant in the Witwatersrand goldfields of South Africa: a sustainability initiative(University of the Witwatersrand, Johannesburg, 2024) Mlalazi, Nkanyiso; Chimuka, Luke; Simatele, Mulala DannyIn the Witwatersrand goldfields of South Africa, mine tailings and footprint areas are significant environmental problems because they are major sources of toxic metals. These metals can leach into soils, and both surface and ground water, causing serious risks to human, animal, and plant life. In this study, the compost-assisted phytoremediation of tailing storage facilities (TSFs) and footprint soil using Chrysopogon zizanioides (vetiver grass) enhanced with moringa leaf extract (MLE) was investigated. A greenhouse experiment was conducted to identify the most favorable parameters, and was followed by a field study to test the optimized parameters under real-environment settings. For the greenhouse experiment, a 3×2×2 fully crossed factorial design was used to determine the optimum variables. Vetiver growth was assessed under three compost concentrations (0%, 30% and 60%), two types of MLE (laboratory extracted MLE and commercial MLE) and two application regimens (once a week and twice a week) were used. The biomass and metal concentrations in the vetiver grass roots and leaves were measured after sixteen weeks followed by a two-way ANOVA analysis and the post-hoc tests. All the vetiver that was planted in 0% compost died within four weeks regardless of the MLE treatment. Vetiver grass planted on the 60% compost amendments and sprayed with laboratory extracted MLE had the highest biomass production, followed by plants grown in 30% compost amendments and sprayed with commercial biostimulant. However, the heavy metal removal or uptake data by the plant was inconclusive, as most of the toxic metals were not removed by vetiver grass which was attributed to the effect of compost. Based on biomass data, the 30% compost amendment and commercial bio-stimulant was the ideal treatments for the phytoremediation of gold mine tailings using vetiver grass. Although metal accumulation by plants is one of the attributes considered in phytoremediation, it is not the most significant factor in the phytostabilisation process. Plant growth and biomass production are the most significant, therefore it is concluded that vetiver, MLE and compost can be used in the phytostabilisation of gold mine tailings, however reduction in compost may be considered in future to improve the accumulation of metals in the roots for improved results. Following the conclusion of the greenhouse study, a field study was conducted during the rainy season of 2021. Two field experiments were carried out concurrently at two sites: the footprint area (that was used as a rock dump) and the tailings storage facility (TSF 4). A split-plot design was used in this study. The experiment at each site assumed a 3×1×2 factorial design, with three levels of compost treatment (0%, 15% and 30%), 1 level of vetiver cultivar (Chrysopogon zizanioides), and 2 levels of MLE treatment (commercial MLE and tap water, both sprayed once a week). Three blocks measuring 1 m × 2 m, each with 20 holes filled with equal amounts of soil amended with the different compost levels were prepared in triplicates. A single vetiver grass slip was planted in each hole. The blocks were then divided into 2 sections, each with 10 holes, and commercial MLE was sprayed on one section, while only water was sprayed on the other section once a week. After sixteen weeks, three plants were harvested from each section and the number of leaves, leaf length, number of tillers, biomass for roots and leaves and element concentrations were measured. Data analysis was done using two-way ANOVAItem Reassessing the stratigraphy and formation of the basal deposits at Klasies River Main Site with a multiscale and multiproxy approach(University of the Witwatersrand, Johannesburg, 2024) Morrissey, Peter; Wurz, Sarah; Mentzer, SusanThe basal deposits at Klasies River Main site, associated with the MSA I and II lithic cultural phases and dating from >120 ka to ~80 ka, have yielded highly significant archaeological assemblages and human fossils across multiple phases of excavation since the late 1960s. These finds have contributed to a growing understanding of the appearance and intensification of modern human behaviours and provide rare insight into Homo sapiens anatomy during the early parts of the Late Pleistocene. The three recesses occupied during this period represent distinct depositional environments with differing degrees of attractiveness for human activities. Significant climatic, environmental, and geomorphic changes, including large fluctuations in sea level, occurred, impacting formation processes within the site complex. Stratigraphic relationships across a space like this would always be complicated but understanding them here is even more difficult because there are not continuous deposits between the recesses for all or part of their respective sequences. Geoarchaeological research has taken place alongside all three phases of excavation at Klasies. Until Sarah Wurz began her field programme in 2013, this work entailed macroscopic descriptions of standing sections (at differing resolutions) and the sedimentological analysis of bulk samples. Given the finely laminated nature of many of the deposits, even higher resolution bulk sampling resulted in the incorporation of multiple visible deposits into individual samples in many cases. More recently, archaeological micromorphology and other microscale analyses have been applied to deposits in the site complex by Susan Mentzer and colleagues. This work has provided important new insights into human behaviour and the spatially and temporally variable impacts of different diagenetic processes. Here, field observations of standing sections and microcontextual analysis are used to provide greater insight into the formation of deposits in two areas of the site complex. This information is used, along with unpublished field notes and profile drawings and critical engagement with the extensive, but seldom detailed, literature to assess and refine stratigraphic correlations of the basal deposits both between different recesses and different stratigraphic systems (the layers used in the initial excavations and the excavation units grouped into members and sub-members in subsequent work). The results demonstrate that the formation of any particular deposit could involve any number of combinations and relative intensities of different depositional and post- depositional processes. Furthermore, the interplay between geogenic, biogenic, and anthropogenic processes is often significant. Anthropogenic deposition has long been recognised as being highly significant at Klasies, but it is now also clear that humans played a major role in reworking sediment through daily activities during occupations, very likely including trampling and site maintenance activities. Chemical diagenesis had a major impact on the preservation of anthropogenic features, but variations in the intensity and frequency of anthropogenic deposition also influenced how susceptible deposits were to diagenesis. It has proven possible to correlate between the two stratigraphic systems in Cave 1B, a particularly understudied area of the site complex, providing clarity on the cultural association of a highly significant human fossil. The overall stratigraphic system used at the site complex is now also better understood, both in terms of correlations and the nature of the system. Finally, this study highlights the utility of a multiscale geoarchaeological approach to site complexes like Klasies for understanding site formation and stratigraphy. It also highlights the vital, but often ignored or underplayed, connection between site formation processes and stratigraphy, especially in such a complicated context.