Browsing by Author "Smit, Julian"

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    Open Access
    A pluralistic, socio-ecological approach to understand the long-term impact of mountain conservation: a counterfactual and place-based assessment of social, ecological and hydrological change in the Groot Winterhoek Mountains of the Cape Floristic Region
    (2018) Holden, Petra Brigitte; Hoffman, Timm; Eckardt, Frank; New, Mark; Smit, Julian; Visser, Martine; Ziervogel, Gina
    The problem: For protected areas to remain relevant, we need to understand their impact on a wide set of conservation objectives and environmental outcomes. We also need to evaluate how this influence relates to the socio-ecological environment within which they occur. This is a complex endeavour requiring a pluralistic approach, which draws on a wide range of interdisciplinary fields. Research question: This thesis addresses the following question: What effects do mountain protected areas have on ecosystem services over time and how does this influence relate to broader socio-economic and ecological drivers of landscape change? Aim and objectives: I use a pluralistic, socio-ecological framing to assess the impact of ~40 years of mountain protection, drawing on comparisons of ~30 and ~40 years before and after protection respectively, with an adjacent area of similar terrain informing scenarios of counterfactual conditions. I also investigate what types of values (economic and intrinsic) are important when determining the impact of mountain protected areas. Thesis approach and methods: I operationalise the concepts of socio-ecological systems, ecosystem services, land use transitions and counterfactuals to investigate socio-ecological change and how it relates to protected area impact in the Groot Winterhoek, a mountain catchment in the south-western Cape of South Africa. This mountain catchment is important for regional water supplies for agricultural and domestic uses and falls in the Cape Floristic Region, a global biodiversity hotspot. It is comprised of privately owned mountain wildlands and a wilderness-protected area, known as the Groot Winterhoek Wilderness Area, established in 1978 (gazetted in 1985) which forms part of the Cape Floristic Region World Heritage Site. I combine methods from social science, ecology, environmental geography, geomatics and hydrology to understand the history of land use and cover (land use/cover) and associated ecosystem service trade-offs, how they are perceived by landowners as well as their wider impact on the region. Specifically, I assess the impact of protection on land use/cover, vegetation, fire and water flows over the last ~50 years, by comparing and contextualising results of change within the protected area to alternative scenarios of “no protection” (the counterfactual conditions). Vegetation and land use/cover change inside the protected area were determined respectively using 72 repeat terrestrial photographs and vegetation surveys, and an analysis of orthorectified aerial imagery. Methods used to construct the counterfactual scenarios of mechanisms (e.g. changes in land use/cover) that would likely drive vegetation changes inside the protected area included: i) 60 repeat surveys and in-depth interviews with landowners adjacent or proximal to the protected area owning unprotected land of similar terrain to the protected area; and ii) land use/cover change analysis of orthorectified aerial imagery of adjacent unprotected land of similar terrain before and after protected area establishment. 4 This latter information was used to understand the role of the protected area in driving vegetation changes inside the protected area. Social, biophysical and remote sensing results were directly used to parameterise land use/cover components of a hydrological model to determine the influence of protection on water flows. Specifically, water flows were simulated for the current state of the environment inside the protected area as well as for several counterfactual scenarios i.e. the alternative land use/cover scenarios of “no protection”. These counterfactual scenarios included land use/cover at two-time steps of ~30 and ~8 years before protection and one-time step ~40 years after protection both inside and outside the protected area. Results: Long-term change in ecosystem service use outside the protected area on privately owned land of similar terrain to inside the protected area (Section 3): Over the last ~50 years, outside the protected area, there was a shift from livestock-based, subsistence agriculture and small-scale farming to a diversified set of ecosystem service uses. The combined area of grazing and wildflower harvesting declined by 39%, while the number of landowners using the mountains for personal nature-based recreation and ecotourism increased by 61% and 23% respectively. Agriculture intensified in suitable areas of mountain land with the number of landowners cultivating land increasing by 20%. Exogenous socioeconomic drivers associated with globalisation and economic growth were important causal mechanisms of land use change. Landowners valued mountain protection for intrinsic and non-use reasons (73-80% of landowners), including existence, bequest and option values, as well as for the indirect use of water supply (72% of landowners) in comparison with direct use reasons such as spiritual/cultural experiences and nature-based recreation inside the protected area (18 and 50% of landowners respectively). Personal, nature-based recreation outside the wilderness-protected area was associated with valuing the protection of mountain land for intrinsic and non-use reasons. Long-term vegetation change inside the protected area and plausible mechanisms driving vegetation change (Section 4): Inside the mountain protected area, fynbos vegetation cover increased on average between 11 and 30% and there were significant declines in bare ground and rock cover. In 5 accumulation and fire intensities. However, these latter changes in land use/cover also occurred outside the protected area (see results summarised for Section 3 above and Section 4 below) and therefore cannot be attributed to protected area establishment. Land use/cover and the influence on water flows inside the protected area compared to counterfactual scenarios of no protection (Section 5): Declines in grazing and changes to the fire regimes occurred regardless of the protected area boundaries. In the past, there was a high frequency of small, low intensity fires across the landscape, both inside and outside the protected area. More recently, fires have been actively suppressed and this resultsin the build-up of biomass and the development of extensive, high intensity fires which, under suitable conditions, burn large expanses of the mountain catchment. Hydrological modelling showed that a high intensity burning regime negatively affected streamflow regardless of protected area boundaries. Streamflow increased by more than 80% under high flow conditions and decreased by more than 40% under low flow conditions relative to an unburnt ‘natural’ scenario. Over the last 50 years there has also been a substantial increase in dams, buildings and roads and minor increases in cultivation outside the protected area. This has been avoided inside the protected area where these land use/cover classes declined. If the increase in these land use/cover types observed outside the protected area occurred inside the protected area this would have resulted in reductions in daily streamflow leaving the protected portion of the catchment. For example, outside the protected area reductions of 8% to 25% of streamflow were observed during mid and low flow conditions respectively, particularly during dry years, in comparison to a ‘natural’ scenario. In contrast, inside the protected area streamflow recovered from past conditions to more closely resemble the natural flow conditions of the catchment. Therefore, had the protected area not been established there would have been losses in streamflow from the catchment as well as an increase in the degree of fragmentation within this mountain area. However, with increased water storage and fragmentation outside the protected area has also come increased socio-economic opportunities such as employment and local opportunities for ecotourism and sustainable agriculture e.g. indigenous cut flows. This highlights the importance of maintaining various forms of land management systems (multifunctional landscapes) within mountain ecosystems but also the need to understand the sustainability of different land management system types. Determining appropriate land management systems for mountain areas should be based on a full understanding of the impacts on ecosystem service benefits and costs at local and regional levels between social groups both spatially and temporally. Broader significance: This thesis contributes to the conservation literature on two main fronts. Firstly, it contributes conceptually and theoretically to understanding the dynamics of ecosystem services in relation to mountain protection. Secondly, it contributes methodologically by using an inclusive, trans- and interdisciplinary research approach for evidence-based conservation at a place-based and landscape level. The study provides a case 6 study example of the positive impact that mountain protection has on water-related ecosystem services, notably by maintaining streamflow throughout high to low flow periods and during dry years. It also provides clear evidence that ecosystem service trade-offs do not remain constant over time and shows that intrinsic and non-use values are required when describing the importance of mountain protected areas. In terms of understanding the impact that protected areas have in mountain regions, the research shows that complex processes are at play that extend beyond the boundaries of a specific protected area in both time and space. Interactions between global and local drivers were found to be prominent causal mechanisms of socio-ecological change and ultimately determined the influence of mountain-protection on land use/cover, fire, vegetation and water-related ecosystem services. The thesis emphasises that counterfactual framings are necessary to understand and attribute the impacts of protected areas on environmental outcomes, however pluralism and socio-ecological approaches are critical to determine plausible counterfactual conditions. This thesis focused only on landowners adjacent and proximal to the protected area owning the majority of mountain catchment land of similar terrain. It is likely that multiple socioeconomic trade-offs have occurred between different social groups and generations at both local and regional levels. Understanding how the disadvantages and benefits of the impacts of protected areas are apportioned across the landscape and temporally is an aspect that requires future research. Central to this would be to fully consider how human well-being is influenced both upstream and downstream, including at regional levels, and between social groups and across generations. Considering the impact of protected areas on the full range of ecosystem services and linking this to societal preferences and perceptions should be incorporated into the overall goal of developing an evidence base for conservation. This is because it is both scientific evidence and societal change that can determine protected area persistence and thus long-term protected area impact.
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    A settlement-level perspective of the spatial relationship between economic performance and population change in South Africa between 2001 and 2011
    (2021) Arnold, Kathryn Anne; Smit, Julian; le Roux, Alize
    Migration has long been an important phenomenon shaping the demographic profile of South Africa, and migration and labour are often considered to be intrinsically linked. The push–pull theory of migration, which still tends to dominate gravity-based migration modelling as well as academic thinking, is grounded on the assumption that migration is a functional and inevitable outcome of spatial inequality. Economic drivers of migration are most frequently used to explain population movements in the South African context, given, especially, that slow and uneven economic growth, economic disparities, inequality and unemployment persist as some of the country's biggest socio-economic challenges. Urban living holds the promise of employment prospects and improved conditions, and thus the basic premise of many micro-level models of migrant decision-making is that migration occurs with the expectation of being better off in doing so. The research design of this study set out to empirically investigate the theoretical perspective of the push–pull model of migration from an economic and settlement-based standpoint, and makes novel contributions to the disciplines of Geography, Geographical Information Science, and Urban and Regional Planning. The ultimate aim was to establish a settlement-level perspective of the spatial relationship between economic output (as a measure of economic performance) and working-age population change in South Africa between the Census years of 2001 and 2011. To support the settlement-level analysis scale, special attention was paid to sourcing fine-resolution economic and population datasets covering both the national spatial extent, as well as the tenyear temporal analysis window, and applying advanced GIS methods and techniques to prepare, align, analyse and visualise these datasets. In addition, traditional non-spatial statistical analyses were also employed to measure and quantify the relationship using a correlation-based research approach. Furthermore, the research also proposed a novel way of classifying settlements in South Africa, according to their economic profiles. Based on the research findings, the study identified eight broad settlement types in South Africa, according to an economically profiled settlement classification typology. Population change in the working-age population was found to have a positive statistically significant association with economic performance at settlement level in South Africa. This relationship proved to be multifaceted, given the complex nature of the South African economic landscape at settlement level, with considerable variability (based on the strength of the relationship) between different settlement types. While none of the settlement types exhibited a very strong relationship between economic performance and population change, several settlement types did indicate a moderate to strong association, while other settlement types were shown to have negligible to weak associations. Furthermore, in certain settlement types, some demographic groups, based on age, gender, employment status, and skill level, were found to have markedly higher associations with the economy than others. In its empirical contribution towards evidence-based decision-making, especially in the domain of urban and regional planning, the research findings are valuable in helping to support future policy and development interventions so that development planning can be more successfully targeted and more sensitive to the local South African context, given that South Africa has an intricate history of labour migration, and labour-force participation is a key factor for individuals to improve their socio-economic status. The study highlights important spatial linkages between economic opportunities and patterns of population change in South Africa, and defines and explores a new perspective of this relationship at settlement level. The results of this study further reinforce the literature, that nuanced and dynamic interplays are evident between the push and pull factors influencing population-change dynamics, in that, on its own, economic performance was not found to be a definitive predictor of population change or migration likelihood at settlement level.
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    A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes
    (2013) Ikokou, Guy Blanchard; Smit, Julian
    Multi-scale image segmentation produces high level object features at more than one level, compared to single scale segmentation. Objects generated from this type of segmentation hold additional attributes such as mean values per spectral band, distances to neighbouring objects, size, and texture, as well as shape characteristics. However, the accuracy of these high level features depends on the choice of segmentation scale parameters. Several studies have investigated techniques for scale parameter selection. These proposed approaches do not consider the different objects’ size variability found in complex scenes such as urban scene as they rely upon arbitrary object size measures, introducing instability errors when computing image variances. A technique to select optimal segmentation scale parameters based on image variance and spatial autocorrelation is presented in this paper. Optimal scales satisfy simultaneously the conditions of low object internal variance and high inter-segments spatial autocorrelation. Applied on three Cape Town urban scenes, the technique produced visually promising results that would improve object extraction over urban areas.
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    A way to use GIS (incl. geomasking) to understand homelessness: a focus on the spatial characteristics of and around sleeping locations of the homeless in Cape Town City Bowl
    (2020) Kekana, Dime; Smit, Julian
    Background: The homeless individuals/groups are the most vulnerable and less dignified member of the society. The evidences lie in the nature of their sleeping locations in the urban spaces, amongst other aspects. An internationally unique and integrated approach (GIS/socio-spatial) is utilized to enhance the knowledge and understanding of homelessness through analyzing the spatial characteristics of and around the sleeping locations of the homeless community in the urban public spaces, Cape Town City Bowl (South Africa) case study. Data Source and Method: Through the quantitative approach, the individual sleeping locations of The Homeless, including their surrounding characteristics, are observed daily for two weeks, 13-26 Oct. 2018 (total of all locations: n = 9515, daily average, n = 680) between 06:00 am and 08:30am. The analyses entail sequential application of eight analytical methods; spatial distribution, attribute analysis, proximity analysis, weather analysis, and obfuscation/geographic masking Results: (a) The daily individual sleeping locations of the homeless individuals and groups increase over time but their geographic distributions are similar or display insignificant/little variations. (b) Majority of these locations are situated in marginalized urban spaces that deny The Homeless personal privacy/security, human dignity and perpetuate stigmatization and social isolation. (c) The sleeping locations of The Homeless are far from the sources of basic needs to enhance their livelihoods (e.g., water resources). (d) Although more data is needed, however, the limited data in this research show that weather conditions are (in)directly related to the changes in the numbers of sleeping locations. (d) The voronoi masking and weight rand perturbation are best presenting the sleeping location of The Homeless without compromising the spatial confidence of The Homeless, and the spatial distributions/patterns of these locations. Conclusion: GIS (geographic information system) is capable of enhancing the knowledge and understanding of homelessness, and therefore, it can inform establishments and improvements of initiatives/measures that seek to reduce the vulnerability of the homeless community and/or integrate them with the public community, especial in the urban spaces.
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    Creating 3D models of cultural heritage sites with terrestrial laser scanning and 3D imaging
    (2012) Held, Christoph; Rüther, Heinz; Smit, Julian
    The advent of terrestrial laser-scanners made the digital preservation of cultural heritage sites an affordable technique to produce accurate and detailed 3D-computermodel representations for any kind of 3D-objects, such as buildings, infrastructure, and even entire landscapes. However, one of the key issues with this technique is the large amount of recorded points; a problem which was even more intensified by the recent advances in laser-scanning technology, which increased the data acquisition rate from 25 thousand to 1 million points per second. The following research presents a workflow for the processing of large-volume laser-scanning data, with a special focus on the needs of the Zamani initiative. The research project, based at the University of Cape Town, spatially documents African Cultural Heritage sites and Landscapes and produces meshed 3D models, of various, historically important objects, such as fortresses, mosques, churches, castles, palaces, rock art shelters, statues, stelae and even landscapes.
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    Developing a collaboration network framework to facilitate geospatial data access and exchange in the context of National Geospatial Data Infrastructure (NGDI)
    (2025) Odeyemi, Chris; Smit, Julian; Shoko, Moreblessings
    National Geospatial Data Infrastructures (NGDIs) provide holistic frameworks with several technological components that address and overcome geospatial access and exchange issues. The components of any NGDI area include geospatial data, people, access networks, policies, and standards that aim to facilitate geospatial data management. Even though geospatial datasets are becoming more available in most African countries, access and exchange is still challenging. In Nigeria, most Geospatial Information (GI) stakeholders (producers, providers, and users) acquire and produce the same types of geospatial datasets, which are fragmented within the different databases across the nation, thus making them redundant. The challenges to coordinating geospatial data access and exchange using collaboration networks have not been investigated thoroughly. Access to geospatial datasets remains a critical developmental enabler in Africa, which is the overarching goal of any NGDI. It is, therefore, pertinent to investigate how civil society can easily and quickly access and exchange geospatial data in the context of NGDI for sustainable development. This research aims to develop a collaboration network framework to enable access and exchange of geospatial data between GI stakeholders to support the development and implementation. National Geospatial Data Infrastructure (NGDI). A mixed-method research approach is adopted for this research. It combines qualitative and quantitative analysis methods using survey questionnaires and semi-structured interviews to develop a generic collaborative network framework for geospatial access and exchange. The study further reveals that governance, policy, technology, culture, and economics can influence the administration of NGDI through collaboration networks in the country. The developed framework incorporates the five identified components of a collaboration network for geospatial spatial data access, sharing, and exchange as an administrative tool to overcome the challenges faced for further development and the implementation of NGDI in the country. An SDI-Readiness index status was computed for Nigeria to be 0.84 (84%). In a broad sense, the SDI-readiness index has improved compared to 0.58 (58%) computed in 2017, and any country with an index greater than 0.8 can be called a spatially enabled society. This study considered governance, policy, technology culture, economics, and communication as a significant aspect of understanding collaboration networks. The problem investigated in this research is to understand how these five components of a collaboration network can potentially contribute to the goals of development and implementation of NGDI, which requires formalizing a collaboration network between GI stakeholders for geospatial data access and exchange. This research proposed a collaboration network initiative as best practice for NGDI in Nigeria to facilitate geospatial access and exchange. NGDI development and implementation proposed here, through collaboration network, draws heavily on, one, SDI cookbook of the elements and status of SDI, and two the Implementation Guide of IGIF. Furthermore, this research integrated knowledge from geoinformation technology, business, and public administration to help develop the framework. The research has helped close a knowledge gap in that GI organizations to build collaboration networks for geospatial data access and exchange among Public Geospatial Information (GI) stakeholders. Further avenues of research address the need for monitoring the performance of collaboration networks, as it affects geospatial data sharing and exchange, the impact of Internet-of-Things (IoT) on NGDI, the influence of the private sector's on the development and implementation of NGDI, the integration of real-time sensor-based systems to NGDI and exploring the possibility of expanding collaboration network framework into developing a regional NGDI initiative.
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    Developing an accurate close-range photogrammetric technique for extracting 3D information from spherical panoramic images
    (2017) Tagoe, Naa Dedei; Rüther, Heinz; Smit, Julian
    Panoramic images (panoramas) are wide-angle images that provide fields of view of up to 360°. They are acquired with a specialised panoramic camera or by stitching a series of images captured with a conventional digital camera. Panoramas have widely been used to texture 3D models generated from laser scanning, for creating virtual reality tour applications, documenting landscape and cultural heritage sites, advertising real estates and recording crime scenes. The goal of this research was to develop an accurate close-range photogrammetric technique for the semi-automatic extraction of 3D information from spherical panoramas. This was achieved by developing a non-parametric method for the removal of distortions from images acquired from fisheye lenses as well as an algorithm, here referred to as the Minimum Ray Distance (MRD), for the fully automated approximate relative orientation of spherical panoramic images. The bundle adjustment algorithm was then applied to refine the orientation parameters of the panoramas; thus enabling accurate 3D point measurement. Finally, epipolar geometry theory was applied to the oriented panoramas to guide the interactive extraction of additional conjugate points. The MRD algorithm has been extended to laser scanning technology for the first approximations of laser scan setup positions and scan orientation prior to a leastsquares based registration. The determination of approximate scanner orientation and position parameters were accomplished using panoramic intensity images derived from full dome laser scans. Thus, a technique for the semi-automatic extraction of 3D measurements from panoramic images has been developed in this research. The technique is most appropriate for applications which do not require dense point clouds and in situations with limited access to funds or as a quick field method to document many features in a short time. This is because a single image orientation is required for several overlapping images as compared to the normal stereo or multi-image photogrammetric approach. It is not suggested that 3D reconstruction from spherical panoramic images should replace traditional close-range photogrammetry or laser scanning; rather, that the user of panoramic images will be offered supplementary information to the conventional and modern cultural heritage documentation approaches.
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    Development of a land use-based spatial water requirements model for the Berg Water Management Area
    (2017) Van Der Walt, Marthinus; Smit, Julian
    This study was conducted to investigate the requirements for the spatial modelling of current and future water demand in the Berg River Water Management Area in the Western Cape of South Africa in order to produce a prototype model from which annual water requirements could be computed and spatially visualised. To accomplish this the spatial distribution of water demand within the study area was first investigated. The data required to perform spatial water demand modelling of diverse land uses and socio-economic activities were evaluated. Finally, the question of improving spatial water demand modelling at the catchment scale was considered from both a systems design and a technical perspective. The resulting model consists of two main modules; one performing a rudimentary monthly soil water balance to obtain monthly and annual irrigation requirements, and another applying preconfigured determinant layers derived from land use to town zone layers in order to determine annual urban water use intensities per areal unit. The resulting model prototype follows a sequential workflow based on a series of components that combine to produce a spatial overview of water use intensity within the study area. Water demand was found to be predominantly irrigated agriculture in the upper reaches of the Berg (mainly wine grape) and was found to be dominated by intensive industrial users in the central and lower reaches. The model was designed so that new data could be introduced in order to expand the system where required, as well as allowing for updated datasets to be incorporated as they become available. Due to the uncertainties inherent in the modelling and approximation of real world phenomena, the importance of establishing a set of structured, stable, predefined user requirements and system specifications were noted as a fundamental requirement for improving model development and design efficiency and ensuring model validity. It was further found that incorporating additional datasets, covering parameters related to the system, may serve to improve model accuracy, but could easily lead to compounded errors if not correctly parameterised or adequately validated.
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    The development of a method for semi-automatic classification of built-up areas from aerial imagery
    (2013) Duncan, Patricia; Smit, Julian
    It is essential for geospatial and mapping organisations that changes to the landscapeare regularly detected and captured, so that map databases can be updated. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa’s national mapping agency, currently relies on manual methods for digitizing features and detecting changes. These methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The objective of this research is to develop a process for semi-automatic classification of built-up areas from aerial imagery in South Africa. Built-up areas are important as they can grow and change rapidly. Since the South African landscape is varied and climatological conditions differ from one area to another, a general and robust method that can be applied across the country is needed. This project aims to find the best approach for classifying urban built-up areas from high-resolution aerial imagery by comparing various image classification methods, so that a method that is transferable and applicable in diverse South African scenes may be developed. Image classification methods were compared and it was found that pixel-based classifiers were unsatisfactory in classifying built-up areas, whereas object-based classifiers had better results. Image segmentation, the first step in an object-based classification, can considerably influence the results of the classification task. It is therefore essential that suitable image segments be generated before the segments are classified. The proposed The proposed methodology involves the use of cadastral data in the image segmentation process and texture measures in the classification of built-up areas within an object-based process. The method can be applied to diverse scenes across South Africa to find built-up areas. This is a generalised approach and can assist the CD: NGI in the process of updating their topographic database by reducing the time that operators spend on identifying and manually digitizing built-up areas.
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    Enhancement of digital elevation models using tree-based ensemble machine learning algorithms
    (2023) Okolie, Chukwuma; Whittal, Jennifer; Smit, Julian
    Geospatial practitioners and national mapping agencies (NMAs) in Africa are constrained to rely on open-access remote sensing datasets, even as they struggle to meet up with best practices on spatial data infrastructure and topographic map revision. Thus, global digital elevation models (DEMs) have gained worldwide prominence due to their free availability; a prime advantage when compared to prohibitively expensive airborne topographic surveys. However, the accuracies of global DEMs are affected by several anomalies that diminish their quality and compromise their adequacy for applications where precise and accurate terrain information is needed. This research proposes an explainable tree-based ensemble feature-level fusion framework for enhancing satellite DEMs using Cape Town, South Africa as a case study. The enhancement methodology combines elevation and terrain features data alignment (co-registration and resampling) with feature-level fusion (ensemble learning) into a DEM enhancement framework. 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. Initially, the qualities of two satellite-derived interferometric DEMs (NASADEM and Copernicus) and two photogrammetric DEMs (ASTER and AW3D) were comparatively examined in a series of qualitative and quantitative tests in five different landscapes spread across Cape Town: urban/industrial, agricultural, mountain, peninsula and grassland/shrubland. Based on their performances, Copernicus and AW3D DEMs were selected for further analysis. The next phase involved a comparative evaluation of ten treebased ensembles for enhancement of Copernicus DEM over agricultural lands. At two implementation sites, there was a 6 – 13% reduction in the MAE and 15 – 29% reduction in the RMSE, and the corrected Copernicus DEM showed several topographic improvements such as smoothing of rough edges, enhanced stream channel conditioning and diminution of coarse/grainy pixels. Following the comparison, three recent implementations of gradient boosting, the extreme gradient boosting (XGBoost), light boosting machine (LightGBM) and categorical boosting (CatBoost) were selected for the development of a robust DEM enhancement framework. After training and testing, the models were applied for correcting the DEMs at two implementation sites spread across the five landscapes. Going further, a rigorous hyperparameter tuning strategy was implemented for the three models using a principled, robust and computationally efficient Bayesian optimisation scheme. The optimisations were operationalised with ten steps of random exploration for diversification of the exploration space, and 40 - 50 iterations to increase the likelihood of finding an optimal combination of hyperparameter values. The uniqueness of the optimisation scheme is the very wide diversification of the search space for random exploration. The performance of the models was compared based on default hyperparameters versus Bayesianoptimised hyperparameters. The result is a sequential correction and fusion scheme to increase the vertical accuracy and reduce errors in the final DEMs. The corrections achieved significant and highly competitive accuracy gains of up to 64% RMSE (68% MAE) reduction in Copernicus DEM and up to 78% RMSE (82% MAE) reduction in AW3D DEM. The robustness of the proposed framework was proven in several performance evaluations and comparative assessments. Summarily, it outperformed a globally acclaimed corrected DEM and the authoritative South Africa national DEM, and surpassed the achievable accuracies of several previously proposed strategies, including multiple linear regression. Moreover, three-dimensional terrain analysis and lineament mapping showed the potential of the proposed scheme for enhancing deliverables in topographic and geologic mapping. The proposed approach also incorporates explainability measures to describe the interactions between predictor variables and their influence on the predicted DEM errors. It provides a cost-effective framework and ‘minimal' computation expense. The innovative DEM enhancement scheme proposed in this research is applicable to other global landscapes.
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    Evaluating the performance of multi-rotor UAV-Sfm imagery in assessing simple and complex forest structures: comparison to advanced remote sensing sensors
    (2021) Onwudinjo, Kenechukwu Chukwudubem; Smit, Julian
    The implementation of Unmanned Aerial Vehicles (UAVs) and Structure‐from‐Motion (SfM) photogrammetry in assessing forest structures for forest inventory and biomass estimations has shown great promise in reducing costs and labour intensity while providing relative accuracy. Tree Height (TH) and Diameter at Breast Height (DBH) are two major variables in biomass assessment. UAV-based TH estimations depend on reliable Digital Terrain Models (DTMs), while UAV-based DBH estimations depend on reliable dense photogrammetric point cloud. The main aim of this study was to evaluate the performance of multirotor UAV photogrammetric point cloud in estimating homogeneous and heterogeneous forest structures, and their comparison to more accurate LiDAR data obtained from Aerial Laser Scanners (ALS), Terrestrial Laser Scanners (TLS), and more conventional means like manual field measurements. TH was assessed using UAVSfM and LiDAR point cloud derived DTMs, while DBH was assessed by comparing UAVSfM photogrammetric point cloud to LiDAR point cloud, as well as to manual measurements. The results obtained in the study indicated that there was a high correlation between UAVSfM TH and ALSLiDAR TH (R2 = 0.9258) for homogeneous forest structures, while a lower correlation between UAVSfM TH and TLSLiDAR TH (R2 = 0.8614) and UAVSfM TH and ALSLiDAR TH (R2 = 0.8850) was achieved for heterogeneous forest structures. A moderate correlation was obtained between UAVSfM DBH and field measurements (R2 = 0.5955) for homogenous forest structures, as well as between UAVSfM DBH and TLSLiDAR DBH (R2 = 0.5237), but a low correlation between UAVSfM DBH and UAVLiDAR DBH (R2 = 0.1114). This research has demonstrated that UAVSfM can be adequately used as a cheaper alternative in forestry management compared to more highcost and accurate LiDAR, as well as traditional technologies, depending on accuracy requirements.
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    Evaluating the suitability of UAV data for mapping dominant plant species in a heterogenous fynbos seep wetland
    (2025) Musungu, Kevin; Shoko, Moreblessings; Smit, Julian; Dube, Timothy
    Traditional methods for mapping plant species necessitate fieldwork and labour-intensive estimation of proportionate cover of the species under study. However, the inundated nature of wetlands makes fieldwork significantly difficult, costly, and prone to inaccurate estimations. In comparison, remote sensing technology offers a less resource-intensive approach, and multitemporal observations can enable species identification and monitoring. Among the remote sensing sensors, unmanned aerial vehicles (UAVs) have gained global prominence as affordable platforms for vegetation inventory studies. However, the potential use of UAVs for Fynbos wetland inventory has not been explored. This study used multispectral UAV photography from Parrot Sequoia and Micasense RedEdge- M multispectral cameras to discriminate eleven wetland Fynbos plant species in a seep wetland located in the Steenbras Nature Reserve in the Western Cape province of South Africa. The UAV multispectral data was gathered over six dates (August 2018, October 2018, December 2018, February 2019, April 2019, and February 2020) spanning three seasons and used to extract the multitemporal spectral signatures of the plant species. Then, critical spectral indices were identified based on the plant spectral signatures and ensemble feature selection. Of the twenty-seven indices assessed, the Visible Atmospherically Resistant Index (VARI), Modified Soil Adjusted Vegetation Index 2 (MSAVI2) and two indices developed in this study, namely, Red Green Vegetation Index (RG) and Log Red Edge (LogRed) were found to be pertinent for the classification. Three machine learning classifiers comprising Random Forest, K Nearest Neighbour, and Support Vector Machines were used to classify the different plant species across all dates using a dataset consisting of only spectral bands and another consisting of key spectral bands and indices. Classification accuracies improved when spectral indices were integrated with the spectral bands. Random Forest proved the most reliable, with generally better overall and per- class accuracies than the other machine learning classifiers. Lastly, the study assessed the effect of seasonal variability on the per-class performance of the machine learning classifiers and identified Spring as the optimum time of year for the classification of most of the plant species. This study highlights the potential of UAV data for inventory in heterogenous Fynbos wetlands.
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    Flood modelling using data available on the Internet
    (2011) Pretorius, M J; Smit, Julian
    The aim of this study was to determine if sufficient data at no charge is available on the Internet to use as input to a free and open source hydrological model for use in a flood monitoring system. As such, the monitoring system would be SensorWeb enabled. The study area is the C83A quaternary catchment (746 km2) in the Northern Free State, part of the Vaal primary catchment in South Africa.
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    GIS-based analysis of spatial accessibility : an approach to determine public primary healthcare demand in metropolitan areas
    (2015) Mokgalaka, Hunadi; Smit, Julian; Mans, Gerbrand
    It is important for health planners to provide health services as effectively and equitably as possible for the development of quality living environments. The provision of adequate healthcare services, particularly in metropolitan areas, is becoming more difficult because of three developments: slow economic growth; the rapid growth of metropolitan areas and their subsequent increases in population. It is thus a challenge to provide what is considered a fair or socially just distribution of healthcare services to a population with changing healthcare needs. The spatial distribution of people and their varying need for healthcare services is a long-standing interest in the field of service planning, and provides a classic issue well suited for Geographical Information Systems (GIS) to analyse. Access is an important aspect in healthcare service planning. GIS-based accessibility analysis is a logical method that can be applied to test the degree to which access is obtained. Such successful applications of GIS-based analysis have been useful in indicating the accessibility of an existing or potential service. This has provided a good basis for the planning of healthcare services. However, it has been increasingly realised that there is a growing need for a paradigm shift in the planning process. In South Africa, primary healthcare (PHC) is a dual system made up of private and public healthcare facilities. Private PHC is expensive and only affordable to people with medical insurance. These people, most currently belonging to the middle and high income brackets, are theoretically also healthier than the rest of the population. But a small proportion of the population in the low income bracket also has medical aid or insurance. Hence, it is quite difficult to make a clear distinction of the low, middle and high income uninsured population when measuring access to public primary healthcare services. In this study, three different scenarios to calculate the uninsured population were generated and tested using a GIS-based form of catchment area analysis. The results from the catchment area analysis were compared with actual public PHC demand in the form of headcounts and further analysis of the origins of the patients was undertaken using a patient register. Results indicate that there is no significant difference in the spatial extent of the catchment areas of the facilities across the three demand scenarios but that there are significant differences in demand visits per scenario. A patient register and facility headcounts, both based on actual visits to public PHC facilities, were compared to the results of the catchment area analysis. The comparison results show that almost 45% of the patients did not use their closest facility as a first point of contact. The total allocated demand visits in scenario 3 was strongly in line with the total number of headcounts of the area, and thus is considered the most suitable calculation of uninsured population for implementation in a GIS-based accessibility analysis.
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    GIS-based decision support approach for selecting a new landfill site for the city of Cape Town
    (2006) Kimani, Gichobi Justin; Smit, Julian; Butcher, Shirley
    Recent studies indicate that the population of Cape Town generates approximately 2.2 milliontons of waste annually. Numerous waste minimization strategies have been developed whichhave not been successful in reducing the amount that needs to be disposed of at a landfill site.This results to mounting pressure on existing waste disposal sites thus necessitating an urgentneed for a new regional landfill. According to CCA Draft Environmental Impact Report (2006),the former Cape Metropolitan Council (CMC) appointed technical consultants in 2000 to identifyand assess the potential sites for a landfill to service Cape Metropolitan Area (CMA), presentlyreferred to as the City of Cape Town (CCT). The construction of a landfill has significant impacts on the environments. It is for that reason Integrated Environmental Management (IEM) has to be followed to assess the impacts. The principle of IEM is broadly interpreted as applying to the planning, assessment, implementation and management of any project proposal or activity that has a potentially significant effect on the environment. Environmental Impact Assessment (EIA) process, which lies in the heart of the IEM, is enforced to examine the environmental effects of development. These impacts are directly related to the physical location of the project. That makes site selection for proposed project a very important stage of the EIA process. Laws have been enacted to minimizeenvironmental impacts, including strict guidelines for siting landfills. Using landfill siting criteria and site selection methods, the technical consultants identified four potential sites, Atlantis being the only site falling within the City of Cape Town. The interviews, backed by secondary data sources such as websites and project reports, revealed that the techniques used to identify potential sites for the landfill, even when combined are costly and time consuming. Several scenarios were run using various ArcGIS extensions, including the ModelBuilder to identify sites that met the stated criteria. GIS analysis yielded agreeable results with the recommendations from the consultants who used techniques other than GIS to identify the regional landfill. The research findings demonstrate that GIS is an efficient and dependable stand-alone technique that can be implemented in landfill site studies thus expedite the decision making process.
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    GIS-Based Site Suitability Analysis for Wind and Solar Photovoltaics Energy Plants in Central North Region, Namibia
    (2023) Kamati, Klaudia; Smit, Julian; Orti, Miguel
    Increasing urbanisation and population growth are making it difficult for governments to achieve sustainable development. Provision of clean energy is among the seventeen sustainable development goals, as it reduces reliance on fossil fuels. In recent years, Namibia has rapidly increased her reliance on sustainable energy. The renewable energy sources (RESs), including wind and solar energy, can be described as clean sources which have lesser negative environmental impact compared to conventional energy sources. Amongst the pressing challenges today is finding solutions on efficient solar and wind energy production. It is imperative to work out the optimum location of RESs before installing them. This can significantly improve performance and establishes the foundation for studying both solar and wind power in a site selection problem. This study aims to determine potential locations for wind and solar photovoltaic (PV) energy plants installation using one of the multi-criteria decision-making (MCDM) methods, the analytical hierarchy process (AHP), and a geographic information system (GIS) within the Central North Regional Electricity Distributor (CENORED) supply area. Combining GIS with MCDM results in a powerful technique for selecting potential sites, since GIS provides effective analysis, manipulation, and visualization of geospatial data, whereas MCDM provides consistent weighing of criteria. In the evaluations of the location: topographical, environmental, climatic and regulations constraints were considered as factors that may facilitate or hinder the deployment of solarwind energy power plants. For solar PV energy plant, the highest potential areas are in the north-west, south-west and study area's southern regions, whereas for the wind power plant, only the northwest part is a highly suitable location for wind energy plants installation. These findings can be used to determine most favourable location of interest for solar PV and wind power plant development or to support the integration of electrical grid expansion and off-grid electrification strategies.
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    Incorporating local participation and GIS in assessing flood vulnerability in informal settlements : Masiphumelele case study
    (2011) Tyler, Rebecca; Smit, Julian
    The case study applies a GIS-based methodology to assess the vulnerability of Masiphumelele, to both wetland flooding and coastal storm surges. This informal settlement, south of Cape Town has rapidly expanded since its inception 20 years ago, and large numbers of economic migrants largely from the Eastern Cape have swelled the population and over-whelmed the local infrastructure. The settlement is now expanding northwards in a largely uncontrolled fashion into an ecologically important wetland.
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    The integration of Geographical Information Systems with multicriteria decision making techniques to improve poverty eradication planning
    (2014) Daniels, Roger Hubert; Smit, Julian
    Poverty eradication as a policy issue has received significant attention since the promulgation of the South African National Development Plan (NDP). The NDP envisages that by 2030 poverty should be eradicated. To do this government must accurately target their interventions ensuring that the intended population benefits from the actual poverty eradication intervention. With the evolution of systems and processes in the Science and Technology industry over the past two decades, the integration of Geographical Information Systems (GIS) and MCDM techniques has achieved encouraging results within different planning domains (Lidouh, 2012: 2). This research paper presents a vector - based GIS - MCDM methodology that integrates both Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and COmplex PRoportional Assessment (COPRAS) within a GIS environment. This integration is facilitated through the use of loose coupling within the ArcGIS 10.2 environment.
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    Investigating methodologies for evaluating the effectiveness of Integrated Spatial Information System (ISIS) implementation in the valuation department of the City of Cape Town
    (2014) Leponesa, Mphepelo Mabesa; Smit, Julian
    The increasing need to develop fully integrated spatial information systems that help improve planning and decision making have led the countries to create partnerships as to facilitate the improved sharing of spatial data and to realise the full potential of spatial data infrastructure. In this process researchers and practitioners use appropriate methods, tools and frameworks to examine, analyse and evaluate the new implemented systems after its implementation. The attempt to find suitable methodologies for evaluating the effectiveness of the system has led to extensive research to develop, identify and test suitable methods and frameworks and to apply these to case studies. This research investigates the methodologies for evaluating the effectiveness of Integrated Spatial Information Systems (ISIS) implemented in the Valuation Department of the City of Cape Town. The spatial information systems of Valuation Department and the effectiveness of ISIS implementation in this Department are investigated.
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    A new trajectory for spatial data infrastructure evolution in the developing world
    (2010) Makanga, Prestige Tatenda; Smit, Julian
    Spatial Data is a key resource in the development of cities. There is a lot of socio-economic potential that is locked away in spatial data holdings and this potential is unlocked by making the datasets widely available for use. Spatial Data Infrastructures (SDIs) have served this primary purpose; to make data accessible through the use of web based technologies. However, SDIs have not had their anticipated impact at local levels of governance. They have traditionally served as platforms that facilitate access to raw spatial datasets. They have not fully facilitated for the use of these datasets and therefore have attracted minimal attention from decision makers and users. This research suggests a new trajectory for SDI evolution; a trajectory that will allow them to evolve into more relevant platforms for confronting the urban crisis in developing nations and thereby ensuring that they have the societal impact that they are intended to. The research explores the characteristics of the mainstream efforts to counter urban crises in the developing world to determine how the new SDI should be re-conceptualised to more adequately assist in responding to the urban crisis. This leads to the incorporation of Evidence Based Practice (EBP) into SDI through the use of urban indicators and knowledge creation processes to reflect on the pressing societal issues. From the new SDI concept, an architectural design is implemented as a “proof of concept”. At the heart of this new concept is the SDIs ability to provide access to more than just raw spatial datasets but useful information products that are based on these data. This proves that EBP can be incorporated into SDI to make them more efficient in responding to the urban problems in developing nation and consequently more relevant Information Infrastructures for urban decision makers.