Browsing by Author "Shoko, Moreblessings"

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    Analytical camera pose estimation and inverse modelling of high order radial lens distortion polynomials for close range photogrammetry
    (2025) Ikokou, Guy Blanchard; Shoko, Moreblessings; Tagoe, Naa Dedei
    Camera calibration aims at estimating intrinsic and extrinsic camera parameters that accurately describe the projection of points from the 3D scene to the 2D image sensor. The absence of numerical estimates of parameters describing the camera internal and external geometry can prevent absolute readjustment of bundles of rays that project 3D points from the scene onto the image plane. When information derived from photographs is used for metric purposes, small imaging errors can significantly affect the accuracy of derived information. Current analytic a l method for camera pose calibration failed to exploit the intrinsic geometric properties associated with each camera parameter within the structures of individual coefficients of the projective transformation matrix. This resulted in these methods being prone to parameter coupling, sign ambiguity, and multiple roots associated with some of the parameters. In the same way, recursive reversions methods proposed to compute inverses of radial distortion coefficients in order to correct radial distortions were found not suitable for high-degree radial distortion polynomials and failed to model the inverse profiles of severe barrel, pincushio n, and moustache distortions inherent to consumer-grade cameras used in close range photogrammetry. This PhD research successfully developed two analytical calibration systems. The first calibration system decomposed the coefficients of the projective transformation matrix into nineteen robust equations that independently estimate individual parameters describing the internal geometry of the camera as well as its location and orientation in a 3D scene. The second calibration system, based on the concept of forced differential equation, successfully modelled inverse coefficients of high-order quintic, sextic, and octic radial distortion polynomials and reduced the effects of severe barrel, pincushion, and moustache radial distortions on distorted points. The experimental results demonstrate that both developed calibration strategies achieved root mean square reprojection errors of 0.0843 and 0.057 pixels, respectively. These values are substantially lower than those reported by several current state- of-the-art methods, which exhibit average errors around 3.63 pixels. Such a signific a nt reduction in error by nearly two orders of magnitude not only confirms the high accuracy of the proposed approaches but also underscores their suitability for close-range photogramme tr y applications where sub-pixel precision is essential. In practical terms, this level of accuracy enables more reliable 3D reconstructions and measurements in scenarios where even small deviations can lead to substantial errors. These results affirm the reliability and effective ness of the proposed calibration strategies, making them well-suited for high-precision 3D reconstruction, industrial metrology, cultural heritage documentation, and other close-range imaging tasks where geometric accuracy is paramount.
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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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    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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    Spatio-temporal analysis of coastal sediment erosion in Cape Town through remote sensing and geoinformation science
    (2023) Fanikiso, Lynn; Smith, Julian; Shoko, Moreblessings
    Coastal erosion can be described as the landward or seaward propagation of coastlines. Coastal processes occur over various space and time scales, limiting in-situ approaches of monitoring change. As such it is imperative to take advantage of multisensory, multi-scale and multi-temporal modern spatial technologies for multi-dimensional coastline change monitoring. The research presented here intends to showcase the synergy amongst remote sensing techniques by showcasing the use of coastal indicators towards shoreline assessment over the Kommetjie and Milnerton areas along the Cape Town coastline. There has been little progress in coastal studies in the Western Cape that encompass the diverse and dynamic aspects of coastal environments and in particular, sediment movement. Cape Town, in particular; is socioeconomically diverse and spatially segregated, with heavy dependence on its 240km of coastline. It faces sea level rise intensified by real-estate development close to the high-water mark and on reclaimed land. Spectral indices and classification techniques are explored to accommodate the complex bio-optical properties of coastal zones. This allows for the segmentation of land and ocean components to extract shorelines from multispectral Landsat imagery for a long term (1991-2021) shoreline assessment. The DSAS tool used these extracted shorelines to quantify shoreline change and was able to determine an overall averaged erosional rate of 2.56m/yr. for Kommetjie and 2.35m/yr. for Milnerton. Beach elevation modelling was also included to evaluate short term (2016-2021) sediment volumetric changes by applying Differential Interferometry to Sentinel-1 SLC data and the Waterline method through a combination of Sentinel -1 GRD and tide gauge data. The accuracy, validation and correction of these elevation models was conducted at the pixel level by comparison to an in-field RTK GPS survey used to capture the current state of the beaches. The results depict a sediment deficit in Kommetjie whilst accretion is prevalent along the Milnerton coastline. Shoreline propagation and coastal erosion quantification leads to a better understanding of geomorphology, hydrodynamic and land use influences on coastlines. This further informs climate adaptation strategies, urban planning and can support further development of interactive coastal information systems.
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    Use of agent based modelling to investigate the dynamics of slum growth
    (2013) Shoko, Moreblessings; Smit, Julian
    Informal settlements arise as a result of the urgent need for shelter by the urban poor. Urban planners and policy makers face challenges in effective management of slum settlements as they do not fully understand their dynamics and extents. Advances in Geomatics research have recently offered growing results in slum characteristics using various remote sensing and artificial intelligence approaches. The main objective of this research is to propose a conceptual model for the implementation of an empirically informed agent based prototype that can simulate future patterns and trends in land cover change over time specifically with reference to informal settlement proliferation in the city of Cape Town in South Africa. The study incorporates physical, environmental, social and economic factors specific to Cape Town in structuring behavioural rules for agents in a predictive environment. Input data is extracted from a time series study of remote sensing imagery, ancillary data and statistics. The resulting concept model for the prototype incorporates a static model, a dynamic and an interactive behaviour model that collectively form a combo for successful implementation of the physical agent based model. On implementation the model is expected to simulate city wide slum growth patterns and trends in Cape Town over time, highlighting likely areas of new settlement and revealing the eventualities of existing ones. Urban planners can use pattern information for proactive slum management and in preventing risk prone settlement especially in some areas of near coast Cape that are flood prone.