Masters Degrees (School for Geospatial Studies and Information Systems)

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Now showing 1 - 5 of 11
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    Encroachment by informal settlements on military bases: army support base Potchefstroom
    (Stellenbosch : Stellenbosch University, 2023-12) Matjane, Motsweleng Lebogang Anthony; Mtshawu, Babalwa; Henrico, Ivan; Richmond, Amy; Stellenbosch University. Faculty of Military Sciences. School for Geospatial Studies and Information Systems.
    ENGLISH ABSTRACT: Encroachment of informal settlements on military lands is a growing concern that poses significant challenges to both military operations and civilian safety. This study investigated the extent and implications of informal settlement encroachment in the Potchefstroom region, focusing on the Army Support Base (ASB) Potchefstroom and the General De la Rey training area. Utilising geographic information systems (GIS) and remote sensing, this research conducted a comprehensive analysis of informal settlement growth around ASB Potchefstroom from 2011 to 2020. GIS-based change detection methodology was employed to assess changes in the accessibility of military lands over the specified period to reveal the progression of encroachment. In parallel, interpretative phenomenological analysis (IPA) was employed to explore the experiences and perspectives of knowledgeable senior military personnel and former military candidates. Through semi-structured interviews, this qualitative approach captured valuable insights into how encroachment impacts the military community in Potchefstroom. The study findings indicate that previously isolated military lands have been informally occupied by two distinct communities (Marikana and the Eleazer Up & Coming Farmers) with varying characteristics. The escalating scale of encroachment has led to compromised security, vandalism of military infrastructure, and increased safety risks in the military area. Given the seriousness of this issue, the study emphasises the need for immediate attention and proactive measures. Policymakers and relevant stakeholders at local, municipal, provincial, and national levels are urged to take action to prevent further encroachment and to protect the integrity and functionality of military lands. This research contributes to the field of urban geography, security studies, and governance by shedding light on the impact of informal settlements on military lands and raising awareness of the challenges faced by the military community in Potchefstroom. The study’s comprehensive approach of combining GIS analysis and IPA offers valuable insights for future research and policy interventions to address encroachment in similar settings.
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    Understanding crime in the context of COVID-19: the case of the Western Cape Province of South Africa
    (Stellenbosch : Stellenbosch University, 2023-12 ) Mayoyo, Nkosana Prince; Henrico, Ivan; Mtshawu, Babalwa; Stellenbosch University. Faculty of Military Sciences. School for Geospatial Studies and Information Systems.
    ENGLISH ABSTRACT: Crime mapping and geographic information system (GIS) analysis have become essential tools for law enforcement agencies and researchers in understanding, tracking, and combating crime. This master's thesis presents a comprehensive study conducted over three years (2019 to 2022) in the Western Cape Province of South Africa. The study aims to map and analyse crime incidents across all categories as reported by the South African Police Service (SAPS). This research employs two widely used spatial analysis techniques within GIS, namely the Kernel Density Estimation (KDE) and the Getis-Ord Gi* hotspot analysis tool, both available in ArcGIS. The primary focus is on evaluating the effectiveness of these tools in identifying and visualising criminal hotspots within the Western Cape Province. The duration of the study spans from 1 April 2019 to 31 March 2022, encompassing the period during and after the COVID-19 pandemic. It's important to note that the COVID-19 pandemic and associated regulations did not have universally accepted starting and ending dates, and various countries implemented and lifted restrictions at different times. To provide clarity, footnotes are included to specify a) the global temporal parameters of the pandemic1, b) any adjusted parameters within South Africa2, c) the precise temporal parameters of this study, and the rationale for selecting these particular dates3. This study examines crime patterns during the period of extraordinary security regulations and beyond, acknowledging the dynamic nature of the pandemic's timeline. Analogously, like WWI and WWII, wars may begin before formal declarations and persist beyond cease-fires, yet universally accepted calendar starting and ending dates are used for reference. Key findings reveal that while the pandemic led to an overall decrease in crime rates due to restrictions on movement and other factors, certain areas, notably the City of Cape Town Metropolitan, remained persistent hotspots for criminal activity throughout the period under investigation. The analysis further highlights the dominance of specific crime categories, particularly crimes against persons (CAP) and other serious crimes (OSC), which contribute significantly to the province's overall crime landscape. The results of this study hold valuable implications for law enforcement agencies, policymakers, and local authorities. By visualising and understanding spatial crime patterns, stakeholders can make informed decisions on resource allocation and crime prevention strategies, which ultimately reduce criminal activities and enhance public safety. This research contributes to the growing body of knowledge in the field of crime mapping and GIS analysis, particularly in the context of a global pandemic. It also underscores the importance of integrating spatial analysis techniques into crime prevention and law enforcement efforts. This study offers a valuable framework for future research and crime management policy development.
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    The ecological footprint of individual members at the Army Support Base Eastern Cape
    (Stellenbosch : Stellenbosch University, 2022-12) Fouche, Desire Elizabeth; Smit, Hennie; Stellenbosch University. Faculty of Military Sciences. School for Geospatial Studies and Information Systems.
    ENGLISH ABSTRACT: The Ecological Footprint (EF) is a measurement that is used to calculate the demand for resources placed on the environment because of the needs and wants of humans in their daily lives. It is important that each individual is aware of their EF because resources need to be conserved for future generations. In the Constitution of the Republic of South Africa environmental rights are entrenched, and the protection thereof against pollution, ecological degradation and overexploitation specified. The calculation of the EF by means of the Global Footprint Network (GFN) online calculator was used to measure the EF of the individuals of the Army Support Base Eastern Cape (ASB EC). Such a calculation has never been done at any military installation of the South African National Defence Force, a hiatus this research aims to fill. The Ecological Footprint can be measured by either using a mathematical calculation or an online calculator. The mathematical calculation or the Ecological Footprint Analysis (EFA) is based on either a compound - or component EF calculation. The GFN online ecological footprint calculator is currently the most used method to determine the EF of an individual and displays the land use type of each consumption category. These categories include food, shelter, mobility, goods and services, the EF, carbon footprint and carbon footprint as part of the EF as well as the number of Earths needed for a specific lifestyle. The EF online calculator was used to calculate the EF of the individual members at the Army Support Base Eastern Cape, a military support base situated in Gqeberha in the Eastern Cape Province of South Africa. The main function of the ASB EC is to supply support services. The ASB EC is situated in a larger Garrison area which houses other units and Arms of Services and has an average strength of 460 individuals. The methodology was based on a quantitative approach, using research questions and research objectives to classify the research study as a descriptive and exploratory study. A random sample of the population was used to complete the online EF calculation. The EF online survey method, a questionnaire, was used to obtain the quantitative data from the online results from each participant. The different categories and EF calculations were tabulated in a data matrix table to be able to complete the data analysis process. This data matrix table was in the format of an Excel spreadsheet and with the help of the Centre of Statistical Consultation at Stellenbosch University, the statistical analysis was done. The statistical data was analysed by using the STATISTICA 14.0 programme. The qualitative data that was available from the data matrix table was then used to calculate the EF of the individual members of the ASB EC as well as their combined EF. The ASB EC has a total of 460 personnel. On average the strength per day is 300 members. An attempt was made to include a total of 140 members, which is close to 30% of the overall personnel in the unit. The official unit’s name list was used to randomly select the participants. The analysis of the data was based on the examination of each variable which in all cases were expressed on a numerical or quantitative measuring scale. The sum of the variables was determined by computer program analysis. The descriptive EF online calculation data was used to determine the individual and combined EF of the individuals at the ASB EC to answer the research questions and the research objectives. The data-matrix table which contained the individual results of the GFN online EF calculation completed by the ASB EC participants were used to calculate the EF of everyone, and by adding them up, to determine the combined EF of the ASB EC. The results are described in relation to the rank groups, different departments, and gender of the participants. Officers recorded the highest EF across most categories, with NCOs, PSAP, and privates generally recording the lowest scores. The departments rendered fairly similar results across all categories of the EF. Even where differences existed, they were not always significant, however there were significant differences between male and female participants. In almost all categories, males scored higher than females, indicating that they have a higher EF than females. These trends are corroborated by the results of other studies. According to the results, officers have the highest scores in the different categories of ranks. Group 4 (Emergency Services and PTSR) and Group 1 (Headquarters (HQ), Communication, Human Resources, Senior warrant officer (SWO) and Control) dominate the calculation of the different departments, and in terms of gender, males recorded the overall highest scores. Secondly, officers play a dominant role in both the rank groups and the department compositions. Officers are a high-income group which is one of the main reasons for the high EF. Thirdly, males rather than females have the highest EF especially because of a high CF and mobility footprint because of their higher income. The combined results for the ASB EC indicated that the average planet score is 3.6, the EF 5,8gha, and the carbon footprint 10.6 (T per year) which means that 62% is part of the EF. According to the land use categories, the highest land type scores include forest land (0.7) and cropland (1.0), and the lowest score is grazing land (0.1). When considering the consumer categories, the carbon (3.5) and shelter footprints (1.7) are the highest as well as the food (1.1) and mobility footprints (1.0). The main findings from the study can be summarised as follows: level of income plays the most significant part in the calculation of the EF of an individual. A high income can influence 90% of the other categories because the lifestyle of an individual is directly related to their income. The study shows a direct link between higher income (proxied by rank, in this case officers with high income), and a high EF. Officers who fall in a high-income bracket play a dominant role in both the rank group as well as the different Groups because where the participants in the Group where mostly officers, high scores were recorded in the different categories. This means a high income reflects a more lavish lifestyle and a higher EF. The EF of males and females can both be high or low depending on the role that females play in their home and society. In this study, males dominated the EF calculation, evidenced by an overall high score in the different categories. Since almost no statistically significant differences between the different genders were found, it can be postulated that, because of the same working environment, males and females in the ASB EC may not have such a different EF as the raw results may suggest. More research is needed regarding this phenomenon.
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    Towards a learning analytics reference framework to predict at-risk students at the Faculty of Military Science
    (Stellenbosch : Stellenbosch University, 2022-12) Pretorius, Andre; Khoza, Lindiwe Mhaka; Dalton, Wayne Owen; Stellenbosch University. Faculty of Military Science. School for Geospatial Studies and Information Systems.
    ENGLISH ABSTRACT: Learning analytics (LA) is a relatively new field of application in the Analytics domain. Its main aim is to analyse teaching and learning (T&L) data from various sources to provide users with insights towards improving T&L. One of these T&L improvements is a greater focus on student success and more accurate methods of limiting student failure. This process starts with the identification of students at risk of failure (so-called “at-risk” students) through a prediction methodology which commonly falls within the knowledge sphere of Artificial Intelligence (AI), more specifically Machine Learning (ML). In contemporary information systems, the supporting platform for this is provided by an LA information system (LAIS) that relies on an underlying virtual learning environment (VLE), which in turn uses T&L data from a learning management system (LMS). A reference framework (RF) establishes a common foundation for future implementation of a system for developers and users. It provides appropriate guidance to users in a specific field of knowledge. Guidance is, however, generic in nature to secure reusability. This research focussed on developing an RF to implement LA in the Faculty of Military Science (FMS) of Stellenbosch University (SU) for at-risk student identification. The RF is supported by five models and one framework, namely, (1) a pedagogical model, (2) a model for effective VLEs, (3) a model for LA implementation, (4) a model for at-risk student identification and (5) a framework for the ethical use of LA. It is the conclusion of the study that the RF for LA in the FMS will provide suitable guidance for future implementation of LA in the faculty to effect timely identification of at-risk students and fitting remedial actions towards greater throughput may be implemented. It is envisioned that this RF be validated in the FMS in the near future and that future research in the use of ML be extended to identify suitable indicators of at-risk students more accurately.
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    Analysing the changes in bathymetry of Saldanha Bay between the years 1977 and 2021
    (2022-04) Du Toit, Louis; Henrico, Ivan; Mtshawu, Babalwa; Stellenbosch University. Faculty of Military Sciences. School for Geospatial Studies and Information Systems.
    ENGLISH ABSTRACT: Possessing one of the finest natural harbours on the South African coast, along with its ideal location on a major international trading route, the Saldanha Bay Municipality has been identified as a key development zone in the blue economy, earmarked to lead major developments in the region. Saldanha Bay is strategically positioned to serve the envisaged oil-and-gas sector on the west coast of the African continent and is a critical area for development for South Africa’s ‘blue economy’. Studies like Henrico & Bezuidenhout (2020) have proven that the changes made during the construction of the Port of Saldanha (PoS) have altered the shape and slope profile of Saldanha Bay (herein called the Bay, which refers to both Inner and Outer Bay, described in section 1.2) significantly, thus changing the hydrodynamics of the Bay. The aim of this study is to compare and analyse the changes in bathymetry of Saldanha Bay between 1977 and 2021. The general tendency of gradual increase in depth from the coastline towards the mouth of the Bay, with sharp increases in depth off Elandspunt and Salamanderpunt, is the same for both 1977 and 2021. The Ordinary Kriging (OK) interpolation method, employed by means of a Geographic Information System (GIS), was selected for creating surface models of the bathymetry of Saldanha Bay, and for conducting the comparison between the two datasets. Said comparison will determine the change in bathymetry over the 44-year period. A slope analysis was also performed to determine the stability of the ocean floor of the Bay. The results of this study indicate a general increase in depth since 1977, with most of the pixels in the graphical representation of the Bay (68.2%) indicating a depth increase between 0.395 - 3.203 m, and an average increase in depth within Big Bay of 1.799 m between 1977 - 2021. There were also two areas identified which experienced changes beyond the standard deviation and showed significant increases or decreases in depth. The general slope trend of Big Bay in 2021 remained fairly like that of 1977, with most of the Bay having a relatively low slope, between 0 - 1.3 degrees. However, in 2021 it can be seen that there is a slight increase in overall slope of Big Bay since 1977, with and average slope of 0.51 recorded in 2021, 0.2 degrees more than in 1977. Furthermore, in 2021 the majority of Big Bay had a slope of 1.3 degrees or less, 0.4 degrees more than in1977. Finally, in 2021 Big Bay also showed an increase in the maximum slope recorded in the Bay, with a maximum slope of 14.8 degrees, more than twice the maximum slope recorded in 1977. The findings of this study support the statements made by Flemming (1977) and Henrico & Bezuidenhout (2020) that the construction of the PoS changed the sedimentation processes within Saldanha Bay to some extent. However, the findings of this study are only relevant for a portion of Saldanha Bay, the inclusion zone in Big Bay as indicated in section 4.3. In this area however, there has been a total loss of 49 364 560.0 m3 in volume. The exact nature and driving forces behind this loss in volume still requires further investigation to be fully understood.