Nethengwe, N. S.Dondofema, F.Daswa, Shumani Samuel2024-10-032024-10-032024-09-06Daswa, S.S. 2024. GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality. . .https://univendspace.univen.ac.za/handle/11602/2709MENVSCDepartment of Geography and Environmental SciencesCrime is a serious problem with high social and economic costs in South Africa. It is neither unique nor random, but rather tends to be unevenly distributed and has a spatio-temporal pattern. The aim of this research is to analyse the spatial and temporal distribution of crime prevalence in Thulamela Local Municipality using Geographic Information Systems (GIS). GIS applications were used to open new opportunities in crime control and prevention. The spatio-temporal distribution of crime in Thulamela Local Municipality was analysed using GIS tools. This research study adopted both quantitative and qualitative approaches to produce a more comprehensive study of the spatial and temporal distribution of crime in Thulamela Local Municipality. Data was analysed for various argumentations, i.e., spatial distribution of crimes, temporal trends, and identification of hotspots. A Hotspot Analysis (Getis-Ord Gi*) tool was employed to unveil spatial clusters of crime prevalence. The analysis pinpointed distinct hotspots where crime incidents were significantly concentrated. The present study has found that crime incidences are influenced by various factors such as alcohol and substance abuse, domestic violence, illiteracy, poverty, unemployment, and self-enrichment. Thohoyandou was found to be one area with a high crime prevalence compared to Tshaulu and Mutale. Crime analysis did not only deepen our understanding of crime patterns, but also provided actionable insights on the types of crimes that happen in the different areas. By employing a diverse array of spatial and temporal analytical tools, I unearthed trends, clusters, and causative factors, understanding the socio-economic factors that play a role in the number of criminal activities that happen all over the country. As we continue to grapple with the multifaceted challenge of crime prevention, this comprehensive analysis serves as a foundation for data-driven strategies that can enhance public safety and well-being in Tshaulu, Mutale, Thohoyandou, and similar regions.1 online resource (ix, 76 leaves) : color illustrations, color mapenUniversity of VendaCrime hotspotUCTDCrime patternsCrime prevalenceSpatial and temporal anaysisThulamela Local MunicipalityDissertationDaswa SS. GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality. []. , 2024 [cited yyyy month dd]. Available from:Daswa, S. S. (2024). <i>GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality</i>. (). . Retrieved fromDaswa, Shumani Samuel. <i>"GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality."</i> ., , 2024.TY - Thesis AU - Daswa, Shumani Samuel AB - Crime is a serious problem with high social and economic costs in South Africa. It is neither unique nor random, but rather tends to be unevenly distributed and has a spatio-temporal pattern. The aim of this research is to analyse the spatial and temporal distribution of crime prevalence in Thulamela Local Municipality using Geographic Information Systems (GIS). GIS applications were used to open new opportunities in crime control and prevention. The spatio-temporal distribution of crime in Thulamela Local Municipality was analysed using GIS tools. This research study adopted both quantitative and qualitative approaches to produce a more comprehensive study of the spatial and temporal distribution of crime in Thulamela Local Municipality. Data was analysed for various argumentations, i.e., spatial distribution of crimes, temporal trends, and identification of hotspots. A Hotspot Analysis (Getis-Ord Gi*) tool was employed to unveil spatial clusters of crime prevalence. The analysis pinpointed distinct hotspots where crime incidents were significantly concentrated. The present study has found that crime incidences are influenced by various factors such as alcohol and substance abuse, domestic violence, illiteracy, poverty, unemployment, and self-enrichment. Thohoyandou was found to be one area with a high crime prevalence compared to Tshaulu and Mutale. Crime analysis did not only deepen our understanding of crime patterns, but also provided actionable insights on the types of crimes that happen in the different areas. By employing a diverse array of spatial and temporal analytical tools, I unearthed trends, clusters, and causative factors, understanding the socio-economic factors that play a role in the number of criminal activities that happen all over the country. As we continue to grapple with the multifaceted challenge of crime prevention, this comprehensive analysis serves as a foundation for data-driven strategies that can enhance public safety and well-being in Tshaulu, Mutale, Thohoyandou, and similar regions. DA - 2024-09-06 DB - ResearchSpace DP - Univen KW - Crime hotspot KW - Crime patterns KW - Crime prevalence KW - Spatial and temporal anaysis KW - Thulamela Local Municipality LK - https://univendspace.univen.ac.za PY - 2024 T1 - GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality TI - GIS based spatio-temporal analysis of crime prevalence in Thulamela Local Municipality UR - ER -