Spatio-Temporal Analysis of Crime Patterns Using Geographic Information System Methodologies in Nairobi City County, Kenya

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dc.contributor.advisorShadrack Murimien_US
dc.contributor.advisorPhilomena Muirurien_US
dc.contributor.authorOwino, Okode Polive
dc.date.accessioned2022-03-23T13:22:57Z
dc.date.available2022-03-23T13:22:57Z
dc.date.issued2021
dc.descriptionA Thesis Submitted to the Department of Geography in Partial Fulfillment of the Requirements for the Award of the Degree of Master of Arts Geography (Urban and Regional Planning) in the School of Humanities and Social Sciences, Kenyatta University, November, 2021en_US
dc.description.abstractThis study analysed spatio-temporal crime patterns using Geographic Information System methodologies in Kasarani, Nairobi City County, Kenya. Kasarani ward is one of the areas with high concentrations of crime. The Kenya National Police Service lists Kasarani ward among the crime hot spots in Nairobi City County. The study focused on crimes on persons and property. Quantitative and qualitative data collection was conducted in two phases. First, questionnaires, focus group discussions, and interview schedules were used to collect data from members of the public and key informants. Secondly, the Global Positioning System receiver was used to collect coordinates of the crime hot spots in the area identified through participatory Geographic Information System. Statistical Package for Social Sciences version 21 was used for data processing and analysis. Percentages and frequencies were used to describe, analyse and summarize the data. Paired sample T-test was conducted to test research null hypotheses to establish relationships between variables. All the null hypotheses were rejected as there was a significant relationship (p≤0.05). The conclusion that emerges is that crime is not randomly dispersed across space but concentrates in particular areas and at specific times. Several push and pull factors were identified as perpetuating crimes on person and property in the area. Poor police patrols were attributed to contributing to crime occurrences in Kasarani. Geographic Information System was used to map and analyse crime hot spot attributes in the area. The analysis entailed creation of the attribute table with information on crime hot spot names, crime types, number of crime types per hot spot, and coordinates of latitude and longitude. The geodatabase layers were added into the ArcMap desktop version 10.5.1. and then overlaid to form crime hot spot maps. In an era where criminals have taken their game higher, urban security managers need to match their fight by engaging the use of GIS for mapping crime hot spots. The benefit of GIS in crime mapping and analysis is that it possesses capabilities to identify crime trends necessary for advising police officers on areas to intensify their patrols. This study reinforces a recommendation that has already been made in other studies about the need for concerned government agencies to roll out plans aimed at addressing factors perpetuating crimes on person and property. One such is the need for the government, through the Ministry of Interior and Coordination of National Government, to embrace the use of GIS in the Police department for crime mapping and analysis. The tool will inform the government decision making in resource allocation, such as assigning police patrol vehicles in places recording high cases of crime at particular times. GIS enable digital automation of OB records and linking them with geo-location of crime hot spotsen_US
dc.description.sponsorshipKenyatta Universityen_US
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/23324
dc.language.isoenen_US
dc.publisherKenyatta Universityen_US
dc.subjectSpatio-Temporal Analysisen_US
dc.subjectCrime Patternsen_US
dc.subjectGeographic Information System Methodologiesen_US
dc.subjectNairobi City Countyen_US
dc.subjectKenyaen_US
dc.titleSpatio-Temporal Analysis of Crime Patterns Using Geographic Information System Methodologies in Nairobi City County, Kenyaen_US
dc.typeThesisen_US
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