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dc.contributor.authorSsendagi, John Vianney
dc.date.accessioned2024-09-26T08:39:51Z
dc.date.available2024-09-26T08:39:51Z
dc.date.issued2022-09-20
dc.identifier.citationSsendagi, John Vianney. (2022). A GIS based road crash data analysis Kampala City. a case study of Nakawa division. (Unpublished Master’s Dissertation) Makerere University; Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/10570/13451
dc.descriptionA final year project report submitted to the College of Engineering, Design, Art and Technology in partial fulfillment of the requirement for the award of Master of Science in Geo-information Science and Technology of Makerere University.en_US
dc.description.abstractTraffic road crashes rank high among the leading causes of deaths. This issue is more pertinent in developing counties with Uganda being the most affected in the East African region. This issue is further worse in Kampala, which accounts to over 40% of the total annual road crashes. However, to achieve a proper road safety analysis and management system, there must proper data management which is not the case in Kampala and Uganda at large. This is evidenced by the relevant authorities, case in point the UPF which to this date still uses a paper based system to record road crashes as and when they occur. The goal of this research was to therefore to develop a GIS based, road crashes analysis system for Kampala. The methodology mainly involved data collection of previous recorded crashes for the year 2021, additionally the probable causes of these crashes were also compiled. This data was visualized with existing secondary data including road infrastructure, police stations and also the time for patterns and trends. Furthermore, using by using Kernel Density Estimate (KDE), these crash points were modelled for hotspots. The findings revealed hotspots around road sections with increased traffic volume namely road junctions, flyovers and market areas. Additionally, serious crashes were more common than fatal crashes and also motorcyclists were at the highest risk to road crashes. On a temporal scale, road crashes were most in December and serious road crashes were more likely to occur during peak hours. It was concluded therefore, that that human errors are the most pertinent single cause of road crashes with further analysis revealed that it is usually an interplay of various factors during a road crash. Additionally, road junctions and flyovers were found to be more susceptible to road crashes.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectGIS, Road safety, Kampalaen_US
dc.subjectRoad crash dataen_US
dc.titleA GIS based road crash data analysis Kampala City. a case study of Nakawa division.en_US
dc.typeThesisen_US


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