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The Organic Pattern of Space: : A Space Syntax Analysis of Natural Streets and Street Segments for Measuring Crime and Traffic Accidents / Rummets naturliga mönster: : En space syntax analys av naturliga gator och gatusegment för att mäta förekomsten av brott och trafikolyckor

The natural streets model is a research prototype that has been shown to perform better than the conventional GIS-based streets segments for explaining traffic flow and human movement. However, given its experimental status, a gap in the literature was identified. Therefore, the aim of this thesis was to contribute to the literature by investigating the wider applications of natural streets and observe whether a city’s spatial configuration (or structure) is related to outcomes of human behaviour and activity. In this case, the two previously unstudied outcomes were chosen: crime and traffic accidents. Taking an exploratory approach, Stockholm was chosen as the case study. Using the space syntax methodology, the street segments and natural streets connectivity was used to analyse whether accessibility or ‘potential through movement’ is associated with crime and traffic accidents. Two study areas were generated: a primary study area consisting of six nested zones and a secondary study area with hot spots and cold spots for events of crime and traffic accidents. To observe the statistical association between connectivity and events of crime and traffic accidents for natural streets and street segments, a classical regression model was used. The regression analysis showed that natural streets perform significantly better than street segments as they are better able to explain events of crime and traffic accidents. However, more so for traffic accidents. Most importantly, the topological structure or scaling characteristics of natural streets served as a better indicator for measuring human phenomena. The implication of this is that it could potentially be used to further the understanding of human activities in the context of the urban environment.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-264938
Date January 2019
CreatorsAttig, Stefan
PublisherKTH, Urbana och regionala studier
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationTRITA-ABE-MBT ; 19695

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