Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Organic Pattern of Space:: A Space Syntax Analysis of Natural Streets and Street Segments for Measuring Crime and Traffic Accidents
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Urban and Regional Studies.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Rummets naturliga mönster: : En space syntax analys av naturliga gator och gatusegment för att mäta förekomsten av brott och trafikolyckor (Swedish)
Abstract [en]

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.

 

Place, publisher, year, edition, pages
2019.
Series
TRITA-ABE-MBT ; 19695
Keywords [en]
Space Syntax, natural streets, street segments, topology, human sub-system, physical sub-system
National Category
Other Social Sciences
Identifiers
URN: urn:nbn:se:kth:diva-264938OAI: oai:DiVA.org:kth-264938DiVA, id: diva2:1375783
Subject / course
Urban and Regional Planning
Educational program
Degree of Master - Sustainable Urban Planning and Design
Presentation
2019-11-22, 00:00 (English)
Supervisors
Examiners
Available from: 2019-12-06 Created: 2019-12-06 Last updated: 2019-12-06Bibliographically approved

Open Access in DiVA

fulltext(7081 kB)67 downloads
File information
File name FULLTEXT01.pdfFile size 7081 kBChecksum SHA-512
835dc7c62d4abe8d1aab5d621aea737be1d5e17f72e313773e17b92c69c31acfc659aba29a4159f7a0bb80e23ec57a84e0658d2c56da03a8955720560bc0d122
Type fulltextMimetype application/pdf

By organisation
Urban and Regional Studies
Other Social Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 67 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 151 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf