Evaluation of the Space Syntax Measures Affecting Pedestrian Density through Ordinal Logistic Regression Analysis

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Hacar O. O., GÜLGEN F., Bilgi S.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, vol.9, no.10, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 9 Issue: 10
  • Publication Date: 2020
  • Doi Number: 10.3390/ijgi9100589
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Agricultural & Environmental Science Database, CAB Abstracts, INSPEC, Veterinary Science Database, Directory of Open Access Journals
  • Keywords: space syntax, pedestrian density, axial analysis, visual graph analysis, integration, MOVEMENT, NETWORK, WALKING
  • Yıldız Technical University Affiliated: Yes


This paper examines the relationship between pedestrian density and space syntax measures in a university campus using ordinal logistic regression analysis. The pedestrian density assumed as the dependent variable of regression analysis was categorised in low, medium, and high classes by using Jenks natural break classification. The data elements of groups were derived from pedestrian counts performed in 22 gates 132 times. The counting period grouped in nominal categories was assumed as an independent variable. Another independent was one of the 15 derived measures of axial analysis and visual graphic analysis. The statistically significant model results indicated that the integration of axial analysis was the most reasonable measure that explained the pedestrian density. Then, the changes in integration values of current and master plan datasets were analysed using paired sample t-test. The calculated p-value of t-test proved that the master plan would change the campus morphology for pedestrians.