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

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...

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Bibliographic Details
Published in:ISPRS international journal of geo-information 2020-10, Vol.9 (10), p.589
Main Authors: Hacar, Özge, Gülgen, Fatih, Bilgi, Serdar
Format: Article
Language:English
Subjects:
axial analysis
Buildings
Cities
College campuses
Connectivity
Counting
Density
Dependent variables
Geographic information systems
Independent variables
Integration
Morphology
pedestrian density
Pedestrians
Regression analysis
space syntax
Statistical analysis
Syntax
visual graph analysis
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Summary: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.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi9100589