Abstract
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.
Highlights
A geographic area with buildings to visit and streets where pedestrians can walk encourages people to travel on foot [1,2,3,4,5,6,7,8]
AA and visual graph analysis (VGA) values calculated for 22 gates are given in Tables 1 and 2, respectively
Since the local integrations of AA were calculated for two different radii (r = 3 and r = 6), the total number of measures in the two tables was 16
Summary
A geographic area with buildings to visit and streets where pedestrians can walk encourages people to travel on foot [1,2,3,4,5,6,7,8]. Pedestrians generally prefer to move along linear lines characterised by a minimum number of turns, with movement guided by the perception of visual spaces. These spaces, defined by Hillier [9] as walkable physical environments for pedestrians in city centres where buildings’ density is high, physically coincide with the street network [10]. Space syntax (SS) techniques are often used to analyse pedestrian walking behaviour in an urban environment consisting of street and building configurations. Some recent studies examine the relationships between measures obtained from VGA and pedestrian movements and evaluate them together with AA measures. Pagkratidou et al [23] explored the behaviours of individuals unfamiliar with the Temple University campus using the integration, choice, and connectivity measures of both VGA and AA
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