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.

中文翻译：

---

通过序数Logistic回归分析评估影响行人密度的空间句法测度

本文使用序数逻辑回归分析研究了大学校园中行人密度与空间句法测度之间的关系。通过使用Jenks自然中断分类法，将被假定为回归分析的因变量的行人密度分为低，中和高级类别。组的数据元素来自132个门的22次门的行人计数。按名义类别分组的计数期被假定为自变量。另一个独立因素是轴向分析和视觉图形分析的15种衍生措施之一。具有统计意义的模型结果表明，轴向分析的集成是解释行人密度的最合理方法。然后，t检验 计算的t检验的p值证明，总体规划会改变行人的校园形态。