Ripley's K-function for Network-Constrained Flow Data
Ripley's K-function for Network-Constrained Flow Data
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DOI：
10.1111/gean.12300
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发表时间：
2021-06-29
影响因子：
3.6
通讯作者：
Tang, Luliang
中科院分区：
文献类型：
--
作者：
Kan, Zihan;Kwan, Mei-Po;Tang, Luliang
包括行人流和车流在内的多种空间流都受到空间网络的约束并分布在空间网络上。在文献中，网络约束流通常被建模为平面空间中的直线，使用为平面空间中的流设计的方法。此外，在流态的空间统计分析中，距离度量和流的空间随机性假设也对流态的确定有显著影响。在本研究中，我们将平面流的整体和局部Ripley K函数推广到网络空间。网络和平面K-函数的流被应用到检测模式的出租车始发-目的地流数据的道路网络在多个尺度。距离措施和模拟方法在网络和平面Ripley的K函数的效果进行了检查。我们发现，平面K函数是更敏感的规模的变化，并倾向于检测更多的集群流相比，在相同的规模的网络K函数。距离测量和模拟方法对网络约束流模式的检测比网络或平面Ripley K函数的选择有更显著的影响。这项研究表明，距离的措施和假设的空间随机性，必须仔细选择之前，应用流态分析方法，网络约束流和解释流态的结果。
Many types of spatial flows, including pedestrian flows and vehicle flows, are constrained by and distribute on spatial networks. In the literature, network-constrained flows are usually modeled as a direct line in planar space using methods designed for flows in planar space. Further, in spatial statistical analysis of flow patterns, distance measures and the hypothesis of spatial randomness of flows also have a significant impact on the determination of flow patterns. In this study, we extend the global and local Ripley's K functions for planar flows to network space. Both the network and planar K-functions for flows are applied to detect the patterns of taxi Origin-Destination flow data on a road network at multiple scales. The effect of distance measures and simulation methods in the network and planar Ripley's K functions are examined. We found that the planar K function is more sensitive to the changes in scale and tends to detect more clustered flows compared with the network K function at the same scale. Distance measures and simulation methods have a more significant influence on the detection of patterns of network-constrained flows than the selection of the network or planar Ripley's K functions. This study suggests that distance measures and hypotheses of spatial randomness have to be chosen carefully before applying flow pattern analytic methods to network-constrained flows and interpreting the results of flow patterns.