A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Resolving urban mobility networks from individual travel graphs using massive-scale mobile phone tracking data
Abstract Human movements and interactions with cities are characterized by urban mobility networks. Many studies that address urban mobility are inspired by complex networks. The models of complex networks require a large amount of empirical data. However, current works relied on traditional survey data and were unable to take full advantage of the capabilities offered by complex networks; thus, the possibility of quantifying urban mobility networks by considering individual travel patterns has not yet been addressed. This study presents a data-driven approach for characterizing urban mobility networks based on massive-scale mobile phone tracking data. Individual travel motifs are first extracted using a graph-based approach. The global urban mobility network (G-UMN) and the motif-dependent urban mobility subnetworks (MD-UMNs) are then constructed. Next, network properties, including statistical measures and scaling relations between the basic measures, are proposed for characterizing mobility networks. We have conducted experiments focusing on Shenzhen, China. The results demonstrated that (1) the individual travel motifs are structurally and spatially heterogeneous, (2) the G-UMN exhibits a evolutionary hierarchical structure, and (3) the MD-UMNs show many behavioral differences in their spatial and topological properties, reflecting the impacts of the heterogeneity of the individual travel motifs. These results bridge the gap between complex network properties and urban mobility patterns and provide crucial implications and policies for data-informed urban planning.
Highlights Urban mobility networks are resolved using mobile phone tracking data Nine individual travel motifs are extracted, presenting structurally and spatially heterogeneous The global and the motif-dependent mobility networks are characterized by complex-network measures and scaling relations The global urban mobility network is neither purely scale-free nor completely random, exhibits a hierarchical structure The motif-dependent urban mobility networks show differences in their spatial and topological properties
Resolving urban mobility networks from individual travel graphs using massive-scale mobile phone tracking data
Abstract Human movements and interactions with cities are characterized by urban mobility networks. Many studies that address urban mobility are inspired by complex networks. The models of complex networks require a large amount of empirical data. However, current works relied on traditional survey data and were unable to take full advantage of the capabilities offered by complex networks; thus, the possibility of quantifying urban mobility networks by considering individual travel patterns has not yet been addressed. This study presents a data-driven approach for characterizing urban mobility networks based on massive-scale mobile phone tracking data. Individual travel motifs are first extracted using a graph-based approach. The global urban mobility network (G-UMN) and the motif-dependent urban mobility subnetworks (MD-UMNs) are then constructed. Next, network properties, including statistical measures and scaling relations between the basic measures, are proposed for characterizing mobility networks. We have conducted experiments focusing on Shenzhen, China. The results demonstrated that (1) the individual travel motifs are structurally and spatially heterogeneous, (2) the G-UMN exhibits a evolutionary hierarchical structure, and (3) the MD-UMNs show many behavioral differences in their spatial and topological properties, reflecting the impacts of the heterogeneity of the individual travel motifs. These results bridge the gap between complex network properties and urban mobility patterns and provide crucial implications and policies for data-informed urban planning.
Highlights Urban mobility networks are resolved using mobile phone tracking data Nine individual travel motifs are extracted, presenting structurally and spatially heterogeneous The global and the motif-dependent mobility networks are characterized by complex-network measures and scaling relations The global urban mobility network is neither purely scale-free nor completely random, exhibits a hierarchical structure The motif-dependent urban mobility networks show differences in their spatial and topological properties
Resolving urban mobility networks from individual travel graphs using massive-scale mobile phone tracking data
Cao, Jinzhou (author) / Li, Qingquan (author) / Tu, Wei (author) / Gao, Qili (author) / Cao, Rui (author) / Zhong, Chen (author)
Cities ; 110
2020-12-17
Article (Journal)
Electronic Resource
English
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