Road network structure and ride-sharing accessibility: A network science perspective

Wang, Mingshu; Chen, Zheyan; Mu, Lan; Zhang, Xuan

doi:10.1016/j.compenvurbsys.2019.101430

Cited by 41 publications

(17 citation statements)

References 40 publications

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“…The number of bus stops and the length of the road network conceptualize the transportation infrastructure around each COVID-19 cluster location. The well-developed transportation infrastructure may result in higher accessibility ( Wang & Mu, 2018 ; Wang, Chen, Mu, & Zhang, 2020 ) and more prosperous commercial conditions, which may, in turn, lead to a high possibility of population movement in the surrounding community of clusters of COVID-19 confirmed cases. Although the direct relationship between medical service and COVID-19 cluster size is not significant, the increments of the POI of clinics and drugstores will cause an increased medical service level, in turn, an increase of COVID-19 cluster size through the intermediate of commercial prosperity.…”

Section: Discussionmentioning

confidence: 99%

Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

You

et al. 2021

Sustainable Cities and Society

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114

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Section: Discussionmentioning

confidence: 99%

Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

You

et al. 2021

Sustainable Cities and Society

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114

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“… Betweenness centrality Reflects the degree of control (power) of the target node on other nodes in the network. Departing from the study of transportation networks, that commonly utilize the “shortest path length” in their calculations ( Wang, Chen, Mu, & Zhang, 2020 ), we use the “maximum flow” between the nodes ( Freeman, Borgatti, & White, 1991 ) for our directed-weighted network:

(5) Where, m jk is the maximum flow from node v j to node v k , i.e. the weight value of the path with the largest weight from node v j to node v k ; m jk (i) is the maximum flow from node v j to node v k that passes through node v i ; n is the total number of nodes.…”

Section: Methodsmentioning

confidence: 99%

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

Zheng

Mou

Zhang

et al. 2021

Computers, Environment and Urban Systems

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Geo-located travel blogs, a new data source, enable to achieve more detailed analysis of tourists' spatio-temporal behavior. Taking Chinese tourists in Nordic countries as the research object, this paper focuses on their behavior, seasonal patterns and complex network effects by using geo-located travel blog data collected from Qunar.com . The results show that: (1) Chinese tourists visiting Nordic countries are often experienced in traveling. The local climate during the cold season does not prevent them from pursuing the aurora scenery. (2) The travel behavior of Chinese tourists is spatially heterogeneous. The network analysis reveals that Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect. (3) During the warm season, Chinese tourists choose a variety of destinations, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights. These results provide helpful information for the tourism management departments of Nordic countries to improve their marketing and development efforts directed for Chinese tourists.

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“…The nodes are the intersections formed by road segments and dead ends, and the links are the road segments themselves that connect the nodes. To quantitatively characterize the topological properties of road networks, various measures have been used in the literature, including network centrality measures such as betweenness centrality [13,27,34,37,51,52], closeness centrality [13,50,[53][54][55], degree centrality [13,45,[56][57][58][59] and clustering coefficient [35]. Each measure can be used to capture a certain property of the road networks.…”

Section: Network Sciencementioning

confidence: 99%

A Geometric Classification of World Urban Road Networks

et al. 2022

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This article presents a method to uncover universal patterns and similarities in the urban road networks of the 80 most populated cities in the world. To that end, we used degree distribution, link length distribution, and intersection angle distribution as topological and geometric properties of road networks. Moreover, we used ISOMAP, a nonlinear dimension reduction technique, to better express variations across cities, and we used K-means to cluster cities. Overall, we uncovered one universal pattern between the number of nodes and links across all cities and identified five classes of cities. Gridiron Cities tend to have many 90° angles. Long Link Cities have a disproportionately high number of long links and include mostly Chinese cities that developed towards the end of the 20th century. Organic Cities tend to have short links and more non-90 and 180° angles; they also include relatively more historical cities. Hybrid Cities tend to have both short and long links; they include cities that evolved both historically and recently. Finally, Mixed Cities exhibit features from all other classes. These findings can help transport planners and policymakers identify peer cities that share similar characteristics and use their characteristics to craft tailored transport policies.

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Road network structure and ride-sharing accessibility: A network science perspective

Cited by 41 publications

References 40 publications

Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

A Geometric Classification of World Urban Road Networks

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