Betweenness-accessibility: Estimating impacts of accessibility on networks

Sarlas, Georgios; Páez, Antonio; Axhausen, Kay W.

doi:10.1016/j.jtrangeo.2020.102680

Cited by 30 publications

(18 citation statements)

References 55 publications

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“…Population is often used as a key variable for travel demand estimation (Choupani & Mamdoohi, 2016) and accessibility analyses (Sarlas, Páez, & Axhausen, 2020). High population density positively affects shared bicycle flows (Faghih-Imani, Eluru, El-Geneidy, Rabbat, & Haq, 2014), and decreases the likelihood of owning more than one car (Soltani & Somenahalli, 2005), thereby promotes sustainability within the transportation sector.…”

Section: Populationmentioning

confidence: 99%

Spatial parameters for transportation: A multi-modal approach for modelling the urban spatial structure using deep learning and remote sensing

Stiller

Wurm

Stark

et al. 2021

JTLU

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A significant increase in global urban population affects the efficiency of urban transportation systems. Remarkable urban growth rates are observed in developing or newly industrialized countries where researchers, planners, and authorities face scarcity of relevant official data or geo-data. In this study, we explore remote sensing and open geo-data as alternative sources to generate missing data for transportation models in urban planning and research. We propose a multi-modal approach capable of assessing three essential parameters of the urban spatial structure: buildings, land use, and intra-urban population distribution. Therefore, we first create a very high-resolution (VHR) 3D city model for estimating the building floors. Second, we add detailed land-use information retrieved from OpenStreetMap (OSM). Third, we test and evaluate five experiments to estimate population at a single building level. In our experimental set-up for the mega-city of Santiago de Chile, we find that the multi-modal approach allows generating missing data for transportation independently from official data for any area across the globe. Beyond that, we find the high-level 3D city model is the most accurate for determining population on small scales, and thus evaluate that the integration of land use is an inevitable step to obtain fine-scale intra-urban population distribution.

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Section: Populationmentioning

confidence: 99%

Spatial parameters for transportation: A multi-modal approach for modelling the urban spatial structure using deep learning and remote sensing

Stiller

Wurm

Stark

et al. 2021

JTLU

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“…Sarlas et al presented the notion of betweennessaccessibility, a network centrality measure that combines the well-studied concepts of network science and transport geography, namely, betweenness with accessibility. They demonstrated through a case study on Zurich map that the proposed metric identifies critical nodes and links whose interdiction hampers a network's serviceability [26]. Scott et al presented a metric for identification of critical transport network links, called Network Robustness Index (NRI), measured as the change in travel-time cost associated with rerouting network traffic should that link become unusable.…”

Section: ) New Interdiction and Vaccine Distribution Strategiesmentioning

confidence: 99%

Effectiveness of Network Interdiction Strategies to Limit Contagion During a Pandemic

2021

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COVID-19 is an infectious disease that has been declared as a global public health emergency by the World Health Organization. Besides claiming over 3 million lives worldwide, COVID-19 led to unprecedented disruption in industrial productivity, trading, and global food supply, resulting in loss of livelihood. Despite initial success in curbing the spread of diseases through a lockdown and rapid vaccine development, human lives are threatened by sudden outbreaks from new strains of the virus. This motivates the conceptualization of effective interdiction policies to inform human mobility in a manner that the damage to lives as well as the economy could be minimized. In this work, we present three interdiction policies that employ machine learning-based network inference on daily infected cases to infer the influence of contagion between neighboring zones. The proposed policies leverage network science concepts such as coloring and clustering to attain time-varying partial or complete travel restrictions. Through extensive simulation experiments, we show that these strategies yield lower infection spread than greedy and random migration-based tie elimination approaches as well as a balance between contagion mitigation and economic gain.

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“…El-Adaway et al used SNA to analyze transportation networks, which proves its effectiveness as a supplementary tool for improving transportation planning [27]. Sarlas et al proposed a new method by combining the indicator of betweenness in social networks with geographical accessibility to estimate real-life urban network accessibility [28]. Chen and Chang illustrated the relationship between connectivity and accessibility and proved that SNA is valid for connectivity assessment [29].…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method

Liu

Chen

Sun

et al. 2021

Journal of Advanced Transportation

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Dockless sharing bikes play an increasingly significant role in transit transfer, especially for the first/last mile. However, it is not always accessible for users to find sharing bicycles. The objective of this paper is to assess the accessibility of dockless sharing bikes from a network perspective, which would provide a decision-making basis not only for potential bike users but also for urban planners, policymakers, and bicycle suppliers to optimize sharing-bike systems. Considering bicycle travel characteristics, a hierarchical clustering algorithm was applied to construct the dockless sharing-bike network. The social network analysis (SNA) method was adopted to assess the accessibility of the bike network. Then, a spatial interaction model was chosen to conduct a correlation analysis to compare the accessibility obtained from the SNA approach. The case study of Shanghai indicates a strong connection between the accessibility and the SNA indicators with the correlation coefficient of 0.779, which demonstrates the feasibility of the proposed method. This paper contributes to a deep understanding of dockless sharing-bike network accessibility since the SNA approach considers both the interaction barriers and the network structure of a bicycle network. The developed methodology requires fewer data and is easy to operate. Thus, it can serve as a tool to facilitate the smart management of sharing bikes for improving a sustainable transportation system.

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Betweenness-accessibility: Estimating impacts of accessibility on networks

Cited by 30 publications

References 55 publications

Spatial parameters for transportation: A multi-modal approach for modelling the urban spatial structure using deep learning and remote sensing

Spatial parameters for transportation: A multi-modal approach for modelling the urban spatial structure using deep learning and remote sensing

Effectiveness of Network Interdiction Strategies to Limit Contagion During a Pandemic

Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method

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