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Special Issue "Geospatial Data and Methods for Sustainable Mobility and Urban Accessibility"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: 20 March 2023 | Viewed by 1276

Special Issue Editors

Dr. Zihan Kan
E-Mail Website
Guest Editor
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
Interests: geospatial data analytics; urban mobility and accessibility; environmental exposure; health geography; GIScience

Special Issue Information

Dear Colleagues,

Modern society is facing the challenge of sustainable mobility. Accessibility and sustainable mobility are central to smart and healthy city development, which not only requires clean travel modes but also involves equitable, healthful, and highly accessible resources and facilities. In recent years, the application and development of new geospatial datasets and methods have provided new possibilities for studying urban mobility and accessibility to support sustainable mobility planning. Our main area of interest is the development and application of geospatial technologies and methods in addressing key issues related to the sustainable mobility and accessibility of urban spaces.

This Special Issue calls for theoretical, methodological, policy, and empirical contributions on the topic of geospatial data and methods for sustainable accessibility and urban mobility. Relevant themes include but are not limited to: geospatial data analysis in transport geography; urban mobility and urban sustainability; and the development and application of new methods, approaches, and analytical frameworks for improving urban sustainability and urban infrastructure accessibility.

Potential topics include, but are not limited to, the following:

  • Sustainable mobility;
  • Analyzing travel behavior using geospatial data;
  • Geospatial data analytics in mobility research;
  • Development and adoption of active travel modes;
  • Environmental impacts of motorized travel;
  • Urban infrastructure accessibility;
  • Transportation equalities;
  • Intelligent transport systems;
  • Human mobility;
  • Transport geography;
  • Transport planning and policy;
  • The recent COVID pandemic and spatial inequalities in mobility and accessibility.

Dr. Zihan Kan
Prof. Dr. Mei-Po Kwan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable cities
  • urban mobility
  • accessibility
  • geospatial analysis
  • big data

Published Papers (2 papers)

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Research

Article
Uncovering Inequalities in Food Accessibility between Koreans and Japanese in 1930s Colonial Seoul Using GIS and Open-Source Transport Analytics Tools
Sustainability 2022, 14(19), 11852; https://doi.org/10.3390/su141911852 - 20 Sep 2022
Viewed by 257
Abstract
This study aimed to investigate the disparities and inequalities in food accessibility in colonial Seoul (Keijo [京城] in Japanese, and Gyeongseong [경성] in Korean) in the 1930s, using a geographic information system (GIS) and open-source transport analytics tools. We specifically focused on the [...] Read more.
This study aimed to investigate the disparities and inequalities in food accessibility in colonial Seoul (Keijo [京城] in Japanese, and Gyeongseong [경성] in Korean) in the 1930s, using a geographic information system (GIS) and open-source transport analytics tools. We specifically focused on the unique social standing of people in the colonial era, namely colonial rulers (Japanese) vs. subjects (Koreans) and examined whether neighborhoods with larger proportions of colonial rulers had more access to food opportunities. For a comprehensive evaluation, we computed food accessibility by multiple transport modes (e.g., public transit and walking), as well as by different time budgets (e.g., 15 min and 30 min) and considered various sets of food options—including rice, meat, seafood, general groceries, vegetables, and fruits—when measuring and comparing accessibility across neighborhoods in colonial Seoul. We took a novel digital humanities approach by synthesizing historical materials and modern, open-source transport analysis tools to compute cumulative opportunity-based accessibility measures in 1930s colonial Seoul. The results revealed that Japanese-dominant neighborhoods had higher accessibility by both public transit and walking than Korean-dominant neighborhoods. The results further suggest that inequality and disparity in food accessibility is observed not only in contemporary society but also in the 1930s, indicating a historically rooted issue. Full article
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Article
Spatiotemporal Evolution of Travel Pattern Using Smart Card Data
Sustainability 2022, 14(15), 9564; https://doi.org/10.3390/su14159564 - 03 Aug 2022
Viewed by 373
Abstract
Automated fare collection (AFC) systems can provide tap-in and tap-out records of passengers, allowing us to conduct a comprehensive analysis of spatiotemporal patterns for urban mobility. These temporal and spatial patterns, especially those observed over long periods, provide a better understanding of urban [...] Read more.
Automated fare collection (AFC) systems can provide tap-in and tap-out records of passengers, allowing us to conduct a comprehensive analysis of spatiotemporal patterns for urban mobility. These temporal and spatial patterns, especially those observed over long periods, provide a better understanding of urban transportation planning and community historical development. In this paper, we explored spatiotemporal evolution of travel patterns using the smart card data of subway traveling from 2011 to 2017 in Shenzhen. To this end, a Gaussian mixture model with expectation–maximization (EM) algorithm clusters the travel patterns according to the frequency characteristics of passengers’ trips. In particular, we proposed the Pareto principle to negotiate diversified evaluation criteria on model parameters. Seven typical travel patterns are obtained using the proposed algorithm. Our findings highlighted that the proportion of each pattern remains relatively stable from 2011 to 2017, but the regular commuting passengers play an increasingly important position in the passenger flow. Additionally, focusing on the busiest commuting passengers, we depicted the spatial variations over years and identified the characters in different periods. Their cross-year usage of smart cards was finally examined to understand the migration of travel patterns over years. With reference to these methods and insights, transportation planners and policymakers can intuitively understand the historical variations of passengers’ travel patterns, which lays the foundation for improving the service of the subway system. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Profiling and Contextualising the Dynamics of Neighbourhood-level Mobility Inequity amid COVID-19 Pandemic: a Case Study in New York City
Authors: Yunzhe Liu; Meixu Chen; Tao Cheng
Author Affiliations: Yunzhe Liu: Deep Medicine, Oxford Martin School, University of Oxford, Oxford; Meixu Chen: Department of Geography, University College London, London; Tao Cheng: SpaceTimeLab, University College London, London, UK.
Highlights: Using network analysis to formulate a time-series mobility metrics for each CT in NYC amid the COVID-19 pandemic Clustering CTs by using the H-K-means algorithm based on their DTW similarities derived from the mobility metrics (Time-series Cluster) Contextualising mobility disparities by using geodemographic analysis (Geodemographic Cluster) Evaluating the interconnections between the Time-series Cluster and Geodemographic Cluster

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