Urban Form, Transportation, and Environmental Sustainability: New Data, Methods, and Findings

A special issue of Urban Science (ISSN 2413-8851).

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 1875

Special Issue Editors

1. School of Architecture and Art, Central South University, Changsha 410082, China
2. Department of Urban Planning and Design, University of Hong Kong, Hong Kong 999077, China
Interests: urban vitality; urban heat island; air quality; the application of the geographical open data in urban and environmental studies
Special Issues, Collections and Topics in MDPI journals
Department of Urban Planning and Design, University of Hong Kong, Hong Kong 999077, China
Interests: urban economics; air pollution; urban heat island; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Urban areas are on the frontline of addressing issues of global sustainable development, as the design and development of our cities and towns have complex but considerable impacts on the environmental and social patterns. This Special Issue aims to offer a forum to foster new approaches, analyses, and understandings of the physical fabric of cities and towns, transport development and mobility, as well as their environmental effects. The findings will help to promote sustainable urban planning and transportation for creating safer, more vibrant, and healthier cities.

There is a rapidly growing body of literature examining the changes in a number of key environmental performance indicators (e.g., air pollution, energy consumption, green gas emissions, and urban heat island effect) in response to spatial interventions (e.g., land use, the built environment, and transport development) across multiple spatial scales (e.g., neighbourhoods, cities, and regions). However, most previous studies suffer from significant deficiencies and problems, such as inconsistent or controversial conclusions in different study areas, at various spatial scales, or over distinct time periods. Some these difficulties have arisen due to the lack of standardized measures of urban form and transportation (i.e., traffic, mobility, and accessibility), fuzziness in conceptualization and assessment of environmental performance, and endogeneity issues underlying methodological frameworks. The growing availability of fine-grained location-based big data, coupled with new and advanced analytics, largely facilitates the measurements of spatial and temporal dynamics of cities in a timely and accurate manner as well as creates new opportunities to revisit the issues related to urban form, transportation, and environmental sustainability. This Special Issue will highlight the new applications of big data and urban analytics to the environmental challenges faced by an increasingly urbanized and vulnerable world.

This Special Issue encourages high-standard original empirical studies and review articles, which focus on environmental performance and its contributing factors from the perspectives of urban planning and design, transport development, and human mobility. Potential topics may include but are not limited to the following:

  • New methods or theories for quantifying three-dimensional urban forms, transport development, and their environmental impacts;
  • Use of new data in examining urban form, built environment, and environmental sustainability;
  • Environmentally friendly transportation;
  • Dynamic changes in urban form and transport infrastructure and their environmental impacts;
  • Multi-scale analysis of environmental impacts of urban form and transportation;
  • Integrated land use and transportation planning in achieving environmental sustainability;
  • Viewpoints and reviews on conceptualization and measurements of urban form, transportation, and environmental sustainability.

Dr. Anqi Zhang
Dr. Yifu Ou
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. Urban Science is an international peer-reviewed open access quarterly 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 1600 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

  • urban form
  • transportation
  • environmental sustainability
  • urban analytics
  • big data

Published Papers (1 paper)

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Research

15 pages, 1588 KiB  
Article
Interaction between Development Intensity: An Evaluation of Alternative Spatial Weight Matrices
by Manman Li, Mengying Cui and David Levinson
Urban Sci. 2023, 7(1), 22; https://doi.org/10.3390/urbansci7010022 - 09 Feb 2023
Cited by 1 | Viewed by 1235
Abstract
This paper investigates the spatial dependency of job and worker densities for the Minneapolis–St. Paul (Twin Cities) metropolitan area using census block level data from 2002 to 2017. A spatial weight matrix is proposed, considering the statistical expression of data, referred to as [...] Read more.
This paper investigates the spatial dependency of job and worker densities for the Minneapolis–St. Paul (Twin Cities) metropolitan area using census block level data from 2002 to 2017. A spatial weight matrix is proposed, considering the statistical expression of data, referred to as the correlation matrix, which detects the variations of dependencies among spatial units in both direction and level. The superior performance of the correlation matrix is demonstrated through a series of spatial regression models to predict land use patterns, in comparison with the conventionally used adjacency matrix as well as the accessibility matrix. Full article
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