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Urban Informatics and Applications on Infrastructure for Sustainable Cities
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Urban Informatics and Applications on Infrastructure for Sustainable Cities

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

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 20268

Special Issue Editors

Dr. Manuel Herrera

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Guest Editor
Department of Engineering, University of Cambridge, Cambridge, UK
Interests: water systems; time series analysis; network science
Special Issues, Collections and Topics in MDPI journals
Dr. Marta C. Gonzalez

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Guest Editor
Department of City and Regional Planning, UC Berkeley, 406 Wurster Hall, Berkeley, CA 94720, USA
Interests: human mobility; urban science; network science; complex systems; statistical physics; city & regional planning
Dr. Aristide Athanassiadis

E-Mail Website
Guest Editor
BATir Department - École Polytechnique, Université Libre de Bruxelles, Belgium
Interests: urban metabolism; circular economy; urban and regional planning; industrial ecology; built environment
Prof. Dr. João Porto de Albuquerque

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Guest Editor
Institute for Global Sustainable Development, University of Warwick, Coventry CV4 7AL, UK
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The overall objective of this Special Issue is to improve knowledge on developing and using computational methods and complex network analysis on urban infrastructures: communication, transport, and utilities. Our aim is to create suitable frameworks supporting insightful urban computing approaches to aid timely decision-making processes for utility managers, engineers, and other practitioners. City data are growing at an unprecedented speed, and becoming increasingly available. Examples are: taxi trips, surveillance camera data, call detailed records, location based services from smartphones, events from social media, citizen science data, car accident reports, bike sharing information, points-of-interest, traffic sensors, public transportation data, energy meters, contactless transit cards, environmental sensors, among others. How to utilize such large-scale city data towards a more sustainable system? This Special Issue calls for research that utilizes data to gain understanding or develop applications for collective and environmental well being. Contributions are expected to explore new research avenues that combine urban informatics and sustainability. This can be of great value for both academia and stakeholders. In addition, important social benefits are expected from a number of research objectives that ultimately aim to foster green and sustainable solutions based on urban informatics applied to resilient and energy-efficient cities. These objectives include a wide spectrum of subjects, such as: enhancing urban infrastructure resilience to climate change and disaster risks, improving infrastructure management for constantly growing cities, and investigating green and efficient energy solutions for future cities and urban sustainable development, among others.

Dr. Manuel Herrera
Dr. Marta C. Gonzalez
Dr. Aristide Athanassiadis
Dr. João Porto de Albuquerque
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 2400 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

  • graph-theoretical methods and complex and social networks applications to support urban infrastructure system analyses
  • infrastructure resilience for urban development facing adverse scenarios such as climate change, overpopulation, and natural disasters
  • intelligent infrastructure and assets management: connected, sustainable, and urban economic activities
  • data-driven methods to monitor and assess progress towards sustainable development goals
  • green-intelligent infrastructure for energy efficient cities
  • metabolism of cities and city science
  • urban analytics methods on citizen-generated data and volunteered geographic information
  • innovative techniques for urban utility networks management within a smart city framework
  • meta-analysis models development and open-source urban data
  • urban applications of computer vision and artificial intelligence
  • human-natural systems interactions

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Published Papers (3 papers)

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Research

23 pages, 2491 KiB  
Article
Understanding Smart City—A Data-Driven Literature Review
by Johannes Stübinger and Lucas Schneider
Sustainability 2020, 12(20), 8460; https://doi.org/10.3390/su12208460 - 14 Oct 2020
Cited by 60 | Viewed by 8944
Abstract
This paper systematically reviews the top 200 Google Scholar publications in the area of smart city with the aid of data-driven methods from the fields natural language processing and time series forecasting. Specifically, our algorithm crawls the textual information of the considered articles [...] Read more.
This paper systematically reviews the top 200 Google Scholar publications in the area of smart city with the aid of data-driven methods from the fields natural language processing and time series forecasting. Specifically, our algorithm crawls the textual information of the considered articles and uses the created ad-hoc database to identify the most relevant streams “smart infrastructure”, “smart economy & policy”, “smart technology”, “smart sustainability”, and “smart health”. Next, we automatically assign each manuscript into these subject areas by dint of several interdisciplinary scientific methods. Each stream is evaluated in a deep-dive analysis by (i) creating a word cloud to find the most important keywords, (ii) examining the main contributions, and (iii) applying time series methodologies to determine the past and future relevance. Due to our large-scaled literature, an in-depth evaluation of each stream is possible, which ultimately reveals strengths and weaknesses. We hereby acknowledge that smart sustainability will come to the fore in the next years—this fact confirms the current trend, as minimizing the required input of energy, water, food, waste, heat output and air pollution is becoming increasingly important. Full article
(This article belongs to the Special Issue Urban Informatics and Applications on Infrastructure for Sustainable Cities)
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19 pages, 23734 KiB  
Article
Computational Bottom-Up Vulnerability Indicator for Low-Income Flood-Prone Urban Areas
by Edna M. Rodríguez-Gaviria, Sol Ochoa-Osorio, Alejandro Builes-Jaramillo and Verónica Botero-Fernández
Sustainability 2019, 11(16), 4341; https://doi.org/10.3390/su11164341 - 11 Aug 2019
Cited by 11 | Viewed by 3956
Abstract
This study presents the implementation of a methodology for the formulation of a vulnerability indicator for low-income urban territories in flood-prone areas, for two flood types: Sudden and slow. The methodology developed a computational assessment tool based on the Multiple Correspondence Analysis and [...] Read more.
This study presents the implementation of a methodology for the formulation of a vulnerability indicator for low-income urban territories in flood-prone areas, for two flood types: Sudden and slow. The methodology developed a computational assessment tool based on the Multiple Correspondence Analysis and the framework for vulnerability analysis in sustainable science. This approach uses participatory mapping and on-site data. The data collection was easily implemented with free software tools to facilitate its use in low-income urban territories. The method combines the evaluation of experts using the of the traditional approach for the qualification of the variables of vulnerability in its three components (exposure, susceptibility, and resilience), and incorporates a computational method of the correspondence analysis family to formulate the indicators of vulnerability. The results showed that the multiple correspondence analysis is useful for the identification of the most representative variables in the vulnerability assessment, used for the construction of spatial disaggregated vulnerability indicators and therefore the development of vulnerability maps that will help in the short term in disaster risk management, urban planning, and infrastructure protection. In addition, the variables of the susceptibility component are the most representative regardless of the type of flooding, followed by the variables of the exposure component, for sudden flood-prone territories, and the resilience component for slow flood-prone territories. Our findings and the computational tool can facilitate the prioritization of improvement projects and flood risk management on a household, neighborhood, and municipal level. Full article
(This article belongs to the Special Issue Urban Informatics and Applications on Infrastructure for Sustainable Cities)
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14 pages, 2462 KiB  
Article
Spatial Accessibility to Hospitals Based on Web Mapping API: An Empirical Study in Kaifeng, China
by Zhicheng Zheng, Haoming Xia, Shrinidhi Ambinakudige, Yaochen Qin, Yang Li, Zhixiang Xie, Lijun Zhang and Haibin Gu
Sustainability 2019, 11(4), 1160; https://doi.org/10.3390/su11041160 - 22 Feb 2019
Cited by 50 | Viewed by 6048
Abstract
The accessibility of hospital facilities is of great importance not only for maintaining social stability, but also for protecting the basic human right to health care. Traditional accessibility research often lacks consideration of the dynamic changes in transport costs and does not reflect [...] Read more.
The accessibility of hospital facilities is of great importance not only for maintaining social stability, but also for protecting the basic human right to health care. Traditional accessibility research often lacks consideration of the dynamic changes in transport costs and does not reflect the actual travel time of urban residents, which is critical to time-sensitive hospital services. To avoid these defects, this study considered the city of Kaifeng, China, as an empirical case, and directly acquired travel time data for two travel modes to the hospital in different time periods through web mapping API (Application Program Interface). Further, based on travel time calculations, we compared five baseline indicators. For the last indicator, we used the optimal weighted accessibility model to measure hospital accessibility for each residential area. The study discovered significant differences in the frequency and spatial distribution of hospital accessibility using public transit and self-driving modes of transportation. In addition, there is an imbalance between accessibility travel times in the study area and the number of arrivals at hospitals. In particular, different modes of transportation and different travel periods also have a certain impact on accessibility of medical treatment. The research results shed new light on the accessibility of urban public facilities and provide a scientific basis with which local governments can optimize the spatial structure of hospital resources. Full article
(This article belongs to the Special Issue Urban Informatics and Applications on Infrastructure for Sustainable Cities)
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