Special Issue "GIS in Sustainable Transportation"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Prof. Dr. Alexandre B. Gonçalves
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Guest Editor
Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Interests: geographical information systems; spatial analysis; optimization; geographic modeling; spatial data algorithms; computational geometry; spatial data infrastructures; applications of spatial data
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Prof. Filipe Moura
Website
Guest Editor
Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Interests: transportation systems; sustainable urban mobility; active modes; travel behaviour; transportation environmental impacts; econometric analysis in transportation; discrete choice modeling in transportation; technological diffusion; spatial analysis of transport activity

Special Issue Information

Dear Colleagues,

Sustainable transportation is a multidisciplinary discipline and research area, requiring the analysis of economic, social, environmental, and technological aspects, taking into account sustainability-related goals, for instance, in the development of universally accessible, safe, environmentally-friendly, and affordable transportation.

Studies in the field of sustainable transportation require adequate information and evaluation tools that use temporal and spatial data. By dealing with spatial phenomena such as the features and environment that are considered in such studies and the capacity to integrate distinct datasets, support spatial and temporal analyses, and communicate analytical results, geographical information systems (GIS) have been extensively used in a range of applications within sustainable transportation research. Recent studies using GIS and sustainable transportation have, for instance, focused on the spatial modeling of active transportation systems (e.g., walkability assessment, design of pedestrian and cycling networks, analysis of bikesharing systems), spatial analysis of resource consumption, emissions of air pollutants and greenhouse gases, or the design of efficient transport infrastructures, policies, and demand management based on spatial attributes or using GIS as a tool for decision-support.

This Special Issue of ISPRS International Journal of Geo-Information will include a selection of contributions on the theory and practice of analysing spatial data and the use of GIS in all aspects within sustainabile transportation studies. We encourage researchers to submit contributions through articles, reviews, case studies, and position papers where the role and contribution of spatial analysis and geospatial techniques in this scope is enhanced. This may include, in a non-exclusive list of potential topics, contributions on:

  • planar, 3D, and spatiotemporal simulation or modeling of data in sustainable transportation studies;
  • methodological aspects of geospatial data analysis impacting transportation;
  • data handling techniques for the spatialization of sustainability-related indicators;
  • case studies concerning the application of GIS modelling and analysis of social equity, economic efficiency, and environmental responsibility of transportation systems;
  • impacts of spatial data models, quality, transformation, and processing in sustainability assessment for transportation;
  • applications for spatial data mining, geovisualization or spatial decision-support systems in sustainable transportation.

Prof. Alexandre Bacelar Gonçalves
Prof. Filipe Moura
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 papers will be 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. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly 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 1000 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.

Published Papers (2 papers)

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Research

Open AccessArticle
A Comparative Study of Several Metaheuristic Algorithms to Optimize Monetary Incentive in Ridesharing Systems
ISPRS Int. J. Geo-Inf. 2020, 9(10), 590; https://doi.org/10.3390/ijgi9100590 - 08 Oct 2020
Abstract
The strong demand on human mobility leads to excessive numbers of cars and raises the problems of serious traffic congestion, large amounts of greenhouse gas emissions, air pollution and insufficient parking space in cities. Although ridesharing is a potential transport mode to solve [...] Read more.
The strong demand on human mobility leads to excessive numbers of cars and raises the problems of serious traffic congestion, large amounts of greenhouse gas emissions, air pollution and insufficient parking space in cities. Although ridesharing is a potential transport mode to solve the above problems through car-sharing, it is still not widely adopted. Most studies consider non-monetary incentive performance indices such as travel distance and successful matches in ridesharing systems. These performance indices fail to provide a strong incentive for ridesharing. The goal of this paper is to address this issue by proposing a monetary incentive performance indicator to improve the incentives for ridesharing. The objectives are to improve the incentive for ridesharing through a monetary incentive optimization problem formulation, development of a solution methodology and comparison of different solution algorithms. A non-linear integer programming optimization problem is formulated to optimize monetary incentive in ridesharing systems. Several discrete metaheuristic algorithms are developed to cope with computational complexity for solving the above problem. These include several discrete variants of particle swarm optimization algorithms, differential evolution algorithms and the firefly algorithm. The effectiveness of applying the above algorithms to solve the monetary incentive optimization problem is compared based on experimental results. Full article
(This article belongs to the Special Issue GIS in Sustainable Transportation)
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Open AccessArticle
Public Traffic Congestion Estimation Using an Artificial Neural Network
ISPRS Int. J. Geo-Inf. 2020, 9(3), 152; https://doi.org/10.3390/ijgi9030152 - 08 Mar 2020
Abstract
Alleviating public traffic congestion is an efficient and effective way to improve the travel time reliability and quality of public transport services. The existing public network optimization models usually ignored the essential impact of public traffic congestion on the performance of public transport [...] Read more.
Alleviating public traffic congestion is an efficient and effective way to improve the travel time reliability and quality of public transport services. The existing public network optimization models usually ignored the essential impact of public traffic congestion on the performance of public transport service. To address this problem, this study proposes a data-based methodology to estimate the traffic congestion of road segments between bus stops (RSBs). The proposed methodology involves two steps: (1) Extracting three traffic indicators of the RSBs from smart card data and bus trajectory data; (2) The self-organizing map (SOM) is used to cluster and effectively recognize traffic patterns embedded in the RSBs. Furthermore, a congestion index for ranking the SOM clusters is developed to determine the congested RSBs. A case study using real-world datasets from a public transport system validates the proposed methodology. Based on the congested RSBs, an exploratory example of public transport network optimization is discussed and evaluated using a genetic algorithm. The clustering results showed that the SOM could suitably reflect the traffic characteristics and estimate traffic congestion of the RSBs. The results obtained in this study are expected to demonstrate the usefulness of the proposed methodology in sustainable public transport improvements. Full article
(This article belongs to the Special Issue GIS in Sustainable Transportation)
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