Special Issue "Resilience of Inland Transport Networks to Extreme Events"

A special issue of Infrastructures (ISSN 2412-3811).

Deadline for manuscript submissions: closed (30 May 2020).

Special Issue Editors

Dr. Belén Riveiro
Website
Guest Editor
Universidade de Vigo, CINTEX, GeoTech Lab, Campus Universitario de Vigo, As Lagoas, Marcosende, 36310 Vigo, Spain
Interests: laser scanning; structural monitoring; resilience of infrastructure
Special Issues and Collections in MDPI journals
Dr. Carlos Perez-Collazo
Website SciProfiles
Guest Editor
School of Mines and Energy Engineering, University of Vigo, R./ Maxwell s/n, Vigo 36310, Spain
Interests: remote monitoring of transport infrastructures; infrastructure modeling; coastal infrastructure monitoring; renewable energy systems; offshore renewable energy; hydrodynamic modeling; computational fluid dynamics; wave energy; project management

Special Issue Information

Dear Colleagues,

It is well known that modern society is becoming increasingly dependent on transportation networks for its daily activities. The ability of transport systems to operate during adverse conditions and quickly recover to acceptable levels of service after an extreme event occurs is fundamental to the wellbeing of citizens.

The transport sector is well aware of the increasing number of extreme events, which are mainly natural (where climate change plays an important role), but also manmade (e.g., accidents, negligence, vandalism, and terrorism). Therefore, actions are required to mitigate the impact of such situations. In recent years, strategies to reduce risk vulnerability and to strengthen network systems with respect to extreme events have increased in demand. Thus, the design, validation, and implementation of new holistic methods, strategies, and tools are needed for inland transport infrastructures to increase their resilience. In addition to the aforementioned threats, transport networks’ reliability is also limited by the condition of the infrastructure; however, risk management systems (RMS) rarely consider infrastructure preservation. Infrastructure management (IM) requires knowledge about the costs and effectiveness of medium- to long-term actions taking extreme natural and manmade events into account. In the short term, resilience is influenced by efficient recovery, which will depend on the incorporation of Big Data and smart ICT into emergency plans, as well as real-time, optimized communication with operators and end-users (via crowdsourcing and social media).

In this context, universities, private companies, transport operators, and public administrations are developing and validating new methods, tools, and strategies to build safer and more resilient infrastructures.

The goal of this Special Issue is to publish original technical and research papers focused on innovative methodologies and approaches to improve the resilience of transport infrastructures in their different dimensions, including, but not limited to, the following:

  • Investigations focused on identification and mapping of extreme weather conditions that can anticipate the malfunctioning of terrestrial transport networks.
  • Methodologies to better understand the magnitude of the consequences of extreme events for transport infrastructure.
  • Technologies and methodologies for more efficient monitoring of infrastructure assets, including large-scale monitoring using remote sensing, contact sensors, connected vehicles, social media, infrastructure information modeling, etc.
  • Structural health monitoring of infrastructure facilities and condition evaluation by using innovative methods.
  • Development of predictive models for projecting risks of future infrastructure damage, shutdown, and deterioration.
  • Optimization of decision support systems.
  • New maintenance strategies.

Dr. Belén Riveiro
Dr. Carlos Perez-Collazo
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. Infrastructures 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.

Keywords

  • Resilience
  • Natural hazards
  • Manmade disasters
  • Structural health monitoring
  • Remote sensing
  • Infrastructure information models
  • Predictive modelling
  • Risk assessment

Published Papers (3 papers)

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Research

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Open AccessArticle
Comparison between Geostatistical Interpolation and Numerical Weather Model Predictions for Meteorological Conditions Mapping
Infrastructures 2020, 5(2), 15; https://doi.org/10.3390/infrastructures5020015 - 01 Feb 2020
Cited by 2
Abstract
Mapping of meteorological conditions surrounding road infrastructures is a critical tool to identify high-risk spots related to harsh weather. However, local or regional data are not always available, and researchers and authorities must rely on coarser observations or predictions. Thus, choosing a suitable [...] Read more.
Mapping of meteorological conditions surrounding road infrastructures is a critical tool to identify high-risk spots related to harsh weather. However, local or regional data are not always available, and researchers and authorities must rely on coarser observations or predictions. Thus, choosing a suitable method for downscaling global data to local levels becomes essential to obtain accurate information. This work presents a deep analysis of the performance of two of these methods, commonly used in meteorology science: Universal Kriging geostatistical interpolation and Weather Research and Forecasting numerical weather prediction outputs. Estimations from both techniques are compared on 11 locations in central continental Portugal during January 2019, using measured data from a weather station network as the ground truth. Results show the different performance characteristics of both algorithms based on the nature of the specific variable interpolated, highlighting potential correlations to obtain the most accurate data for each case. Hence, this work provides a solid foundation for the selection of the most appropriate tool for mapping of weather conditions at the local level over linear transport infrastructures. Full article
(This article belongs to the Special Issue Resilience of Inland Transport Networks to Extreme Events)
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Open AccessArticle
Model Calibration Methodology to Assess the Actual Lighting Conditions of a Road Infrastructure
Infrastructures 2020, 5(1), 2; https://doi.org/10.3390/infrastructures5010002 - 27 Dec 2019
Cited by 2
Abstract
Street lighting plays an important role in the comfort and safety of drivers and pedestrians, so the control and management of the lighting systems operation and consumption is an essential service for a city. In this document, a methodology is presented to calibrate [...] Read more.
Street lighting plays an important role in the comfort and safety of drivers and pedestrians, so the control and management of the lighting systems operation and consumption is an essential service for a city. In this document, a methodology is presented to calibrate lighting models in order to assess the lighting performance through simulation techniques. The objective of this calibration is to identify the maintenance factor of the street lamps, determine the real average luminance coefficient of the road pavement and adapt the reflection properties of the road material. The method is applied in three stages and is based on the use of Radiance and GenOpt software suits for the modeling, simulation, and calibration of lighting scenes. The proposed methodology achieves errors as low as 13% for the calculation of illuminance and luminance, evincing its potential to assess the actual lighting conditions of a road. Full article
(This article belongs to the Special Issue Resilience of Inland Transport Networks to Extreme Events)
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Review

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Open AccessReview
Review of Laser Scanning Technologies and Their Applications for Road and Railway Infrastructure Monitoring
Infrastructures 2019, 4(4), 58; https://doi.org/10.3390/infrastructures4040058 - 20 Sep 2019
Cited by 6
Abstract
Improving the resilience of infrastructures is key to reduce their risk vulnerability and mitigate impact from hazards at different levels (e.g., from increasing extreme events, driven by climate change); or from human-made events such as: accidents, vandalism or terrorist actions. One of the [...] Read more.
Improving the resilience of infrastructures is key to reduce their risk vulnerability and mitigate impact from hazards at different levels (e.g., from increasing extreme events, driven by climate change); or from human-made events such as: accidents, vandalism or terrorist actions. One of the most relevant aspects of resilience is preparation. This is directly related to: (i) the risk prediction capability; (ii) the infrastructure monitoring; and (iii) the systems contributing to anticipate, prevent and prepare the infrastructure for potential damage. This work focuses on those methods and technologies that contribute to more efficient and automated infrastructure monitoring. Therefore, a review that summarizes the state of the art of LiDAR (Light Detection And Ranging)-based data processing is presented, giving a special emphasis to road and railway infrastructure. The most relevant applications related to monitoring and inventory transport infrastructures are discussed. Furthermore, different commercial LiDAR-based terrestrial systems are described and compared to offer a broad scope of the available sensors and tools to remote monitoring infrastructures based on terrestrial systems. Full article
(This article belongs to the Special Issue Resilience of Inland Transport Networks to Extreme Events)
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