Resilience of Inland Transport Networks to Extreme Events

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

Deadline for manuscript submissions: closed (15 January 2022) | Viewed by 30109

Special Issue Editors


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Guest Editor
Defense University Centre at the Spanish Naval Academy, 36320 Marín, Spain
Interests: offshore rebewable energy; offshore wind; wave energy; tidal energy; hydrodynamics; computational fluid dynamics; physical modelling
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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

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Keywords

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

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Published Papers (4 papers)

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Research

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29 pages, 10399 KiB  
Article
System Criticality of Road Network Areas for Emergency Management Services—Spatial Assessment Using a Tessellation Approach
by Adrian Rohr, Peter Priesmeier, Katerina Tzavella and Alexander Fekete
Infrastructures 2020, 5(11), 99; https://doi.org/10.3390/infrastructures5110099 - 12 Nov 2020
Cited by 9 | Viewed by 4203
Abstract
Emergency management services, such as firefighting, rescue teams and ambulances, are all heavily reliant on road networks. However, even for highly industrialised countries such as Germany, and even for large cities, spatial planning tools are lacking for road network interruptions of emergency services. [...] Read more.
Emergency management services, such as firefighting, rescue teams and ambulances, are all heavily reliant on road networks. However, even for highly industrialised countries such as Germany, and even for large cities, spatial planning tools are lacking for road network interruptions of emergency services. Moreover, dependencies of emergency management expand not only on roads but on many other systemic interrelations, such as blockages of bridges. The first challenge this paper addresses is the development of a novel assessment that captures systemic interrelations of critical services and their dependencies explicitly designed to the needs of the emergency services. This aligns with a second challenge: capturing system nodes and areas around road networks and their geographical interrelation. System nodes, road links and city areas are integrated into a spatial grid of tessellated hexagons (also referred to as tiles) with geographical information systems. The hexagonal grid is designed to provide a simple map visualisation for emergency planners and fire brigades. Travel time planning is then optimised for accessing city areas in need by weighing impaired areas of past events based on operational incidents. The model is developed and tested with official incident data for the city of Cologne, Germany, and will help emergency managers to better device planning of resources based on this novel identification method of critical areas. Full article
(This article belongs to the Special Issue Resilience of Inland Transport Networks to Extreme Events)
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21 pages, 5738 KiB  
Article
Comparison between Geostatistical Interpolation and Numerical Weather Model Predictions for Meteorological Conditions Mapping
by Javier López Gómez, Francisco Troncoso Pastoriza, Enrique Granada Álvarez and Pablo Eguía Oller
Infrastructures 2020, 5(2), 15; https://doi.org/10.3390/infrastructures5020015 - 1 Feb 2020
Cited by 9 | Viewed by 5079
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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17 pages, 5515 KiB  
Article
Model Calibration Methodology to Assess the Actual Lighting Conditions of a Road Infrastructure
by Ana Ogando-Martínez, Francisco Troncoso-Pastoriza, Pablo Eguía-Oller, Enrique Granada-Álvarez and Aitor Erkoreka
Infrastructures 2020, 5(1), 2; https://doi.org/10.3390/infrastructures5010002 - 27 Dec 2019
Cited by 9 | Viewed by 5445
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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29 pages, 7137 KiB  
Review
Review of Laser Scanning Technologies and Their Applications for Road and Railway Infrastructure Monitoring
by Mario Soilán, Ana Sánchez-Rodríguez, Pablo del Río-Barral, Carlos Perez-Collazo, Pedro Arias and Belén Riveiro
Infrastructures 2019, 4(4), 58; https://doi.org/10.3390/infrastructures4040058 - 20 Sep 2019
Cited by 100 | Viewed by 13762
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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