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Sustainable Disaster Risk Management and Urban Resilience
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Sustainable Disaster Risk Management and Urban Resilience

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: 10 September 2025 | Viewed by 6791

Special Issue Editor

Dr. Jaime Santos-Reyes

E-Mail Website
Guest Editor
Systems Engineering Department, SEPI-ESIME, Zac., National Polytechnic Institute, Mexico City 07738, Mexico
Interests: natural and technological risk perception; hazard awareness; natural and technological hazard management systems; emergency response systems; earthquake early warning; human behavior during a seismic emergency
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As global urbanization continues to grow, cities become more vulnerable and less resilient to disasters triggered by natural and technological hazards. Frequently, disasters trigger cascading effects causing devastating consequences in terms of loss of life or injury, property loss or damage, and disruption of operation. Driven by the impact of disasters and the need to address environmental concerns, a multidisciplinary approach to disaster risk management and urban resilience is needed. The aim of this Special Issue is to create a forum for discussing these issues from a multidisciplinary point of view. It is hoped that this interchange of experiences, approaches, and new ideas will help to advance to the challenge of reducing disaster risks.

This Special Issue aims to cover, without being limited to, the following areas:

  • Decision-making process in disaster and risk management;
  • Hazard awareness and risk perception;
  • Risk assessment, resilience, and vulnerability assessment;
  • Emergency response systems;
  • Early warning systems;
  • Preparedness before and during the emergency;
  • Building local community and urban resilience;
  • Disasters and individuals with special healthcare needs;
  • Evacuation drills (or exercises);
  • Risk communication;
  • NaTech events and disasters;
  • Social media and disasters;
  • Disaster risk and traditional knowledge solutions.

Dr. Jaime Santos-Reyes
Guest Editor

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

  • risk
  • disaster
  • resilience
  • vulnerability
  • early warning
  • emergency response

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Published Papers (4 papers)

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Research

24 pages, 1308 KiB  
Article
A Bibliometric Analysis of Multi-Criteria Decision-Making Techniques in Disaster Management and Transportation in Emergencies: Towards Sustainable Solutions
by Ezgi Aktas Potur, Ahmet Aktas and Mehmet Kabak
Sustainability 2025, 17(6), 2644; https://doi.org/10.3390/su17062644 - 17 Mar 2025
Cited by 1 | Viewed by 1019
Abstract
Disaster management minimizes potential harm and protects populations across four phases: preparedness, mitigation, response, and recovery. Diverse scientific approaches could be applied at each phase, among which Multi-Criteria Decision-Making (MCDM) methods are widely recognized and utilized. Their integration provides a systematic framework for [...] Read more.
Disaster management minimizes potential harm and protects populations across four phases: preparedness, mitigation, response, and recovery. Diverse scientific approaches could be applied at each phase, among which Multi-Criteria Decision-Making (MCDM) methods are widely recognized and utilized. Their integration provides a systematic framework for prioritizing disaster-related criteria, optimizing resource use, and minimizing environmental impact, ultimately enhancing community resilience. This study conducts a bibliometric analysis to identify pioneering researchers, leading institutions, contributing countries, and interaction levels working on MCDM methods in disaster management and emergency transportation, as well as to reveal key trends. 365 Web of Science and Scopus publications (2000–2024) were analyzed using the Bibliometrix tool in R. As a significant outcome, three important clusters emerged: Disaster Planning and Logistics, Risk and Resilience, and Crisis Response and Decision Support. The interplay between these clusters and the methodologies shaping them was highlighted, alongside insights from the most recent studies. This study could serve as a roadmap for future research, guiding efforts to address gaps such as real-time applications, multi-hazard integration, and scalability. It contributes to the limited body of research on MCDM in disaster management and emergency transportation, laying the groundwork for upcoming studies that could enhance resilience and promote sustainable development. Full article
(This article belongs to the Special Issue Sustainable Disaster Risk Management and Urban Resilience)
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15 pages, 7250 KiB  
Article
Machine Learning Prediction of Co-Seismic Landslide with Distance and Azimuth Instead of Peak Ground Acceleration
by Yang Shi, Zhenguo Zhang, Changhu Xue and Yu Feng
Sustainability 2024, 16(19), 8332; https://doi.org/10.3390/su16198332 - 25 Sep 2024
Cited by 1 | Viewed by 1562
Abstract
Most machine learning (ML) studies on predicting co-seismic landslides have relied on Peak Ground Acceleration (PGA). The PGA of the ground strongly correlates with the relative position and azimuth of the seismogenic faults. Using the co-seismic landslide records of the 2008 Wenchuan earthquake, [...] Read more.
Most machine learning (ML) studies on predicting co-seismic landslides have relied on Peak Ground Acceleration (PGA). The PGA of the ground strongly correlates with the relative position and azimuth of the seismogenic faults. Using the co-seismic landslide records of the 2008 Wenchuan earthquake, we show that the ML model using the distances and azimuths from the epicenter to sites performs better than the PGA model regarding accuracy and actual prediction results. The distances and azimuths are more accessible than the PGA because obtaining accurate and realistic large-scale PGAs is difficult. Considering their computational efficiency and cost-effectiveness, the ML models utilizing distances and azimuths from the epicenter to the sites as inputs could be an alternative to PGA-based models for evaluating the impact of co-seismic landslides. Notably, these models prove advantageous in near-real-time scenarios and settings requiring high spatial resolution, and provide favorable assistance in achieving the goal of sustainable development of society. Full article
(This article belongs to the Special Issue Sustainable Disaster Risk Management and Urban Resilience)
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25 pages, 7200 KiB  
Article
Identification and Management of Epidemic Hazard Areas for Urban Sustainability: A Case Study of Tongzhou, China
by Ming Sun and Tiange Xu
Sustainability 2024, 16(18), 7945; https://doi.org/10.3390/su16187945 - 11 Sep 2024
Cited by 1 | Viewed by 1072
Abstract
The global epidemic is relatively stable, but urban pandemics will still exist. This study used sDNA (spatial design network analysis), spatial autocorrelation, and GWR (geographically weighted regression analysis) to identify potentially risky roads, pandemic hazard areas, and various infrastructure hazard areas in the [...] Read more.
The global epidemic is relatively stable, but urban pandemics will still exist. This study used sDNA (spatial design network analysis), spatial autocorrelation, and GWR (geographically weighted regression analysis) to identify potentially risky roads, pandemic hazard areas, and various infrastructure hazard areas in the Tongzhou District for urban sustainability. The results show that urban roads at risk during an epidemic have high proximity and aggregation effects. These roads are mainly concentrated in the core area. The hazard identification areas are focused on the urban sub-center and Yizhuang New Town. This paper derives the actual hazard areas using the POI (points of interest) data of COVID-19 (coronavirus disease 2019) and compares the results with the hazard identification areas. It is found that the hazard identification areas do not show the actual hazard area completely. In this study, GWR analyses based on gridded data of infrastructure POI proximity are used to obtain the hazard areas of various infrastructure types and develop different control ranges and methods. This provides new perspectives for identifying priority areas for epidemic prevention, control, and sustainable urban development. Full article
(This article belongs to the Special Issue Sustainable Disaster Risk Management and Urban Resilience)
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22 pages, 1662 KiB  
Article
A Tale of Five Cities: Assessing Emergency Management for Future Disasters in the United States
by Madison Tlachac, Lisa L. Greenwood and Jennifer L. Schneider
Sustainability 2024, 16(17), 7419; https://doi.org/10.3390/su16177419 - 28 Aug 2024
Cited by 1 | Viewed by 2596
Abstract
Many cities across the United States (U.S.) face threats from natural hazards, and as climate change continues to worsen, cities will face increased risks. Emergency management helps cities to mitigate these risks and adapt to shifting threats. Based on the Rockefeller City Resilience [...] Read more.
Many cities across the United States (U.S.) face threats from natural hazards, and as climate change continues to worsen, cities will face increased risks. Emergency management helps cities to mitigate these risks and adapt to shifting threats. Based on the Rockefeller City Resilience Framework and City Resilience Index Driver 3, Indicator 3.4, the scope of this research was to develop an emergency management maturity model and explore emergency management capacity for future disasters based on an assessment of five cities across the U.S. With the resulting data, a city’s score would serve as an evaluation of the emergency response indicator (Indicator 3.4) in order to eventually enter the City Resilience Index. The cities selected were Buffalo, New York; Honolulu, Hawaii; Memphis, Tennessee; New Orleans, Louisiana; and Saint Paul, Minnesota, based on their hazard/risk factors. It should be noted that these scores were intended to compare resilience in a city over time and identify unique areas in which the cities could improve emergency management and were not meant to rank the cities against each other. An interesting find was the overlap between the counties and cities regarding policy data, creating a new avenue for research in local level emergency management. Full article
(This article belongs to the Special Issue Sustainable Disaster Risk Management and Urban Resilience)
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