Advancing Urban Resilience Through Enhanced Disaster Response and Recovery

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 7319

Special Issue Editor

Department of Civil and Environmental Engineering, Kennesaw State University, Marietta, GA 30060, USA
Interests: robotics and sensing; smart infrastructure; disaster reconnaissance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This special issue aims to expand the discourse around disaster response and recovery, exploring advancements and innovations that enhance urban resilience. It covers critical aspects of disaster management, including disaster reconnaissance, search and rescue, and long-term recovery strategies. In densely populated urban areas, where the concentration of structures and populations poses complex challenges, advanced strategies and technologies are indispensable. We invite contributions that explore how these methods are transforming disaster response and recovery. Articles may focus on practical solutions and theoretical developments that improve the efficiency and effectiveness of interventions and refine management strategies, ensuring quicker, more effective recovery from disasters. This special issue seeks to showcase a comprehensive approach to disaster management, from initial impact assessment to sustainable long-term recovery.

Dr. Da Hu
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. Buildings 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 2600 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

  • damage assessment
  • disaster reconnaissance
  • building resilience
  • emerging technologies
  • response and recovery

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Published Papers (1 paper)

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Review

32 pages, 4221 KiB  
Review
Integrating Machine Learning and Remote Sensing in Disaster Management: A Decadal Review of Post-Disaster Building Damage Assessment
by Sultan Al Shafian and Da Hu
Buildings 2024, 14(8), 2344; https://doi.org/10.3390/buildings14082344 - 29 Jul 2024
Cited by 10 | Viewed by 6815
Abstract
Natural disasters pose significant threats to human life and property, exacerbated by their sudden onset and increasing frequency. This paper conducts a comprehensive bibliometric review to explore robust methodologies for post-disaster building damage assessment and reconnaissance, focusing on the integration of advanced data [...] Read more.
Natural disasters pose significant threats to human life and property, exacerbated by their sudden onset and increasing frequency. This paper conducts a comprehensive bibliometric review to explore robust methodologies for post-disaster building damage assessment and reconnaissance, focusing on the integration of advanced data collection technologies and computational techniques. The objectives of this study were to assess the current landscape of methodologies, highlight technological advancements, and identify significant trends and gaps in the literature. Using a structured approach for data collection, this review analyzed 370 journal articles from the Scopus database from 2014 to 2024, emphasizing recent developments in remote sensing, including satellite and UAV technologies, and the application of machine learning and deep learning for damage detection and analysis. Our findings reveal substantial advancements in data collection and analysis techniques, underscoring the critical role of machine learning and remote sensing in enhancing disaster damage assessments. The results are significant as they highlight areas requiring further research and development, particularly in data fusion techniques, real-time processing capabilities, model generalization, UAV technology enhancements, and training for the rescue team. These areas are crucial for improving disaster management practices and enhancing community resilience. The application of our research is particularly relevant in developing more effective emergency response strategies and in informing policy-making for disaster-prepared social infrastructure planning. Future research should focus on closing the identified gaps and leveraging cutting-edge technologies to advance the field of disaster management. Full article
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