Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.9
Journals
Sustainability
Special Issues
Advanced Application of Geoinformatics and Artificial Intelligence on Disaster Risk...
sustainability-logo
Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advanced Application of Geoinformatics and Artificial Intelligence on Disaster Risk Management

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 1644

Special Issue Editors

Dr. Weilian Li

E-Mail Website
Guest Editor
lnstitute of Geodesy and Geoinformation, Geoinformation Group, University of Bonn, Bonn, Germany
Interests: virtual geographic environments; disaster representation in 3D; machine learning for geoinformation
Dr. Pierfranco Costabile

E-Mail Website
Guest Editor
Department of Environmental Engineering, University of Calabria, 87036 Rende, CS, Italy
Interests: flood propagation; rainfall-runoff modeling; river networks; hazard communication; surface irrigation; impacts of climate change; lidar; soil erosion and sediment transport
Special Issues, Collections and Topics in MDPI journals
Dr. Lin Fu

E-Mail Website
Guest Editor
School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, China
Interests: virtual geographic environment; three-dimensional geographic information system; spatio-temporal process modeling

Special Issue Information

Dear Colleagues,

In recent years, environmental changes and rapid economic growth have increased the frequency and intensity of disasters, such as COVID-19, floods, earthquakes, hurricanes, etc. Effective disaster risk management contributes to sustainable development. Strengthening research on disaster patterns, causes, and effects plays an important role in improving disaster risk management and environmental sustainability.

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) states to develop, update and disseminate location-based disaster risk information to decision-makers, the general public, and communities at risk based on geospatial information technology, social sensing, and artificial intelligence. Furthermore, we need to understand, predict, and assess disaster risks to reduce disaster loss and prevent future damage to a community, and create a stronger and more resilient environment.

This special issue aims to challenge how to comprehensively utilize geoinformatics, remote sensing, spatial statistics, and geospatial artificial intelligence (GeoAI) to improve disaster risk management and environmental sustainability, multidisciplinary and interdisciplinary approaches are encouraged. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

(1) GeoAI in disaster risk identification, extraction, and assessment

(2) Intelligent networking and social media in disasters

(3) Statistical analysis and risk mapping

(4) New applications of extended reality (XR) in disasters

(5) Virtual Geographic Environments (VGEs) and disaster multi-dimensional representation

(6) Disaster education and risk communication

(7) Disaster intelligent prediction and scenario simulation

We look forward to receiving your contributions.

Dr. Weilian Li
Dr. Pierfranco Costabile
Dr. Lin Fu
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 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

  • disaster risk management
  • resilience and environment sustainability
  • risk communication
  • artificial intelligence
  • geoinformatics

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

18 pages, 1108 KiB  
Article
Research on Integrated Scheduling of Multi-Mode Emergency Rescue for Flooding in Chemical Parks
by Bowen Guo and Wei Zhan
Sustainability 2023, 15(4), 2930; https://doi.org/10.3390/su15042930 - 06 Feb 2023
Cited by 1 | Viewed by 1009
Abstract
As the scale of the chemical park industry continues to expand, the impact of flooding on the park’s people and surrounding environment increases. This paper uses project scheduling theory to optimize the emergency rescue process in order to alleviate the suffering of affected [...] Read more.
As the scale of the chemical park industry continues to expand, the impact of flooding on the park’s people and surrounding environment increases. This paper uses project scheduling theory to optimize the emergency rescue process in order to alleviate the suffering of affected people, promote the sustainable development of society and the environment, and take into account the characteristics of the dynamic evolution of flooding in chemical parks and the periodic renewal of emergency resources. We constructed a proactive–reactive multi-mode emergency rescue integrated scheduling model that aims to minimize the loss of affected people in the early stage of flooding and minimize the sum of the total deviation of the start time and end time of activities before and after reactive scheduling in the later stages of flooding. Furthermore, an ant colony algorithm was designed to solve the constructed model. Next, the effectiveness of the proposed model and solution algorithm was verified using simulations of actual cases. The calculation results show that using proactive–reactive integrated scheduling can improve the efficiency of emergency rescue and reduce the loss of affected people. Moreover, if a multi-mode rescue strategy is adopted, emergency rescue scheduling under four different resource combinations can reduce rescue duration and loss of affected people. The model can provide a decision reference for sustainable emergency rescue scheduling in chemical parks during a flood. Full article
(This article belongs to the Special Issue Advanced Application of Geoinformatics and Artificial Intelligence on Disaster Risk Management)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop