Special Issue "Human-Induced Disaster and Conflict Analysis, Prediction, and Prevention by Geospatial Analytics and Information Systems"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Dr. Maria Antonia Brovelli
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Interests: geospatial web; geodata science; citizen science; open science; open data; open geospatial software; geospatial artificial intelligence
Special Issues and Collections in MDPI journals
Mr. Timur Obukhov
E-Mail Website
Guest Editor Assistant
Data Science Ph.D. Program at the Sapienza University of Rome, Rome, Italy
Interests: geospatial analysis; remote sensing; open-source data and technology

Special Issue Information

Dear Colleagues,

In the last fifty years, the number of annual counts of disasters has increased from around 60 to over 400. Various disasters kill over 60,000 people a year and cost hundreds of billions of US dollars (https://ourworldindata.org/natural-disasters). The geospatial understanding of the underlying factors that induce and influence disasters is often critical for analyzing and detecting them and possibly identifying the patterns that can lead to and/or help to predict similar disasters in the future. This Special Issue focuses on disasters that can be traced directly or indirectly to human actions, such as hazardous material spills, fires, groundwater contamination, transportation accidents, structure failures, mining accidents, explosions, and acts of terrorism, as well as conflicts and related damages. In addition, the amount of publicly available data that can be used to analyze and understand disaster nature is massive. Often, these data are inhomogeneous, inconsistent, and unstructured. Thus, they require innovative methods and tools for collection, processing, and transformation into datasets that can be analyzed and interpreted for practitioners to enhance their knowledge and understanding. This Special Issue invites researchers and practitioners to submit original work related to the entire spectrum of data analysis processes for disaster-related studies. We welcome practitioners and political and social scientists to present their requirements for the tools and processes needed for their daily work. We also welcome researchers presenting various methodologies to collect, process, and convert contextual and inconsistent publicly available data into ready-to-analyze geospatial datasets. Furthermore, we welcome submissions that focus on developing models for disaster-related data analysis. Submissions from cross-cutting disciplines such as climate change, environmental, political, social, data, and geospatial data science and others are welcome. Topics include but are not limited to the following:

  • Innovative geospatial data and crowdsourced information (such as volunteered geographic information, collaborative maps, social media) for analysis and prevention of human-induced disasters and conflicts;
  • Disaster/conflict assessment and mapping;
  • Spatiotemporal monitoring of disaster and conflicts;
  • Event detection and prediction regarding human-induced disaster and conflicts;
  • Geospatial planning tools for disaster/conflict prevention and humanitarian actions to alleviate the effects of human-induced disasters and conflicts;
  • Geospatial data science applied to disaster/conflict analysis and prevention;
  • Collaborative web geospatial platforms for humanitarian actions to alleviate the effects of human-induced disasters and conflicts.

Prof. Dr. Maria Antonia Brovelli
Prof. Dr. Songnian Li
Guest Editors
Mr. Timur Obukhov
Guest Editor Assistant

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. ISPRS International Journal of Geo-Information 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 1400 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.


  • Disaster
  • Conflicts
  • Human-induced
  • Geospatial
  • Open data
  • Analytics
  • Prediction
  • Prevention

Published Papers (1 paper)

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Analysis and Evaluation of Non-Pharmaceutical Interventions on Prevention and Control of COVID-19: A Case Study of Wuhan City
ISPRS Int. J. Geo-Inf. 2021, 10(7), 480; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070480 - 12 Jul 2021
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As the threat of COVID-19 increases, many countries have carried out various non-pharmaceutical interventions. Although many studies have evaluated the impact of these interventions, there is a lack of mapping between model parameters and actual geographic areas. In this study, a non-pharmaceutical intervention [...] Read more.
As the threat of COVID-19 increases, many countries have carried out various non-pharmaceutical interventions. Although many studies have evaluated the impact of these interventions, there is a lack of mapping between model parameters and actual geographic areas. In this study, a non-pharmaceutical intervention model of COVID-19 based on a discrete grid is proposed from the perspective of geography. This model can provide more direct and effective information for the formulation of prevention and control policies. First, a multi-level grid was introduced to divide the geographical space, and the properties of the grid boundary were used to describe the quarantine status and intensity in these different spaces; this was also combined with the model of hospital isolation and self-protection. Then, a process for the spatiotemporal evolution of the early COVID-19 spread is proposed that integrated the characteristics of residents’ daily activities. Finally, the effect of the interventions was quantitatively analyzed by the dynamic transmission model of COVID-19. The results showed that quarantining is the most effective intervention, especially for infectious diseases with a high infectivity. The introduction of a quarantine could effectively reduce the number of infected humans, advance the peak of the maximum infected number of people, and shorten the duration of the pandemic. However, quarantines only function properly when employed at sufficient intensity; hospital isolation and self-protection measures can effectively slow the spread of COVID-19, thus providing more time for the relevant departments to prepare, but an outbreak will occur again when the hospital reaches full capacity. Moreover, medical resources should be concentrated in places where there is the most urgent need under a strict quarantine measure. Full article
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