Human-Induced Disaster and Conflict Analysis, Prediction, and Prevention by Geospatial Analytics and Information Systems I

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

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