An interdisciplinary data-science approach to managing natural hazards risk

Natural hazard risk management is a demanding interdisciplinary task. It requires domain knowledge, integration of robust computational methods, and effective use of complex datasets. However, existing solutions tend to focus on specific aspects, data, or methods, limiting their impact and applicabi...

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Bibliographic Details
Published inarXiv.org
Main Authors Pais, Cristobal, Kim, Minho, Radke, John, Gonzalez, Marta C
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 09.07.2024
Subjects
Complexity
Datasets
Fire hazards
Hazard assessment
Knowledge management
Management methods
Risk assessment
Risk management
Spatial data
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Summary:Natural hazard risk management is a demanding interdisciplinary task. It requires domain knowledge, integration of robust computational methods, and effective use of complex datasets. However, existing solutions tend to focus on specific aspects, data, or methods, limiting their impact and applicability. Here, we present a general data-driven framework to support risk assessment and policy making illustrating its usage in the context of fire hazard by integrating three unique datasets of fire behavior, street network, and census data for the whole state of California. We show that integrating spatial complexity by including a fire behavior layer and a socio-demographic layer changes the universal function observed in previous optimization frameworks that only work with the accessibility of facilities. These results open avenues for the future development of flexible interdisciplinary frameworks in natural hazards management using complex large-scale data.
ISSN:2331-8422