Who are the actors and what are the factors that are used in models to map forest fire susceptibility? A systematic review

Santos Daniel Chicas () and Jonas Østergaard Nielsen ()
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Santos Daniel Chicas: Humboldt-Universität Zu Berlin
Jonas Østergaard Nielsen: Humboldt-Universität Zu Berlin

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 3, No 2, 2417-2434

Abstract: Abstract In the last decades, natural fire regimes have experienced significant alterations in terms of intensity, frequency and severity in fire prone regions of the world. Modelling forest fire susceptibility has been essential in identifying areas of high risk to minimize threats to natural resources, biodiversity and life. There have been significant improvements in forest fire susceptibility modelling over the past two decades 2001–2021. In this study, we conducted a systematic literature review of literature covering forest fire susceptibility modelling published during this period. The review provides insights on the main themes of forest fire susceptibility modelling research, the main base input factors used in models to map forest fire susceptibility, the main researchers, the areas where this type of research were implemented, technology and models used. It also highlights collaboration opportunities, and regions, such as Central America and Africa, where mapping of forest fire susceptibility is needed. We argue that such knowledge is crucial in order to identify critical factors and opportunities which can aid in improving factor selection and forest fire management.

Keywords: Wildfire; Machine learning; Drivers; Fire management; Africa; Fire risk (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11069-022-05495-5

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