Wildfire Occurrence and Damage Dataset for Chile (1985–2024): A Real Data Resource for Early Detection and Prevention Systems

Cristian Vidal-Silva (), Roberto Pizarro, Miguel Castillo-Soto, Claudia de la Fuente, Vannessa Duarte, Claudia Sangüesa, Alfredo Ibañez, Rodrigo Paredes and Ben Ingram
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Cristian Vidal-Silva: Departamento de Visualización Interactiva y Realidad Virtual, Facultad de Ingeniería, Universidad de Talca, Talca 3467769, Chile
Roberto Pizarro: Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
Miguel Castillo-Soto: Forest Fire Laboratory, University of Chile, Santiago 8820808, Chile
Claudia de la Fuente: Departamento de Visualización Interactiva y Realidad Virtual, Facultad de Ingeniería, Universidad de Talca, Talca 3467769, Chile
Vannessa Duarte: Escuela de Ciencias Empresariales, Universidad Católica del Norte, Larrondo 1280, Coquimbo 178142, Chile
Claudia Sangüesa: Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
Alfredo Ibañez: Cátedra UNESCO de Hidrología Superficial, Universidad de Talca, Talca 3467769, Chile
Rodrigo Paredes: Facultad de Ingeniería, Universidad Finis Terrae, Providencia 7501014, Chile
Ben Ingram: Departamento de Visualización Interactiva y Realidad Virtual, Facultad de Ingeniería, Universidad de Talca, Talca 3467769, Chile

Data, 2025, vol. 10, issue 7, 1-12

Abstract: Wildfires represent an increasing global concern, threatening ecosystems, human settlements, and economies. Chile, characterized by diverse climatic zones and extensive forested areas, has been particularly vulnerable to wildfire events over recent decades. In this context, real, long-term data are essential to understand wildfire dynamics and to design effective early warning and prevention systems. This paper introduces a unique dataset containing detailed wildfire occurrence and damage information across Chilean municipalities from 1985 to 2024. Derived from official records by the National Forestry Corporation of Chile CONAF, this dataset encompasses key variables such as the number of fires, total burned area, estimated material damages, and the number of affected individuals. It provides an invaluable resource for researchers and policymakers aiming to improve fire risk assessments, model fire behavior, and develop AI-driven early detection systems. The temporal span of nearly four decades offers opportunities for longitudinal analyses, the study of climate change impacts on fire regimes, and the evaluation of historical prevention strategies. Furthermore, by presenting a complete spatial coverage at the municipal level, it allows fine-grained assessments of regional vulnerabilities and resilience.

Keywords: spatiotemporal analysis; risk mitigation; environmental monitoring; data-driven modeling; wildfire management; public policy; ecological resilience (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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