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Wildfire occurrence and damage dataset for Chile (1985–2024): a real data resource for early detection and prevention systems

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2025-09-01

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2306-5729

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Vidal-Silva C, Pizarro R, Castillo-Soto M, et al., (2025) Wildfire occurrence and damage dataset for Chile (1985–2024): a real data resource for early detection and prevention systems. Data, Volume 10, Issue 7, June 2025, Article number 93

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.

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Git repository

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spatiotemporal analysis, risk mitigation, environmental monitoring, data-driven modeling, wildfire management, public policy, ecological resilience, 46 Information and Computing Sciences, Prevention, 4605 Data management and data science, 4610 Library and information studies

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Attribution 4.0 International

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