A high-resolution spatiotemporal wildfire propagation dataset for the Mediterranean and Europe

Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 320 consecutive burned area maps from 103 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling.

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Publication Details

Journal
Scientific Data
Published
2026-03-11
DOI
https://doi.org/10.1038/s41597-026-06965-2
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
0.00

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article

A high-resolution spatiotemporal wildfire propagation dataset for the Mediterranean and Europe

Kristin Vogel, Zhimin Chen, Simon Müller, Anja Hofmann-Böllinghaus et al.
Scientific Data
Fire effects on ecosystems
article

A high-resolution spatiotemporal wildfire propagation dataset for the Mediterranean and Europe

Kristin Vogel, Zhimin Chen, Simon Müller, Anja Hofmann-Böllinghaus, Philipp Benner
article en

Abstract

Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 320 consecutive burned area maps from 103 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling.

Scientific DataVol. 13(1)
Federal Institute For Materials Research and Testing (DE), Technische Universität Berlin (DE)
European Commission
Industry, innovation and infrastructure
Openalex Percentile: Top 38%
Fire effects on ecosystems
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