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

## TL;DR

This paper introduces a high-resolution dataset tracking wildfire spread in the Mediterranean and Europe to improve fire modeling and management.

## Contribution

The novel contribution is a high-resolution spatiotemporal wildfire propagation dataset called FireSpread_MedEU.

## Key findings

- The dataset includes 320 burned area maps from 103 wildfires between 2017 and 2023.
- The dataset uses Planet satellite imagery with ~3 m spatial resolution and daily temporal resolution.
- The dataset supports machine learning and simulation models for wildfire behavior analysis.

## 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.