ArticleF1000Research2025
A raster-based dataset for spatio-temporal analysis of forest fires in the Amazon rainforest from 2001 to 2020.
Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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Authors and funding
2 authors.
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Abstract
Forest fires are becoming increasingly common worldwide, posing a threat to the environment, economy, and society. Spatiotemporal analysis of forest fires is important to understand their characteristics and causes and to inform decision-making. This type of analysis requires the availability of a number of factors that contribute to fire occurrence, such as land use, environment, climate, and human activities, at high spatial and temporal resolutions. The South American Amazon rainforest covers a large area, and acquiring a useful dataset for analysis requires extensive effort and computer-intensive processing. This study investigates potential data sources, establishes a methodology, and prepares a dataset of attributes useful for spatiotemporal fire analysis. We provide a raster-based dataset that includes fires, land use, environment, and climate factors at a spatial resolution of 500 m and monthly temporal resolution from 2001 to 2020, which facilitates the analysis of forest fires in the Amazon. Moreover, because data sources and implementation procedures are detailed, this work also encourages similar research in other parts of the world.
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