A multi-decadal global Landsat-derived dataset of forest fire patches from 1984–2022

Forest fires are a major ecological disturbance affecting carbon cycling, ecosystem structure, and landscape dynamics worldwide. Understanding long-term changes in forest fire patterns requires consistent information on the distribution, extent, and structure of fire patches across broad spatial and temporal scales. The Landsat archive provides nearly four decades of global observations at 30 m resolution, yet generating a consistent global record of forest fire patches remains challenging because of cloud contamination, heterogeneous observation availability, and the computational demands associated with processing multi-decadal imagery. Here we present an initial release of a global 30 m dataset characterizing forest fire patches (GlobMap FFP) from 1984–2022 based on the full Landsat archive (https://doi.org/10.5281/zenodo.17638167, Liu, 2025). To achieve a consistent representation of fire-related spectral signals under heterogeneous observation conditions, we generated multi-temporal Landsat composites using a minimum Brown Vegetation Index compositing approach implemented on the Google Earth Engine platform. Burned pixels were subsequently identified using artificial neural network modeling, and spatially connected pixels with the same burned years were grouped into fire patches through spatiotemporal clustering. The final raster-based product preserves fine-scale spatial heterogeneity while providing patch-level attributes. Across global forests, the dataset delineated 11.97 million fire patches and mapped an average annual burned area of 7.3 Mha yr−1 over 1984–2022. Agreement metrics calculated against a separately generated Landsat-derived reference dataset showed omission errors ranging from 12.2 %–36.8 % and commission errors ranging from 6.4 %–23.2 % across forest types. Performance varied among forest biomes, with lower agreement observed in tropical evergreen broadleaf forests. Intercomparison with existing burned area products revealed generally consistent large-scale spatial patterns, while discrepancies in burned area estimates and patch delineation reflect variations in observation systems, mapping methodologies, and temporal aggregation strategies. Rather than representing a complete global burned area inventory, GlobMap FFP provides a long-term, spatially explicit characterization of forest fire patch structure from Landsat. This dataset facilitates ecological research, particularly at regional scales, by characterizing fire patch structure and spatial organization over time.