<p style="font-weight: 400;">Forest fires exert profound ecological impacts globally.<span> </span>Characterizing their<span> long-term effects and </span>evolving<span> regimes </span>requires consistent,<span> high-resolution fire records over extended periods. </span>The Landsat archive provides a unique foundation for such efforts, offering fine spatial detail with globally coherent, multi-decadal observations.<span> </span>Yet, it remains challenging to generate<span> </span>a globally consistent, Landsat-based fire product with event-level characterization.<span> </span>Here we present a 30 m global forest<span> </span>fire patch dataset spanning 1984<span>–</span>2022,<span> </span>developed<span> </span>from the full<span> </span>Landsat<span> </span>archive to ensure comprehensive fire characterization.<span> We first condense</span>d<span> multi-temporal burned</span><span> signal</span>s<span> from Landsat archive</span><span> on Google Earth Engine (GEE) </span>using<span> a</span><span> pixel-based image compositing approach.</span><span> This approach also reduces noise from clouds and shadows while ensuring high computational efficiency using GEE</span>. We then mapped burned area using<span> </span>artificial neural network<span> modeling </span>across global forests. Finally, we delineated individual fire patches through spatial–temporal clustering and extracted their key attributes.<span> </span>Across global forests, we identified a total of 11.97 million individual fire patches burning 7.3 Mha yr<sup><span>−</span>1</sup>over 1984–2022. Validation indicated omission errors ranging from 12.2 % to 36.8 % and commission errors ranging from 6.4 % to 23.2 % across diverse forest types. Intercomparison with existing Landsat products revealed strong agreement in annual burned area estimates and fire patch detection, with discrepancies mainly arising from within-fire delineation and small fire detection. This dataset offers a valuable resource for quantifying fire impacts and advancing the understanding of contemporary and future fire regimes in global forests.