Day of burning maps and burn severity landscape metrics in the southwestern United States 2002-2020

Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future. Our understanding of the landscape outcomes of extreme events is limited, particularly whether or not they burn more severely or produce spatial patterns less conducive to ecosystem recovery. To assess relationships between fire spread rates and landscape burn severity patterns, we used satellite fire detections to create day-of-burning (DOB) maps for 623 fires comprising 4,267 single-day events within forested ecoregions of the southwestern United States. We related satellite-measured burn severity and a suite of high-severity patch metrics to the daily area burned. Extreme fire spread events (defined here as burning >4900 ha/day) exhibited higher mean burn severity, a greater proportion of area burned severely, and increased like adjacencies between high-severity pixels. ..., , , # Manuscript title: Extreme fire spread events burn more severely and homogenize post-fire landscapes in the southwestern United States

**Authors: Jessika R. McFarland, Jonathan D. Coop, Jared A. Balik, Kyle C. Rodman, Sean A. Parks, and Camille S. Stevens-Rumann**

Dryad DOI: https://doi.org/10.5061/dryad.9kd51c5sr

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#### **OVERVIEW:**

This folder includes the results, statistical models, raster data, and code used to produce our manuscript on extreme fire spread events and their burn severity outcomes on fires in the southwestern US. Descriptions of each facet of archived data are below.

**Spatial data overview:**
We used a suite of publicly available, remotely sensed data products to do our analysis. Methods are documented in detail in McFarland et al. (2025)

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1. Monitoring Trends in Burn Severity (MTBS):
MTBS data were utilized to select large (>404 ha) fire perimeters within our study area using the Burned Area Boundaries Dataset.
These data can be found at: https://www...,