Fine-scale fire severity patterns

Wildfires in western U.S. dry forests are increasingly burning large areas at high severity. In large contiguous severely burned patches, near-complete overstory mortality challenges natural forest regeneration processes, which require nearby surviving trees to serve as seed sources. Evaluating burn severity patterns – and thus regeneration potential – across large wildfires generally relies on satellite imagery due to its ready availability and spatially continuous coverage. However, the imagery datasets traditionally used have relatively coarse pixels (e.g., ~ 30 m for Landsat), which can contain multiple trees and may miss small patches of surviving trees (“fire refugia”) that have critical value as seed sources for regeneration. Relatedly, trees that initially survive the fire – but that sustained injuries – may ultimately die in the following years, with implications for their value as seed sources. The presence of drought before and/or after fire may affect the prevalence of fire refugia and delayed mortality.

We are using traditional Landsat imagery along with newer and alternative higher-resolution imagery sources, including Sentinel-2, WorldView-3, NAIP, and drone imagery collected by the FOCAL Lab, to understand the prevalence and spectral signatures of small fire refugia and delayed mortality. The work, which focuses on recent large wildfires in the western US, takes advantage of existing ground-reference plot data capturing post-fire canopy conditions. In addition to addressing ecological questions related to fire mortality and seed source availability, the work will help refine best-practices in use of Landsat vs. alternative imagery data sources for fire severity characterization.