Woody, CA
Woody wildfire risk explained
USFS scores Woody at the 95th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 85 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Woody's burn probability — fire likelihood with no building count factored in — sits at the 96th percentile nationally.
What "at risk" means for the buildings here
USFS classifies 100% of Woody's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 85 structures sit close enough to vegetation that lot clearing matters most.
How Woody compares
Woody's 95th national percentile looks worse in isolation than its 75th ranking inside California does — this place is on the milder end for its own state, by 21 points. Among the 31,521 US communities USFS scores, Woody ranks 1,475 for wildfire risk (1 is highest) and 29,680 by building count (1 is largest). Within California alone, it ranks 400 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Woody's 95th-percentile score lands in California, the only two states requiring a wildfire disclosure at sale. California's surplus-lines homeowners market passed 300,000 policies for the first time in 2025, driven by carriers pulling back from wildfire-exposed areas statewide. The disclosure-law guide covers what it requires.
Hardening a home in Woody
Woody's 100% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Woody's figures come from
Every one of the two percentiles behind Woody's 1,475-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Woody's dominant direct exposure actually means, with real examples from across the dataset.