Edna, CA
Edna wildfire risk explained
Out of every US place USFS scores, Edna lands at the 92nd percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 172 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Edna at the 92nd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 61.1% of Edna's buildings as Direct exposure, higher than its 39% Indirect share and far above its 0% Minimal share — a profile where 105 structures sit close enough to vegetation that lot clearing matters most.
Edna against the rest of the country
Edna's 92nd national percentile looks worse in isolation than its 65th ranking inside California does — this place is on the milder end for its own state, by 26 points. Among the 31,521 US communities USFS scores, Edna ranks 2,667 for wildfire risk (1 is highest) and 25,926 by building count (1 is largest). Within California alone, it ranks 549 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
Edna's 92nd-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.
What would actually reduce this score
Because Direct exposure dominates in Edna (61.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Edna's figures come from
The methodology guide shows exactly how USFS turned 172 counted buildings into the percentiles shown above for Edna. The exposure-zones guide covers what Edna's dominant direct exposure actually means, with real examples from across the dataset.