Hiouchi, CA
Hiouchi wildfire risk explained
Hiouchi's 206 buildings earn a 90th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Hiouchi's burn probability — fire likelihood with no building count factored in — sits at the 91st percentile nationally.
Hiouchi's building exposure, zone by zone
Indirect exposure is dominant in Hiouchi (66% of 206 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 34% sit in the Direct zone.
Hiouchi against the rest of the country
Inside California, Hiouchi sits at just the 62nd percentile even though it scores 90th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Hiouchi ranks 3,077 for wildfire risk (1 is highest) and 24,631 by building count (1 is largest). Within California alone, it ranks 597 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Hiouchi and the insurance market
Hiouchi's 90th-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
Hiouchi's 66% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Hiouchi's figures come from
Hiouchi's 90th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Hiouchi's dominant indirect exposure actually means, with real examples from across the dataset.