Honomu, HI
Honomu, HI's wildfire risk, in USFS's own numbers
Honomu sits at the 70th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 274 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Honomu at the 65th percentile, close to its 70th-percentile risk score.
Honomu's building exposure, zone by zone
274 buildings are counted in Honomu, and 63.1% of them are Indirect exposure — ember-driven risk rather than the 36.5% in Direct exposure or the 0.4% rated Minimal.
Where Honomu ranks
Honomu ranks lower within Hawaii (3rd percentile statewide) than its 70th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Honomu ranks 9,357 for wildfire risk (1 is highest) and 22,385 by building count (1 is largest). Within Hawaii alone, it ranks 158 of 163 places by risk. See the full county-by-county picture for Hawaii on its state page.
Shopping for coverage in Honomu
Honomu's 70th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Honomu's 63.1% 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 Honomu's figures come from
The methodology guide shows exactly how USFS turned 274 counted buildings into the percentiles shown above for Honomu. The exposure-zones guide covers what Honomu's dominant indirect exposure actually means, with real examples from across the dataset.