Kapaau, HI
Kapaau wildfire risk explained
USFS's Wildfire Risk to Communities model puts Kapaau at the 88th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 943 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Kapaau at the 85th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Kapaau's buildings actually sit
943 buildings are counted in Kapaau, and 67.3% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
How Kapaau compares
Kapaau's 88th national percentile looks worse in isolation than its 33rd ranking inside Hawaii does — this place is on the milder end for its own state, by 54 points. Among the 31,521 US communities USFS scores, Kapaau ranks 3,903 for wildfire risk (1 is highest) and 12,361 by building count (1 is largest). Within Hawaii alone, it ranks 109 of 163 places by risk. See the full county-by-county picture for Hawaii on its state page.
What this risk score means for insurance
Kapaau's 88th-percentile, very 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.
Lowering exposure, not just insuring around it
Kapaau's 67.3% 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 Kapaau's figures come from
Kapaau's 88th-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 Kapaau's dominant direct exposure actually means, with real examples from across the dataset.