Hanalei, HI
How exposed is Hanalei to wildfire?
USFS scores Hanalei at the 86th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 466 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Hanalei at the 83rd national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Hanalei's building exposure, zone by zone
81.8% of Hanalei's 466 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 18% Direct and 0.2% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Where Hanalei ranks
Hanalei ranks lower within Hawaii (25th percentile statewide) than its 86th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Hanalei ranks 4,318 for wildfire risk (1 is highest) and 17,954 by building count (1 is largest). Within Hawaii alone, it ranks 122 of 163 places by risk. See the full county-by-county picture for Hawaii on its state page.
Hanalei and the insurance market
Hanalei's 86th-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.
What would actually reduce this score
Because 81.8% of Hanalei's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Hanalei's figures come from
The methodology guide shows exactly how USFS turned 466 counted buildings into the percentiles shown above for Hanalei. The exposure-zones guide covers what Hanalei's dominant indirect exposure actually means, with real examples from across the dataset.