Nanakuli, HI
How exposed is Nanakuli to wildfire?
Out of every US place USFS scores, Nanakuli lands at the 100th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 2,940 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Nanakuli at the 100th percentile, close to its 100th-percentile risk score.
Nanakuli's building exposure, zone by zone
2,940 buildings are counted in Nanakuli, and 90.4% of them are Indirect exposure — ember-driven risk rather than the 9% in Direct exposure or the 0.7% rated Minimal.
Where Nanakuli ranks
There's little gap between Nanakuli's 100th national percentile and its 99th percentile inside Hawaii, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Nanakuli ranks 41 for wildfire risk (1 is highest) and 5,529 by building count (1 is largest). Within Hawaii alone, it ranks 2 of 163 places by risk. See the full county-by-county picture for Hawaii on its state page.
Nanakuli and the insurance market
Nanakuli's 100th-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
Nanakuli's 90.4% 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 Nanakuli's figures come from
Nanakuli's 100th-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 Nanakuli's dominant indirect exposure actually means, with real examples from across the dataset.