Kaneohe Base, HI
Kaneohe Base, HI's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Kaneohe Base at the 60th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 2,295 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Kaneohe Base's burn probability — fire likelihood with no building count factored in — sits at the 57th percentile nationally.
What "at risk" means for the buildings here
Most of Kaneohe Base's buildings (95.3% of 2,295) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
Kaneohe Base against the rest of the country
Kaneohe Base's 60th national percentile looks worse in isolation than its 1st ranking inside Hawaii does — this place is on the milder end for its own state, by 59 points. Among the 31,521 US communities USFS scores, Kaneohe Base ranks 12,728 for wildfire risk (1 is highest) and 6,706 by building count (1 is largest). Within Hawaii alone, it ranks 162 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
At the 60th national percentile, Kaneohe Base rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With 95.3% of buildings rated Minimal exposure, Kaneohe Base gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Kaneohe Base's figures come from
Every one of the two percentiles behind Kaneohe Base's 12,728-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Kaneohe Base's dominant minimal exposure actually means, with real examples from across the dataset.