Oakhurst, NJ
Oakhurst wildfire risk explained
USFS scores Oakhurst at the 54th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 1,647 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Oakhurst at the 56th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Oakhurst's building exposure, zone by zone
79.4% of Oakhurst's 1,647 buildings sit in USFS's Minimal exposure zone, with only 20.6% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Oakhurst ranks
Oakhurst scores 54th nationally and 63rd within New Jersey — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Oakhurst ranks 14,596 for wildfire risk (1 is highest) and 8,599 by building count (1 is largest). Within New Jersey alone, it ranks 263 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
What this risk score means for insurance
Oakhurst's elevated wildfire rating (54th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
Even with 79.4% of Oakhurst outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Oakhurst's figures come from
The methodology guide shows exactly how USFS turned 1,647 counted buildings into the percentiles shown above for Oakhurst. The exposure-zones guide covers what Oakhurst's dominant minimal exposure actually means, with real examples from across the dataset.