Oaklyn, NJ
Oaklyn, NJ's wildfire risk, in USFS's own numbers
USFS scores Oaklyn at the 38th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,537 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Oaklyn at the 42nd percentile, close to its 38th-percentile risk score.
Oaklyn's building exposure, zone by zone
95.1% of Oaklyn's 1,537 buildings sit in USFS's Minimal exposure zone, with only 4.9% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Oaklyn against the rest of the country
There's little gap between Oaklyn's 38th national percentile and its 39th percentile inside New Jersey, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Oaklyn ranks 19,699 for wildfire risk (1 is highest) and 9,001 by building count (1 is largest). Within New Jersey alone, it ranks 433 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Oaklyn and the insurance market
Oaklyn's moderate wildfire rating (38th 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
Oaklyn's 95.1% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Oaklyn's figures come from
Every one of the two percentiles behind Oaklyn's 19,699-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Oaklyn's dominant minimal exposure actually means, with real examples from across the dataset.