Kenilworth, NJ
Kenilworth wildfire risk explained
USFS scores Kenilworth at the 24th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 3,441 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Kenilworth at the 26th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Kenilworth's buildings actually sit
Kenilworth rates 97.8% Minimal exposure against just 2.2% Direct and 0% Indirect — of 3,441 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Kenilworth compares
There's little gap between Kenilworth's 24th national percentile and its 13th 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, Kenilworth ranks 24,023 for wildfire risk (1 is highest) and 4,856 by building count (1 is largest). Within New Jersey alone, it ranks 611 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
At the 24th national percentile, Kenilworth rates moderate 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
Kenilworth's 97.8% 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 Kenilworth's figures come from
Every one of the two percentiles behind Kenilworth's 24,023-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Kenilworth's dominant minimal exposure actually means, with real examples from across the dataset.