Vauxhall, NJ
Vauxhall wildfire risk explained
Out of every US place USFS scores, Vauxhall lands at the 35th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,321 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Vauxhall at the 34th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Vauxhall's buildings (97.7% of 1,321) 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.
Where Vauxhall ranks
There's little gap between Vauxhall's 35th national percentile and its 34th 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, Vauxhall ranks 20,613 for wildfire risk (1 is highest) and 9,968 by building count (1 is largest). Within New Jersey alone, it ranks 464 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
Vauxhall's moderate wildfire rating (35th 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
Vauxhall's 97.7% 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 Vauxhall's figures come from
Vauxhall's 35th-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 Vauxhall's dominant minimal exposure actually means, with real examples from across the dataset.