Nanuet, NY
How exposed is Nanuet to wildfire?
Nanuet sits at the 24th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 4,569 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Nanuet's burn probability — fire likelihood with no building count factored in — sits at the 24th percentile nationally.
What "at risk" means for the buildings here
Only 35.1% of Nanuet's 4,569 buildings carry Direct exposure and 0% carry Indirect; the remaining 64.9% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Nanuet against the rest of the country
Within New York, Nanuet ranks higher (50th percentile) than it does nationally (24th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Nanuet ranks 24,054 for wildfire risk (1 is highest) and 3,732 by building count (1 is largest). Within New York alone, it ranks 642 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
What this risk score means for insurance
Nanuet's moderate wildfire rating (24th 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.
What would actually reduce this score
Nanuet's 64.9% 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 Nanuet's figures come from
Nanuet's 24th-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 Nanuet's dominant minimal exposure actually means, with real examples from across the dataset.