Mohawk, NY
Mohawk, NY's wildfire risk, in USFS's own numbers
USFS scores Mohawk at the 6th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 1,171 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 Mohawk at the 6th percentile, close to its 6th-percentile risk score.
What "at risk" means for the buildings here
92.1% of Mohawk's 1,171 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 7.9% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Mohawk against the rest of the country
Mohawk's risk sits at a similar level relative to New York (9th percentile statewide) as it does nationally (6th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Mohawk ranks 29,699 for wildfire risk (1 is highest) and 10,824 by building count (1 is largest). Within New York alone, it ranks 1,175 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
Mohawk's low wildfire rating (6th 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
Mohawk's 92.1% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Mohawk's figures come from
The methodology guide shows exactly how USFS turned 1,171 counted buildings into the percentiles shown above for Mohawk. The exposure-zones guide covers what Mohawk's dominant indirect exposure actually means, with real examples from across the dataset.