Manchester, NY
How exposed is Manchester to wildfire?
USFS's Wildfire Risk to Communities model puts Manchester at the 6th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 883 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Manchester at the 6th percentile, close to its 6th-percentile risk score.
Manchester's building exposure, zone by zone
USFS classifies 59.7% of Manchester's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 40.3% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
How Manchester compares
Manchester's risk sits at a similar level relative to New York (8th 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, Manchester ranks 29,766 for wildfire risk (1 is highest) and 12,878 by building count (1 is largest). Within New York alone, it ranks 1,195 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Manchester and the insurance market
Manchester'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
Even with 59.7% of Manchester outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Manchester's figures come from
Manchester's 6th-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 Manchester's dominant minimal exposure actually means, with real examples from across the dataset.