Cutchogue, NY
Cutchogue, NY's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Cutchogue lands at the 39th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 3,413 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Cutchogue's burn probability — fire likelihood with no building count factored in — sits at the 38th percentile nationally.
What "at risk" means for the buildings here
64.5% of Cutchogue's 3,413 buildings sit in USFS's Direct exposure zone, roughly 2,201 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 35.5% are Minimal.
How Cutchogue compares
Compare Cutchogue's two percentiles: 82nd within New York, only 39th nationally — a gap of 43 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Cutchogue ranks 19,290 for wildfire risk (1 is highest) and 4,900 by building count (1 is largest). Within New York alone, it ranks 230 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Shopping for coverage in Cutchogue
Cutchogue's moderate wildfire rating (39th 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.
Hardening a home in Cutchogue
With 64.5% of Cutchogue in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Cutchogue's figures come from
The methodology guide shows exactly how USFS turned 3,413 counted buildings into the percentiles shown above for Cutchogue. The exposure-zones guide covers what Cutchogue's dominant direct exposure actually means, with real examples from across the dataset.