WildfireRiskFinder

Mahopac, NY

How exposed is Mahopac to wildfire?

Moderate
35thpercentile nationally

Mahopac's 3,331 buildings earn a 35th-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Mahopac's burn probability — fire likelihood with no building count factored in — sits at the 34th percentile nationally.

What "at risk" means for the buildings here

3,331Total buildings
55.5%Direct exposure
28.9%Indirect exposure
15.7%Minimal exposure

3,331 buildings are counted in Mahopac, and 55.5% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 15.7% rated Minimal.

Mahopac against the rest of the country

Mahopac's 76th-percentile standing inside New York outpaces its 35th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Mahopac ranks 20,521 for wildfire risk (1 is highest) and 5,002 by building count (1 is largest). Within New York alone, it ranks 317 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

Mahopac's moderate rating (35th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Mahopac

Because Direct exposure dominates in Mahopac (55.5%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Mahopac's figures come from

Every one of the two percentiles behind Mahopac's 20,521-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Mahopac's dominant direct exposure actually means, with real examples from across the dataset.