Otisville, NY
Otisville, NY's wildfire risk, in USFS's own numbers
USFS scores Otisville at the 56th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 535 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Otisville at the 56th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Of Otisville's 535 counted buildings, 83.2% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Otisville against the rest of the country
Otisville's 98th-percentile standing inside New York outpaces its 56th 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, Otisville ranks 13,910 for wildfire risk (1 is highest) and 16,800 by building count (1 is largest). Within New York alone, it ranks 29 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Otisville and the insurance market
At the 56th national percentile, Otisville rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Because Direct exposure dominates in Otisville (83.2%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Otisville's figures come from
Every one of the two percentiles behind Otisville's 13,910-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Otisville's dominant direct exposure actually means, with real examples from across the dataset.