Brinckerhoff, NY
Brinckerhoff wildfire risk explained
USFS scores Brinckerhoff at the 33rd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,158 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Brinckerhoff at the 32nd national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Brinckerhoff's buildings actually sit
Indirect exposure is dominant in Brinckerhoff (72.7% of 1,158 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 27.3% sit in the Direct zone.
Where Brinckerhoff ranks
Brinckerhoff's 70th-percentile standing inside New York outpaces its 33rd 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, Brinckerhoff ranks 21,245 for wildfire risk (1 is highest) and 10,902 by building count (1 is largest). Within New York alone, it ranks 383 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Brinckerhoff and the insurance market
Brinckerhoff's moderate rating (33rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Because 72.7% of Brinckerhoff's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Brinckerhoff's figures come from
Brinckerhoff's 33rd-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 Brinckerhoff's dominant indirect exposure actually means, with real examples from across the dataset.