Matinecock, NY
Matinecock, NY's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Matinecock at the 37th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 537 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Matinecock at the 37th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Matinecock's buildings actually sit
USFS classifies 95.9% of Matinecock's buildings as Direct exposure, higher than its 4.1% Indirect share and far above its 0% Minimal share — a profile where 515 structures sit close enough to vegetation that lot clearing matters most.
How Matinecock compares
Matinecock's 80th-percentile standing inside New York outpaces its 37th 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, Matinecock ranks 19,888 for wildfire risk (1 is highest) and 16,767 by building count (1 is largest). Within New York alone, it ranks 265 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Matinecock and the insurance market
At the 37th national percentile, Matinecock rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Matinecock
Matinecock's 95.9% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Matinecock's figures come from
The methodology guide shows exactly how USFS turned 537 counted buildings into the percentiles shown above for Matinecock. The exposure-zones guide covers what Matinecock's dominant direct exposure actually means, with real examples from across the dataset.