Gang Mills, NY
How exposed is Gang Mills to wildfire?
USFS scores Gang Mills at the 32nd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,451 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Gang Mills at the 31st percentile, close to its 32nd-percentile risk score.
Where Gang Mills's buildings actually sit
Direct exposure dominates in Gang Mills: 59.9% of its 1,451 buildings, versus 40.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Gang Mills ranks
Gang Mills's 70th-percentile standing inside New York outpaces its 32nd 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, Gang Mills ranks 21,336 for wildfire risk (1 is highest) and 9,392 by building count (1 is largest). Within New York alone, it ranks 390 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
At the 32nd national percentile, Gang Mills rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Gang Mills's 59.9% 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 Gang Mills's figures come from
The methodology guide shows exactly how USFS turned 1,451 counted buildings into the percentiles shown above for Gang Mills. The exposure-zones guide covers what Gang Mills's dominant direct exposure actually means, with real examples from across the dataset.