Orient, NY
How exposed is Orient to wildfire?
USFS's Wildfire Risk to Communities model puts Orient at the 27th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 1,177 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Orient at the 24th national percentile — 4 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Orient's buildings actually sit
52% of Orient's 1,177 buildings sit in USFS's Direct exposure zone, roughly 612 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 48% are Minimal.
How Orient compares
Orient's 57th-percentile standing inside New York outpaces its 27th 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, Orient ranks 22,891 for wildfire risk (1 is highest) and 10,785 by building count (1 is largest). Within New York alone, it ranks 554 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Orient and the insurance market
Orient's moderate wildfire rating (27th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
Orient's 52% 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 Orient's figures come from
Every one of the two percentiles behind Orient's 22,891-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Orient's dominant direct exposure actually means, with real examples from across the dataset.