New Hamburg, NY
New Hamburg wildfire risk explained
New Hamburg sits at the 34th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 381 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts New Hamburg at the 34th percentile, close to its 34th-percentile risk score.
New Hamburg's building exposure, zone by zone
381 buildings are counted in New Hamburg, and 39.1% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 22.1% rated Minimal.
New Hamburg against the rest of the country
New Hamburg's 72nd-percentile standing inside New York outpaces its 34th 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, New Hamburg ranks 20,929 for wildfire risk (1 is highest) and 19,628 by building count (1 is largest). Within New York alone, it ranks 358 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
New Hamburg and the insurance market
At the 34th national percentile, New Hamburg 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
Because Direct exposure dominates in New Hamburg (39.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where New Hamburg's figures come from
New Hamburg's 34th-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 New Hamburg's dominant direct exposure actually means, with real examples from across the dataset.