Hewlett Harbor, NY
How exposed is Hewlett Harbor to wildfire?
Hewlett Harbor's 511 buildings earn a 50th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Hewlett Harbor at the 46th percentile, close to its 50th-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 92.6% of Hewlett Harbor's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 7.4% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
How Hewlett Harbor compares
Hewlett Harbor's 95th-percentile standing inside New York outpaces its 50th 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, Hewlett Harbor ranks 15,762 for wildfire risk (1 is highest) and 17,161 by building count (1 is largest). Within New York alone, it ranks 71 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
Shopping for coverage in Hewlett Harbor
At the 50th national percentile, Hewlett Harbor rates elevated 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
Hewlett Harbor's 92.6% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Hewlett Harbor's figures come from
Every one of the two percentiles behind Hewlett Harbor's 15,762-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Hewlett Harbor's dominant minimal exposure actually means, with real examples from across the dataset.