Hackettstown, NJ
Hackettstown wildfire risk explained
Hackettstown sits at the 39th 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 3,007 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 Hackettstown at the 37th percentile, close to its 39th-percentile risk score.
What "at risk" means for the buildings here
68.4% of Hackettstown's 3,007 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 31.6% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Hackettstown against the rest of the country
Hackettstown scores 39th nationally and 41st within New Jersey — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Hackettstown ranks 19,287 for wildfire risk (1 is highest) and 5,427 by building count (1 is largest). Within New Jersey alone, it ranks 412 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
What this risk score means for insurance
At the 39th national percentile, Hackettstown 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
With ember exposure the dominant pattern in Hackettstown (68.4% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Hackettstown's figures come from
The methodology guide shows exactly how USFS turned 3,007 counted buildings into the percentiles shown above for Hackettstown. The exposure-zones guide covers what Hackettstown's dominant indirect exposure actually means, with real examples from across the dataset.