Belvidere, NJ
Belvidere wildfire risk explained
USFS's Wildfire Risk to Communities model puts Belvidere at the 31st national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 1,145 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Belvidere at the 31st national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Belvidere's buildings actually sit
USFS puts 67.9% of Belvidere's 1,145 buildings in the Indirect exposure zone, versus 32.1% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Belvidere against the rest of the country
Belvidere's risk sits at a similar level relative to New Jersey (27th percentile statewide) as it does nationally (31st) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Belvidere ranks 21,688 for wildfire risk (1 is highest) and 10,990 by building count (1 is largest). Within New Jersey alone, it ranks 510 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Shopping for coverage in Belvidere
Belvidere's moderate wildfire rating (31st 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.
Hardening a home in Belvidere
Because 67.9% of Belvidere's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Belvidere's figures come from
Belvidere's 31st-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 Belvidere's dominant indirect exposure actually means, with real examples from across the dataset.