Ringoes, NJ
Ringoes wildfire risk explained
Ringoes sits at the 30th 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 547 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Ringoes at the 29th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Ringoes's building exposure, zone by zone
547 buildings are counted in Ringoes, and 93.6% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Where Ringoes ranks
Ringoes scores 30th nationally and 25th 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, Ringoes ranks 22,191 for wildfire risk (1 is highest) and 16,615 by building count (1 is largest). Within New Jersey alone, it ranks 528 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Ringoes and the insurance market
Ringoes's moderate wildfire rating (30th 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 Ringoes
With 93.6% of Ringoes in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Ringoes's figures come from
The methodology guide shows exactly how USFS turned 547 counted buildings into the percentiles shown above for Ringoes. The exposure-zones guide covers what Ringoes's dominant direct exposure actually means, with real examples from across the dataset.