The Ponds, NJ
The Ponds wildfire risk explained
USFS scores The Ponds at the 62nd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 350 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, The Ponds's burn probability — fire likelihood with no building count factored in — sits at the 62nd percentile nationally.
What "at risk" means for the buildings here
98.9% of The Ponds's 350 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 1.1% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
The Ponds against the rest of the country
The Ponds scores 62nd nationally and 71st 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, The Ponds ranks 11,951 for wildfire risk (1 is highest) and 20,313 by building count (1 is largest). Within New Jersey alone, it ranks 203 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 62nd percentile nationally, The Ponds carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in The Ponds
Because 98.9% of The Ponds'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 The Ponds's figures come from
Every one of the two percentiles behind The Ponds's 11,951-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what The Ponds's dominant indirect exposure actually means, with real examples from across the dataset.