Ramblewood, NJ
Ramblewood, NJ's wildfire risk, in USFS's own numbers
USFS scores Ramblewood at the 48th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 1,966 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Ramblewood at the 51st percentile, close to its 48th-percentile risk score.
What "at risk" means for the buildings here
Only 26.8% of Ramblewood's 1,966 buildings carry Direct exposure and 0% carry Indirect; the remaining 73.2% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Ramblewood against the rest of the country
Ramblewood scores 48th nationally and 54th 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, Ramblewood ranks 16,358 for wildfire risk (1 is highest) and 7,572 by building count (1 is largest). Within New Jersey alone, it ranks 321 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Shopping for coverage in Ramblewood
Ramblewood's elevated rating (48th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Even with 73.2% of Ramblewood outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Ramblewood's figures come from
The methodology guide shows exactly how USFS turned 1,966 counted buildings into the percentiles shown above for Ramblewood. The exposure-zones guide covers what Ramblewood's dominant minimal exposure actually means, with real examples from across the dataset.