Edgewood, NM
Edgewood, NM's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Edgewood at the 90th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 3,698 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Edgewood at the 88th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Edgewood's buildings actually sit
USFS classifies 98.1% of Edgewood's buildings as Direct exposure, higher than its 1.9% Indirect share and far above its 0% Minimal share — a profile where 3,628 structures sit close enough to vegetation that lot clearing matters most.
Edgewood against the rest of the country
Edgewood's 90th national percentile looks worse in isolation than its 75th ranking inside New Mexico does — this place is on the milder end for its own state, by 15 points. Among the 31,521 US communities USFS scores, Edgewood ranks 3,126 for wildfire risk (1 is highest) and 4,528 by building count (1 is largest). Within New Mexico alone, it ranks 125 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Edgewood and the insurance market
At the 90th percentile nationally, Edgewood carries the very 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 Edgewood
Because Direct exposure dominates in Edgewood (98.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Edgewood's figures come from
Every one of the two percentiles behind Edgewood's 3,126-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Edgewood's dominant direct exposure actually means, with real examples from across the dataset.