Madrid, NM
How exposed is Madrid to wildfire?
USFS's Wildfire Risk to Communities model puts Madrid at the 82nd national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 216 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Madrid at the 76th national percentile — 6 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 60.7% of Madrid's buildings as Direct exposure, higher than its 39.4% Indirect share and far above its 0% Minimal share — a profile where 131 structures sit close enough to vegetation that lot clearing matters most.
How Madrid compares
Madrid ranks lower within New Mexico (56th percentile statewide) than its 82nd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Madrid ranks 5,738 for wildfire risk (1 is highest) and 24,278 by building count (1 is largest). Within New Mexico alone, it ranks 218 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
What this risk score means for insurance
At the 82nd percentile nationally, Madrid 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 Madrid
Madrid's 60.7% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Madrid's figures come from
The methodology guide shows exactly how USFS turned 216 counted buildings into the percentiles shown above for Madrid. The exposure-zones guide covers what Madrid's dominant direct exposure actually means, with real examples from across the dataset.