Lindrith, NM
How exposed is Lindrith to wildfire?
Out of every US place USFS scores, Lindrith lands at the 77th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 84 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Lindrith at the 71st national percentile — 6 points below its risk-to-structures score, a gap driven by how much is actually built there.
Lindrith's building exposure, zone by zone
Of Lindrith's 84 counted buildings, 100% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Lindrith against the rest of the country
Lindrith ranks lower within New Mexico (50th percentile statewide) than its 77th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Lindrith ranks 7,157 for wildfire risk (1 is highest) and 29,737 by building count (1 is largest). Within New Mexico alone, it ranks 249 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Lindrith and the insurance market
At the 77th percentile nationally, Lindrith 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.
Lowering exposure, not just insuring around it
Lindrith's 100% 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 Lindrith's figures come from
The methodology guide shows exactly how USFS turned 84 counted buildings into the percentiles shown above for Lindrith. The exposure-zones guide covers what Lindrith's dominant direct exposure actually means, with real examples from across the dataset.