Coahoma, TX
Coahoma, TX's wildfire risk, in USFS's own numbers
Coahoma sits at the 86th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 695 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Coahoma at the 85th percentile, close to its 86th-percentile risk score.
Where Coahoma's buildings actually sit
695 buildings are counted in Coahoma, and 54.8% of them are Indirect exposure — ember-driven risk rather than the 23.3% in Direct exposure or the 21.9% rated Minimal.
Coahoma against the rest of the country
Coahoma's risk sits at a similar level relative to Texas (76th percentile statewide) as it does nationally (86th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Coahoma ranks 4,356 for wildfire risk (1 is highest) and 14,726 by building count (1 is largest). Within Texas alone, it ranks 428 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
What this risk score means for insurance
At the 86th percentile nationally, Coahoma 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.
What would actually reduce this score
With ember exposure the dominant pattern in Coahoma (54.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Coahoma's figures come from
Every one of the two percentiles behind Coahoma's 4,356-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Coahoma's dominant indirect exposure actually means, with real examples from across the dataset.