Seminole, TX
How exposed is Seminole to wildfire?
Seminole 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 3,994 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Seminole's burn probability — fire likelihood with no building count factored in — sits at the 84th percentile nationally.
Seminole's building exposure, zone by zone
Indirect exposure is dominant in Seminole (89.7% of 3,994 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 10.3% sit in the Direct zone.
How Seminole compares
Seminole's risk sits at a similar level relative to Texas (75th 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, Seminole ranks 4,489 for wildfire risk (1 is highest) and 4,251 by building count (1 is largest). Within Texas alone, it ranks 451 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Seminole
Seminole's 86th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
With ember exposure the dominant pattern in Seminole (89.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Seminole's figures come from
The methodology guide shows exactly how USFS turned 3,994 counted buildings into the percentiles shown above for Seminole. The exposure-zones guide covers what Seminole's dominant indirect exposure actually means, with real examples from across the dataset.