Muenster, TX
How exposed is Muenster to wildfire?
Muenster's 1,051 buildings earn a 87th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Muenster at the 87th percentile, close to its 87th-percentile risk score.
Muenster's building exposure, zone by zone
Most of Muenster's buildings (83.8%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Muenster compares
Muenster scores 87th nationally and 77th within Texas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Muenster ranks 4,267 for wildfire risk (1 is highest) and 11,591 by building count (1 is largest). Within Texas alone, it ranks 420 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Muenster and the insurance market
Muenster's 87th-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.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Muenster (83.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Muenster's figures come from
Muenster's 87th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Muenster's dominant indirect exposure actually means, with real examples from across the dataset.