Glenwood, UT
Glenwood wildfire risk explained
Glenwood sits at the 84th 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 350 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Glenwood's burn probability — fire likelihood with no building count factored in — sits at the 82nd percentile nationally.
What "at risk" means for the buildings here
81.4% of Glenwood's 350 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 18.6% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Glenwood compares
Inside Utah, Glenwood sits at just the 45th percentile even though it scores 84th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Glenwood ranks 5,122 for wildfire risk (1 is highest) and 20,322 by building count (1 is largest). Within Utah alone, it ranks 180 of 326 places by risk. See the full county-by-county picture for Utah on its state page.
What this risk score means for insurance
Glenwood's very high rating (84th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
Glenwood's 81.4% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Glenwood's figures come from
Every one of the two percentiles behind Glenwood's 5,122-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Glenwood's dominant indirect exposure actually means, with real examples from across the dataset.