Glidden, TX
Glidden wildfire risk explained
USFS's Wildfire Risk to Communities model puts Glidden at the 65th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 418 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Glidden at the 66th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Glidden's buildings actually sit
USFS classifies 73.2% of Glidden's buildings as Direct exposure, higher than its 26.8% Indirect share and far above its 0% Minimal share — a profile where 306 structures sit close enough to vegetation that lot clearing matters most.
Glidden against the rest of the country
Glidden ranks lower within Texas (21st percentile statewide) than its 65th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Glidden ranks 11,106 for wildfire risk (1 is highest) and 18,867 by building count (1 is largest). Within Texas alone, it ranks 1,421 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Glidden and the insurance market
Glidden's high rating (65th 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
With 73.2% of Glidden in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Glidden's figures come from
Glidden's 65th-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 Glidden's dominant direct exposure actually means, with real examples from across the dataset.