Clute, TX
How exposed is Clute to wildfire?
Clute sits at the 92nd 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 3,586 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Clute's burn probability — fire likelihood with no building count factored in — sits at the 93rd percentile nationally.
Clute's building exposure, zone by zone
USFS classifies 44.7% of Clute's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 19.2% Direct and 36.1% Indirect — a landscape-level risk rather than a building-by-building one.
How Clute compares
Clute scores 92nd nationally and 88th 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, Clute ranks 2,688 for wildfire risk (1 is highest) and 4,672 by building count (1 is largest). Within Texas alone, it ranks 215 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Clute and the insurance market
At the 92nd percentile nationally, Clute 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.
Lowering exposure, not just insuring around it
Even with 44.7% of Clute outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Clute's figures come from
Every one of the two percentiles behind Clute's 2,688-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Clute's dominant minimal exposure actually means, with real examples from across the dataset.