Sienna, TX
Sienna, TX's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Sienna at the 73rd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 6,875 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Sienna at the 77th percentile, close to its 73rd-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in Sienna (83.4% of 6,875 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 16.6% sit in the Direct zone. At 6,875 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Sienna ranks
Sienna's 73rd national percentile looks worse in isolation than its 39th ranking inside Texas does — this place is on the milder end for its own state, by 34 points. Among the 31,521 US communities USFS scores, Sienna ranks 8,493 for wildfire risk (1 is highest) and 2,518 by building count (1 is largest). Within Texas alone, it ranks 1,087 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Sienna
Sienna's high rating (73rd 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.
Hardening a home in Sienna
Because 83.4% of Sienna's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Sienna's figures come from
Sienna's 73rd-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 Sienna's dominant indirect exposure actually means, with real examples from across the dataset.