Lebanon, MO
How exposed is Lebanon to wildfire?
Lebanon's 7,184 buildings earn a 82nd-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 Lebanon at the 84th percentile, close to its 82nd-percentile risk score.
Where Lebanon's buildings actually sit
7,184 buildings are counted in Lebanon, and 67.6% of them are Indirect exposure — ember-driven risk rather than the 23.9% in Direct exposure or the 8.5% rated Minimal. At 7,184 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Lebanon against the rest of the country
Lebanon's 99th-percentile standing inside Missouri outpaces its 82nd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Lebanon ranks 5,797 for wildfire risk (1 is highest) and 2,383 by building count (1 is largest). Within Missouri alone, it ranks 14 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Shopping for coverage in Lebanon
Lebanon's very high rating (82nd 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
Because 67.6% of Lebanon'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 Lebanon's figures come from
Lebanon's 82nd-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 Lebanon's dominant indirect exposure actually means, with real examples from across the dataset.