Shawneetown, IL
How exposed is Shawneetown to wildfire?
Shawneetown's 810 buildings earn a 30th-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Shawneetown at the 32nd percentile, close to its 30th-percentile risk score.
Shawneetown's building exposure, zone by zone
Only 13.2% of Shawneetown's 810 buildings carry Direct exposure and 16.4% carry Indirect; the remaining 70.4% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Shawneetown against the rest of the country
Shawneetown's 80th-percentile standing inside Illinois outpaces its 30th 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, Shawneetown ranks 21,991 for wildfire risk (1 is highest) and 13,551 by building count (1 is largest). Within Illinois alone, it ranks 291 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
Shopping for coverage in Shawneetown
Shawneetown's moderate rating (30th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
With 70.4% of buildings rated Minimal exposure, Shawneetown gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Shawneetown's figures come from
Every one of the two percentiles behind Shawneetown's 21,991-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Shawneetown's dominant minimal exposure actually means, with real examples from across the dataset.