WildfireRiskFinder

Limestone, IL

Limestone wildfire risk explained

Low
15thpercentile nationally

Limestone's 938 buildings earn a 15th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places 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 Limestone at the 15th percentile, close to its 15th-percentile risk score.

What "at risk" means for the buildings here

938Total buildings
31.7%Direct exposure
0%Indirect exposure
68.3%Minimal exposure

USFS classifies 68.3% of Limestone's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 31.7% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.

Where Limestone ranks

Compare Limestone's two percentiles: 53rd within Illinois, only 15th nationally — a gap of 38 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Limestone ranks 26,782 for wildfire risk (1 is highest) and 12,407 by building count (1 is largest). Within Illinois alone, it ranks 676 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.

Limestone and the insurance market

Limestone's low rating (15th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Limestone

Even with 68.3% of Limestone 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 Limestone's figures come from

The methodology guide shows exactly how USFS turned 938 counted buildings into the percentiles shown above for Limestone. The exposure-zones guide covers what Limestone's dominant minimal exposure actually means, with real examples from across the dataset.