Bardolph, IL
Bardolph wildfire risk explained
Bardolph sits at the 5th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 215 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Bardolph at the 5th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Bardolph's buildings actually sit
87.4% of Bardolph's 215 buildings sit in USFS's Minimal exposure zone, with only 12.6% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
How Bardolph compares
Bardolph's 29th-percentile standing inside Illinois outpaces its 5th 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, Bardolph ranks 29,933 for wildfire risk (1 is highest) and 24,301 by building count (1 is largest). Within Illinois alone, it ranks 1,026 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
Shopping for coverage in Bardolph
At the 5th national percentile, Bardolph rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Even with 87.4% of Bardolph 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 Bardolph's figures come from
The methodology guide shows exactly how USFS turned 215 counted buildings into the percentiles shown above for Bardolph. The exposure-zones guide covers what Bardolph's dominant minimal exposure actually means, with real examples from across the dataset.