White Heath, IL
How exposed is White Heath to wildfire?
White Heath sits at the 6th 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 207 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks White Heath at the 6th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
White Heath's building exposure, zone by zone
Most of White Heath's buildings (87.9% of 207) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How White Heath compares
White Heath's 31st-percentile standing inside Illinois outpaces its 6th 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, White Heath ranks 29,650 for wildfire risk (1 is highest) and 24,590 by building count (1 is largest). Within Illinois alone, it ranks 991 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
Shopping for coverage in White Heath
At the 6th national percentile, White Heath rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
White Heath's 87.9% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where White Heath's figures come from
Every one of the two percentiles behind White Heath's 29,650-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what White Heath's dominant minimal exposure actually means, with real examples from across the dataset.