WildfireRiskFinder

Neponset, IL

How exposed is Neponset to wildfire?

Low
3rdpercentile nationally

USFS scores Neponset at the 3rd national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 368 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Neponset's burn probability — fire likelihood with no building count factored in — sits at the 3rd percentile nationally.

What "at risk" means for the buildings here

368Total buildings
23.4%Direct exposure
0%Indirect exposure
76.6%Minimal exposure

Most of Neponset's buildings (76.6% of 368) 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 Neponset compares

Compare Neponset's two percentiles: 20th within Illinois, only 3rd nationally — a gap of 17 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Neponset ranks 30,566 for wildfire risk (1 is highest) and 19,899 by building count (1 is largest). Within Illinois alone, it ranks 1,164 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.

What this risk score means for insurance

Neponset's low wildfire rating (3rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.

Hardening a home in Neponset

With 76.6% of buildings rated Minimal exposure, Neponset gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Neponset's figures come from

The methodology guide shows exactly how USFS turned 368 counted buildings into the percentiles shown above for Neponset. The exposure-zones guide covers what Neponset's dominant minimal exposure actually means, with real examples from across the dataset.