WildfireRiskFinder

Hamel, IL

Hamel wildfire risk explained

Low
5thpercentile nationally

USFS's Wildfire Risk to Communities model puts Hamel at the 5th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 499 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Hamel at the 5th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

499Total buildings
11%Direct exposure
0%Indirect exposure
89%Minimal exposure

Hamel rates 89% Minimal exposure against just 11% Direct and 0% Indirect — of 499 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

Hamel against the rest of the country

Within Illinois, Hamel ranks higher (29th percentile) than it does nationally (5th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Hamel ranks 29,935 for wildfire risk (1 is highest) and 17,376 by building count (1 is largest). Within Illinois alone, it ranks 1,028 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

At the 5th national percentile, Hamel rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

Hardening a home in Hamel

With 89% of buildings rated Minimal exposure, Hamel gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Hamel's figures come from

Hamel's 5th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Hamel's dominant minimal exposure actually means, with real examples from across the dataset.