Martinton, IL
Martinton wildfire risk explained
Out of every US place USFS scores, Martinton lands at the 0th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 247 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Martinton at the 0th 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
USFS classifies 94.3% of Martinton's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 5.7% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Martinton ranks
There's little gap between Martinton's 0th national percentile and its 2nd percentile inside Illinois, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Martinton ranks 31,482 for wildfire risk (1 is highest) and 23,233 by building count (1 is largest). Within Illinois alone, it ranks 1,425 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 0th national percentile, Martinton 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 Martinton
With 94.3% of buildings rated Minimal exposure, Martinton gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Martinton's figures come from
Martinton's 0th-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 Martinton's dominant minimal exposure actually means, with real examples from across the dataset.