WildfireRiskFinder

Marshall, IN

Marshall, IN's wildfire risk, in USFS's own numbers

Low
9thpercentile nationally

Marshall's 245 buildings earn a 9th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Marshall at the 8th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

245Total buildings
42.5%Direct exposure
0.4%Indirect exposure
57.1%Minimal exposure

USFS classifies 57.1% of Marshall's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 42.5% Direct and 0.4% Indirect — a landscape-level risk rather than a building-by-building one.

Marshall against the rest of the country

Compare Marshall's two percentiles: 52nd within Indiana, only 9th nationally — a gap of 43 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Marshall ranks 28,767 for wildfire risk (1 is highest) and 23,290 by building count (1 is largest). Within Indiana alone, it ranks 468 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.

What this risk score means for insurance

At the 9th national percentile, Marshall 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

Marshall's 57.1% 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 Marshall's figures come from

The methodology guide shows exactly how USFS turned 245 counted buildings into the percentiles shown above for Marshall. The exposure-zones guide covers what Marshall's dominant minimal exposure actually means, with real examples from across the dataset.