WildfireRiskFinder

Hardinsburg, IN

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

Moderate
22ndpercentile nationally

Hardinsburg's 230 buildings earn a 22nd-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Hardinsburg at the 23rd national percentile — 1 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

230Total buildings
57%Direct exposure
43%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Hardinsburg: 57% of its 230 buildings, versus 43% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

Hardinsburg against the rest of the country

Compare Hardinsburg's two percentiles: 85th within Indiana, only 22nd nationally — a gap of 63 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Hardinsburg ranks 24,701 for wildfire risk (1 is highest) and 23,792 by building count (1 is largest). Within Indiana alone, it ranks 149 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

Hardinsburg's moderate rating (22nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Hardinsburg

Because Direct exposure dominates in Hardinsburg (57%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Hardinsburg's figures come from

The methodology guide shows exactly how USFS turned 230 counted buildings into the percentiles shown above for Hardinsburg. The exposure-zones guide covers what Hardinsburg's dominant direct exposure actually means, with real examples from across the dataset.