WildfireRiskFinder

Lapel, IN

Lapel wildfire risk explained

Low
2ndpercentile nationally

USFS's Wildfire Risk to Communities model puts Lapel at the 2nd national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,468 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Lapel at the 2nd 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

1,468Total buildings
15.5%Direct exposure
0%Indirect exposure
84.5%Minimal exposure

Lapel rates 84.5% Minimal exposure against just 15.5% Direct and 0% Indirect — of 1,468 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

Where Lapel ranks

Lapel scores 2nd nationally and 16th within Indiana — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Lapel ranks 30,825 for wildfire risk (1 is highest) and 9,318 by building count (1 is largest). Within Indiana alone, it ranks 814 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.

Lapel and the insurance market

Lapel's low rating (2nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Lowering exposure, not just insuring around it

With 84.5% of buildings rated Minimal exposure, Lapel gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Lapel's figures come from

Lapel's 2nd-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 Lapel's dominant minimal exposure actually means, with real examples from across the dataset.