WildfireRiskFinder

Luana, IA

Luana wildfire risk explained

Low
9thpercentile nationally

USFS scores Luana at the 9th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 209 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Luana at the 10th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Luana's buildings actually sit

209Total buildings
23%Direct exposure
0%Indirect exposure
77%Minimal exposure

77% of Luana's 209 buildings sit in USFS's Minimal exposure zone, with only 23% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

Where Luana ranks

Luana's risk sits at a similar level relative to Iowa (19th percentile statewide) as it does nationally (9th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Luana ranks 28,552 for wildfire risk (1 is highest) and 24,510 by building count (1 is largest). Within Iowa alone, it ranks 825 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.

Luana and the insurance market

Luana's low wildfire rating (9th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.

Hardening a home in Luana

Luana's 77% 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 Luana's figures come from

Luana's 9th-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 Luana's dominant minimal exposure actually means, with real examples from across the dataset.