WildfireRiskFinder

Redkey, IN

Redkey wildfire risk explained

Low
1stpercentile nationally

USFS scores Redkey at the 1st national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 828 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Redkey at the 1st percentile, close to its 1st-percentile risk score.

What "at risk" means for the buildings here

828Total buildings
10.3%Direct exposure
0%Indirect exposure
89.7%Minimal exposure

Only 10.3% of Redkey's 828 buildings carry Direct exposure and 0% carry Indirect; the remaining 89.7% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.

Redkey against the rest of the country

Redkey scores 1st nationally and 6th 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, Redkey ranks 31,270 for wildfire risk (1 is highest) and 13,367 by building count (1 is largest). Within Indiana alone, it ranks 916 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 1st national percentile, Redkey rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

What would actually reduce this score

Redkey's 89.7% 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 Redkey's figures come from

Every one of the two percentiles behind Redkey's 31,270-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Redkey's dominant minimal exposure actually means, with real examples from across the dataset.