WildfireRiskFinder

Deering, AK

How exposed is Deering to wildfire?

Elevated
51stpercentile nationally

USFS scores Deering at the 51st national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 73 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 Deering at the 55th percentile, close to its 51st-percentile risk score.

Where Deering's buildings actually sit

73Total buildings
6.9%Direct exposure
0%Indirect exposure
93.2%Minimal exposure

Most of Deering's buildings (93.2% of 73) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.

Deering against the rest of the country

Deering scores 51st nationally and 41st within Alaska — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Deering ranks 15,589 for wildfire risk (1 is highest) and 30,155 by building count (1 is largest). Within Alaska alone, it ranks 192 of 322 places by risk. See the full county-by-county picture for Alaska on its state page.

Shopping for coverage in Deering

Deering's elevated rating (51st 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 Deering

Deering's 93.2% 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 Deering's figures come from

Every one of the two percentiles behind Deering's 15,589-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Deering's dominant minimal exposure actually means, with real examples from across the dataset.