WildfireRiskFinder

De Smet, ID

How exposed is De Smet to wildfire?

High
77thpercentile nationally

Out of every US place USFS scores, De Smet lands at the 77th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 71 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts De Smet at the 78th percentile, close to its 77th-percentile risk score.

De Smet's building exposure, zone by zone

71Total buildings
28.2%Direct exposure
71.8%Indirect exposure
0%Minimal exposure

71 buildings are counted in De Smet, and 71.8% of them are Indirect exposure — ember-driven risk rather than the 28.2% in Direct exposure or the 0% rated Minimal.

Where De Smet ranks

De Smet ranks lower within Idaho (43rd percentile statewide) than its 77th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, De Smet ranks 7,341 for wildfire risk (1 is highest) and 30,238 by building count (1 is largest). Within Idaho alone, it ranks 132 of 232 places by risk. See the full county-by-county picture for Idaho on its state page.

De Smet and the insurance market

De Smet's high rating (77th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

Lowering exposure, not just insuring around it

With ember exposure the dominant pattern in De Smet (71.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where De Smet's figures come from

De Smet's 77th-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 De Smet's dominant indirect exposure actually means, with real examples from across the dataset.