Sandpoint, ID
Sandpoint wildfire risk explained
Sandpoint's 4,197 buildings earn a 62nd-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sandpoint at the 56th national percentile — 6 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Sandpoint's buildings (63.7%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Sandpoint ranks
Sandpoint's 62nd national percentile looks worse in isolation than its 29th ranking inside Idaho does — this place is on the milder end for its own state, by 33 points. Among the 31,521 US communities USFS scores, Sandpoint ranks 12,095 for wildfire risk (1 is highest) and 4,062 by building count (1 is largest). Within Idaho alone, it ranks 167 of 232 places by risk. See the full county-by-county picture for Idaho on its state page.
Sandpoint and the insurance market
Sandpoint's 62nd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Sandpoint
With ember exposure the dominant pattern in Sandpoint (63.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Sandpoint's figures come from
The methodology guide shows exactly how USFS turned 4,197 counted buildings into the percentiles shown above for Sandpoint. The exposure-zones guide covers what Sandpoint's dominant indirect exposure actually means, with real examples from across the dataset.