Sweet Home, OR
Sweet Home, OR's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Sweet Home at the 64th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 4,633 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sweet Home at the 65th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Sweet Home's building exposure, zone by zone
81.8% of Sweet Home's 4,633 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 18.2% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Sweet Home compares
There's little gap between Sweet Home's 64th national percentile and its 52nd percentile inside Oregon, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sweet Home ranks 11,448 for wildfire risk (1 is highest) and 3,669 by building count (1 is largest). Within Oregon alone, it ranks 204 of 420 places by risk. See the full county-by-county picture for Oregon on its state page.
Sweet Home and the insurance market
Sweet Home's 64th-percentile score lands in Oregon, the only two states requiring a wildfire disclosure at sale. Oregon's own hazard map feeds directly into that disclosure requirement. The disclosure-law guide covers what it requires.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Sweet Home (81.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Sweet Home's figures come from
The methodology guide shows exactly how USFS turned 4,633 counted buildings into the percentiles shown above for Sweet Home. The exposure-zones guide covers what Sweet Home's dominant indirect exposure actually means, with real examples from across the dataset.