WildfireRiskFinder

Sublimity, OR

Sublimity wildfire risk explained

Moderate
21stpercentile nationally

Sublimity's 1,262 buildings earn a 21st-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Sublimity's burn probability — fire likelihood with no building count factored in — sits at the 24th percentile nationally.

Where Sublimity's buildings actually sit

1,262Total buildings
6%Direct exposure
76.5%Indirect exposure
17.5%Minimal exposure

USFS puts 76.5% of Sublimity's 1,262 buildings in the Indirect exposure zone, versus 6% Direct and 17.5% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.

Sublimity against the rest of the country

Sublimity scores 21st nationally and 14th within Oregon — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Sublimity ranks 25,003 for wildfire risk (1 is highest) and 10,287 by building count (1 is largest). Within Oregon alone, it ranks 362 of 420 places by risk. See the full county-by-county picture for Oregon on its state page.

Sublimity and the insurance market

Sublimity's 21st-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

Because 76.5% of Sublimity's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.

Where Sublimity's figures come from

Sublimity's 21st-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 Sublimity's dominant indirect exposure actually means, with real examples from across the dataset.