WildfireRiskFinder

Weyerhaeuser, WI

Weyerhaeuser wildfire risk explained

Low
11thpercentile nationally

Weyerhaeuser's 251 buildings earn a 11th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Weyerhaeuser's burn probability — fire likelihood with no building count factored in — sits at the 10th percentile nationally.

What "at risk" means for the buildings here

251Total buildings
18.3%Direct exposure
81.7%Indirect exposure
0%Minimal exposure

251 buildings are counted in Weyerhaeuser, and 81.7% of them are Indirect exposure — ember-driven risk rather than the 18.3% in Direct exposure or the 0% rated Minimal.

Where Weyerhaeuser ranks

Weyerhaeuser scores 11th nationally and 8th within Wisconsin — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Weyerhaeuser ranks 28,131 for wildfire risk (1 is highest) and 23,124 by building count (1 is largest). Within Wisconsin alone, it ranks 746 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.

Weyerhaeuser and the insurance market

Weyerhaeuser's low rating (11th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Lowering exposure, not just insuring around it

Weyerhaeuser's 81.7% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.

Where Weyerhaeuser's figures come from

Weyerhaeuser's 11th-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 Weyerhaeuser's dominant indirect exposure actually means, with real examples from across the dataset.