Wood, SD
Wood, SD's wildfire risk, in USFS's own numbers
Wood sits at the 75th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 82 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Wood at the 71st percentile, close to its 75th-percentile risk score.
Wood's building exposure, zone by zone
68.3% of Wood's 82 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 31.7% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Wood compares
Wood's risk sits at a similar level relative to South Dakota (73rd percentile statewide) as it does nationally (75th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Wood ranks 7,797 for wildfire risk (1 is highest) and 29,824 by building count (1 is largest). Within South Dakota alone, it ranks 119 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
What this risk score means for insurance
At the 75th percentile nationally, Wood carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Wood's 68.3% 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 Wood's figures come from
The methodology guide shows exactly how USFS turned 82 counted buildings into the percentiles shown above for Wood. The exposure-zones guide covers what Wood's dominant indirect exposure actually means, with real examples from across the dataset.