Oglala, SD
Oglala wildfire risk explained
USFS scores Oglala at the 96th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 416 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Oglala at the 97th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Direct exposure dominates in Oglala: 69.2% of its 416 buildings, versus 30.8% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Oglala ranks
Oglala's risk sits at a similar level relative to South Dakota (99th percentile statewide) as it does nationally (96th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Oglala ranks 1,244 for wildfire risk (1 is highest) and 18,914 by building count (1 is largest). Within South Dakota alone, it ranks 6 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
Oglala and the insurance market
At the 96th percentile nationally, Oglala carries the very 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.
Lowering exposure, not just insuring around it
With 69.2% of Oglala in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Oglala's figures come from
Every one of the two percentiles behind Oglala's 1,244-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Oglala's dominant direct exposure actually means, with real examples from across the dataset.