Lone Grove, OK
Lone Grove, OK's wildfire risk, in USFS's own numbers
USFS scores Lone Grove at the 90th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 3,304 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lone Grove's burn probability — fire likelihood with no building count factored in — sits at the 91st percentile nationally.
What "at risk" means for the buildings here
Direct exposure dominates in Lone Grove: 74.7% of its 3,304 buildings, versus 23.5% Indirect and 1.8% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Lone Grove compares
Lone Grove's 90th national percentile looks worse in isolation than its 48th ranking inside Oklahoma does — this place is on the milder end for its own state, by 42 points. Among the 31,521 US communities USFS scores, Lone Grove ranks 3,128 for wildfire risk (1 is highest) and 5,041 by building count (1 is largest). Within Oklahoma alone, it ranks 433 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Lone Grove and the insurance market
Lone Grove's very high rating (90th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
With 74.7% of Lone Grove 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 Lone Grove's figures come from
Lone Grove's 90th-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 Lone Grove's dominant direct exposure actually means, with real examples from across the dataset.