Dunlap, TN
Dunlap wildfire risk explained
USFS scores Dunlap at the 83rd national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 2,886 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Dunlap's burn probability — fire likelihood with no building count factored in — sits at the 87th percentile nationally.
What "at risk" means for the buildings here
Direct exposure dominates in Dunlap: 63.1% of its 2,886 buildings, versus 36.9% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Dunlap ranks
There's little gap between Dunlap's 83rd national percentile and its 92nd percentile inside Tennessee, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Dunlap ranks 5,307 for wildfire risk (1 is highest) and 5,606 by building count (1 is largest). Within Tennessee alone, it ranks 41 of 502 places by risk. See the full county-by-county picture for Tennessee on its state page.
Dunlap and the insurance market
Dunlap's 83rd-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Dunlap (63.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Dunlap's figures come from
Every one of the two percentiles behind Dunlap's 5,307-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Dunlap's dominant direct exposure actually means, with real examples from across the dataset.