Mayland, TN
Mayland, TN's wildfire risk, in USFS's own numbers
Mayland sits at the 77th 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 377 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Mayland at the 80th national percentile — 3 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
Of Mayland's 377 counted buildings, 89.7% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How Mayland compares
There's little gap between Mayland's 77th national percentile and its 80th percentile inside Tennessee, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Mayland ranks 7,287 for wildfire risk (1 is highest) and 19,731 by building count (1 is largest). Within Tennessee alone, it ranks 99 of 502 places by risk. See the full county-by-county picture for Tennessee on its state page.
What this risk score means for insurance
Mayland's high rating (77th 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
Because Direct exposure dominates in Mayland (89.7%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Mayland's figures come from
Mayland's 77th-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 Mayland's dominant direct exposure actually means, with real examples from across the dataset.