Seven Lakes, NC
Seven Lakes wildfire risk explained
Seven Lakes 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 2,877 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Seven Lakes at the 78th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Seven Lakes's buildings actually sit
2,877 buildings are counted in Seven Lakes, and 58.4% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 5.2% rated Minimal.
Where Seven Lakes ranks
Seven Lakes's risk sits at a similar level relative to North Carolina (79th percentile statewide) as it does nationally (77th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Seven Lakes ranks 7,191 for wildfire risk (1 is highest) and 5,619 by building count (1 is largest). Within North Carolina alone, it ranks 161 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
What this risk score means for insurance
Seven Lakes'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.
Hardening a home in Seven Lakes
Seven Lakes's 58.4% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Seven Lakes's figures come from
Seven Lakes'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 Seven Lakes's dominant direct exposure actually means, with real examples from across the dataset.