Seven Corners, VA
Seven Corners wildfire risk explained
USFS scores Seven Corners at the 9th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 648 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Seven Corners's burn probability — fire likelihood with no building count factored in — sits at the 9th percentile nationally.
Seven Corners's building exposure, zone by zone
79.8% of Seven Corners's 648 buildings sit in USFS's Minimal exposure zone, with only 20.2% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
How Seven Corners compares
There's little gap between Seven Corners's 9th national percentile and its 1st percentile inside Virginia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Seven Corners ranks 28,826 for wildfire risk (1 is highest) and 15,226 by building count (1 is largest). Within Virginia alone, it ranks 676 of 681 places by risk. See the full county-by-county picture for Virginia on its state page.
What this risk score means for insurance
At the 9th national percentile, Seven Corners rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Even with 79.8% of Seven Corners outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Seven Corners's figures come from
The methodology guide shows exactly how USFS turned 648 counted buildings into the percentiles shown above for Seven Corners. The exposure-zones guide covers what Seven Corners's dominant minimal exposure actually means, with real examples from across the dataset.