Salley, SC
Salley, SC's wildfire risk, in USFS's own numbers
Salley's 269 buildings earn a 69th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Salley at the 69th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Salley's buildings actually sit
USFS classifies 65.4% of Salley's buildings as Direct exposure, higher than its 34.6% Indirect share and far above its 0% Minimal share — a profile where 176 structures sit close enough to vegetation that lot clearing matters most.
Where Salley ranks
Salley scores 69th nationally and 54th within South Carolina — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Salley ranks 9,750 for wildfire risk (1 is highest) and 22,549 by building count (1 is largest). Within South Carolina alone, it ranks 218 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
Salley and the insurance market
Salley's 69th-percentile, 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.
Hardening a home in Salley
With 65.4% of Salley 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 Salley's figures come from
Salley's 69th-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 Salley's dominant direct exposure actually means, with real examples from across the dataset.