Lancaster, SC
How exposed is Lancaster to wildfire?
USFS's Wildfire Risk to Communities model puts Lancaster at the 50th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 3,913 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lancaster's burn probability — fire likelihood with no building count factored in — sits at the 52nd percentile nationally.
Lancaster's building exposure, zone by zone
48% of Lancaster's 3,913 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 39.4% Direct and 12.7% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Lancaster against the rest of the country
Lancaster ranks lower within South Carolina (2nd percentile statewide) than its 50th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Lancaster ranks 15,931 for wildfire risk (1 is highest) and 4,325 by building count (1 is largest). Within South Carolina alone, it ranks 464 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
Shopping for coverage in Lancaster
Lancaster's elevated rating (50th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Because 48% of Lancaster's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Lancaster's figures come from
Every one of the two percentiles behind Lancaster's 15,931-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Lancaster's dominant indirect exposure actually means, with real examples from across the dataset.