Ridgeland, SC
Ridgeland wildfire risk explained
USFS's Wildfire Risk to Communities model puts Ridgeland at the 80th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 1,311 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Ridgeland at the 78th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Ridgeland's building exposure, zone by zone
1,311 buildings are counted in Ridgeland, and 61.1% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Ridgeland against the rest of the country
Ridgeland scores 80th nationally and 85th 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, Ridgeland ranks 6,188 for wildfire risk (1 is highest) and 10,019 by building count (1 is largest). Within South Carolina alone, it ranks 70 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
Shopping for coverage in Ridgeland
Ridgeland's 80th-percentile, very 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.
What would actually reduce this score
Because Direct exposure dominates in Ridgeland (61.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Ridgeland's figures come from
The methodology guide shows exactly how USFS turned 1,311 counted buildings into the percentiles shown above for Ridgeland. The exposure-zones guide covers what Ridgeland's dominant direct exposure actually means, with real examples from across the dataset.