India Hook, SC
India Hook wildfire risk explained
USFS scores India Hook at the 53rd national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 1,569 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks India Hook at the 57th national percentile — 4 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
1,569 buildings are counted in India Hook, and 72.6% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 3.4% rated Minimal.
India Hook against the rest of the country
Inside South Carolina, India Hook sits at just the 7th percentile even though it scores 53rd nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, India Hook ranks 14,824 for wildfire risk (1 is highest) and 8,892 by building count (1 is largest). Within South Carolina alone, it ranks 444 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
India Hook and the insurance market
India Hook's elevated rating (53rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in India Hook
With 72.6% of India Hook 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 India Hook's figures come from
The methodology guide shows exactly how USFS turned 1,569 counted buildings into the percentiles shown above for India Hook. The exposure-zones guide covers what India Hook's dominant direct exposure actually means, with real examples from across the dataset.