Nettleton, MS
Nettleton wildfire risk explained
USFS scores Nettleton at the 53rd national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 1,123 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Nettleton at the 55th percentile, close to its 53rd-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 59.3% of Nettleton's buildings as Direct exposure, higher than its 40.7% Indirect share and far above its 0% Minimal share — a profile where 666 structures sit close enough to vegetation that lot clearing matters most.
Nettleton against the rest of the country
Nettleton's 53rd national percentile looks worse in isolation than its 21st ranking inside Mississippi does — this place is on the milder end for its own state, by 32 points. Among the 31,521 US communities USFS scores, Nettleton ranks 14,845 for wildfire risk (1 is highest) and 11,132 by building count (1 is largest). Within Mississippi alone, it ranks 331 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
Shopping for coverage in Nettleton
Nettleton'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.
Lowering exposure, not just insuring around it
With 59.3% of Nettleton 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 Nettleton's figures come from
Nettleton's 53rd-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 Nettleton's dominant direct exposure actually means, with real examples from across the dataset.