Emma, NC
Emma wildfire risk explained
Emma sits at the 47th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,106 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Emma's burn probability — fire likelihood with no building count factored in — sits at the 50th percentile nationally.
What "at risk" means for the buildings here
Most of Emma's buildings (56.3%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Emma compares
Inside North Carolina, Emma sits at just the 31st percentile even though it scores 47th 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, Emma ranks 16,738 for wildfire risk (1 is highest) and 11,245 by building count (1 is largest). Within North Carolina alone, it ranks 531 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
What this risk score means for insurance
Emma's elevated rating (47th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
With ember exposure the dominant pattern in Emma (56.3% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Emma's figures come from
Every one of the two percentiles behind Emma's 16,738-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Emma's dominant indirect exposure actually means, with real examples from across the dataset.