WildfireRiskFinder

Elon, NC

Elon wildfire risk explained

Elevated
51stpercentile nationally

Elon's 2,637 buildings earn a 51st-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Elon at the 53rd percentile, close to its 51st-percentile risk score.

What "at risk" means for the buildings here

2,637Total buildings
40%Direct exposure
27.9%Indirect exposure
32.2%Minimal exposure

USFS classifies 40% of Elon's buildings as Direct exposure, higher than its 27.9% Indirect share and far above its 32.2% Minimal share — a profile where 1,054 structures sit close enough to vegetation that lot clearing matters most.

Elon against the rest of the country

There's little gap between Elon's 51st national percentile and its 40th percentile inside North Carolina, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Elon ranks 15,603 for wildfire risk (1 is highest) and 6,038 by building count (1 is largest). Within North Carolina alone, it ranks 467 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.

Elon and the insurance market

Elon's elevated rating (51st 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

Because Direct exposure dominates in Elon (40%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Elon's figures come from

Every one of the two percentiles behind Elon's 15,603-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Elon's dominant direct exposure actually means, with real examples from across the dataset.