WildfireRiskFinder

Calverton, VA

Calverton, VA's wildfire risk, in USFS's own numbers

Moderate
24thpercentile nationally

Calverton's 393 buildings earn a 24th-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Calverton at the 25th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

Calverton's building exposure, zone by zone

393Total buildings
76.8%Direct exposure
23.2%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Calverton: 76.8% of its 393 buildings, versus 23.2% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

How Calverton compares

Calverton scores 24th nationally and 14th within Virginia — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Calverton ranks 23,903 for wildfire risk (1 is highest) and 19,358 by building count (1 is largest). Within Virginia alone, it ranks 583 of 681 places by risk. See the full county-by-county picture for Virginia on its state page.

Calverton and the insurance market

Calverton's moderate wildfire rating (24th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.

Hardening a home in Calverton

Because Direct exposure dominates in Calverton (76.8%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Calverton's figures come from

The methodology guide shows exactly how USFS turned 393 counted buildings into the percentiles shown above for Calverton. The exposure-zones guide covers what Calverton's dominant direct exposure actually means, with real examples from across the dataset.