Chincoteague, VA
Chincoteague wildfire risk explained
Chincoteague sits at the 76th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 4,584 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Chincoteague's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
Chincoteague's building exposure, zone by zone
55.8% of Chincoteague's 4,584 buildings sit in USFS's Minimal exposure zone, with only 26.2% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Chincoteague ranks
Chincoteague scores 76th nationally and 90th 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, Chincoteague ranks 7,517 for wildfire risk (1 is highest) and 3,718 by building count (1 is largest). Within Virginia alone, it ranks 68 of 681 places by risk. See the full county-by-county picture for Virginia on its state page.
Chincoteague and the insurance market
Chincoteague's high rating (76th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Hardening a home in Chincoteague
Even with 55.8% of Chincoteague outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Chincoteague's figures come from
The methodology guide shows exactly how USFS turned 4,584 counted buildings into the percentiles shown above for Chincoteague. The exposure-zones guide covers what Chincoteague's dominant minimal exposure actually means, with real examples from across the dataset.