Cordova, NC
How exposed is Cordova to wildfire?
Cordova's 986 buildings earn a 80th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Cordova's burn probability — fire likelihood with no building count factored in — sits at the 82nd percentile nationally.
Cordova's building exposure, zone by zone
USFS classifies 68.5% of Cordova's buildings as Direct exposure, higher than its 31.5% Indirect share and far above its 0% Minimal share — a profile where 675 structures sit close enough to vegetation that lot clearing matters most.
Cordova against the rest of the country
Cordova scores 80th nationally and 86th within North Carolina — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Cordova ranks 6,275 for wildfire risk (1 is highest) and 12,036 by building count (1 is largest). Within North Carolina alone, it ranks 112 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Cordova and the insurance market
Cordova's 80th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
With 68.5% of Cordova 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 Cordova's figures come from
The methodology guide shows exactly how USFS turned 986 counted buildings into the percentiles shown above for Cordova. The exposure-zones guide covers what Cordova's dominant direct exposure actually means, with real examples from across the dataset.