Pleasanton, NE
How exposed is Pleasanton to wildfire?
Pleasanton sits at the 67th 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 269 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Pleasanton at the 61st national percentile — 6 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Pleasanton's buildings actually sit
Indirect exposure is dominant in Pleasanton (91.8% of 269 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 8.2% sit in the Direct zone.
How Pleasanton compares
Pleasanton's risk sits at a similar level relative to Nebraska (63rd percentile statewide) as it does nationally (67th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Pleasanton ranks 10,405 for wildfire risk (1 is highest) and 22,540 by building count (1 is largest). Within Nebraska alone, it ranks 218 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
Shopping for coverage in Pleasanton
At the 67th percentile nationally, Pleasanton carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in Pleasanton
Because 91.8% of Pleasanton's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Pleasanton's figures come from
The methodology guide shows exactly how USFS turned 269 counted buildings into the percentiles shown above for Pleasanton. The exposure-zones guide covers what Pleasanton's dominant indirect exposure actually means, with real examples from across the dataset.