Heartwell, NE
Heartwell, NE's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Heartwell lands at the 5th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 66 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Heartwell at the 4th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 90.9% of Heartwell's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 9.1% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
How Heartwell compares
Heartwell's risk sits at a similar level relative to Nebraska (2nd percentile statewide) as it does nationally (5th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Heartwell ranks 29,917 for wildfire risk (1 is highest) and 30,436 by building count (1 is largest). Within Nebraska alone, it ranks 572 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
What this risk score means for insurance
At the 5th national percentile, Heartwell rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With 90.9% of buildings rated Minimal exposure, Heartwell gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Heartwell's figures come from
Heartwell's 5th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Heartwell's dominant minimal exposure actually means, with real examples from across the dataset.