Greenwood, MO
Greenwood, MO's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Greenwood lands at the 47th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 2,409 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Greenwood at the 47th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Greenwood's buildings actually sit
Indirect exposure is dominant in Greenwood (60% of 2,409 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 34.8% sit in the Direct zone.
Greenwood against the rest of the country
Greenwood ranks lower within Missouri (26th percentile statewide) than its 47th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Greenwood ranks 16,863 for wildfire risk (1 is highest) and 6,495 by building count (1 is largest). Within Missouri alone, it ranks 786 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Shopping for coverage in Greenwood
Greenwood's elevated wildfire rating (47th 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.
What would actually reduce this score
With ember exposure the dominant pattern in Greenwood (60% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Greenwood's figures come from
Greenwood's 47th-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 Greenwood's dominant indirect exposure actually means, with real examples from across the dataset.