WildfireRiskFinder

Netawaka, KS

How exposed is Netawaka to wildfire?

Very High
80thpercentile nationally

Netawaka's 141 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.)

Fire likelihood alone (USFS's burn-probability figure) ranks Netawaka at the 82nd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Netawaka's buildings actually sit

141Total buildings
69.5%Direct exposure
0%Indirect exposure
30.5%Minimal exposure

USFS classifies 69.5% of Netawaka's buildings as Direct exposure, higher than its 0% Indirect share and far above its 30.5% Minimal share — a profile where 98 structures sit close enough to vegetation that lot clearing matters most.

Where Netawaka ranks

Netawaka scores 80th nationally and 79th within Kansas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Netawaka ranks 6,268 for wildfire risk (1 is highest) and 27,251 by building count (1 is largest). Within Kansas alone, it ranks 151 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.

What this risk score means for insurance

Netawaka's very high rating (80th 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.

What would actually reduce this score

Netawaka's 69.5% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.

Where Netawaka's figures come from

The methodology guide shows exactly how USFS turned 141 counted buildings into the percentiles shown above for Netawaka. The exposure-zones guide covers what Netawaka's dominant direct exposure actually means, with real examples from across the dataset.