WildfireRiskFinder

Oberlin, KS

Oberlin, KS's wildfire risk, in USFS's own numbers

Elevated
46thpercentile nationally

Oberlin's 1,431 buildings earn a 46th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Oberlin at the 45th 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

1,431Total buildings
6.1%Direct exposure
93.9%Indirect exposure
0%Minimal exposure

1,431 buildings are counted in Oberlin, and 93.9% of them are Indirect exposure — ember-driven risk rather than the 6.1% in Direct exposure or the 0% rated Minimal.

How Oberlin compares

Oberlin ranks lower within Kansas (24th percentile statewide) than its 46th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Oberlin ranks 16,887 for wildfire risk (1 is highest) and 9,472 by building count (1 is largest). Within Kansas alone, it ranks 548 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.

Oberlin and the insurance market

At the 46th national percentile, Oberlin rates elevated 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 ember exposure the dominant pattern in Oberlin (93.9% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Oberlin's figures come from

Every one of the two percentiles behind Oberlin's 16,887-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Oberlin's dominant indirect exposure actually means, with real examples from across the dataset.