WildfireRiskFinder

Cut Off, LA

Cut Off, LA's wildfire risk, in USFS's own numbers

Moderate
35thpercentile nationally

Out of every US place USFS scores, Cut Off lands at the 35th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 3,788 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Cut Off at the 26th percentile, close to its 35th-percentile risk score.

Cut Off's building exposure, zone by zone

3,788Total buildings
34.9%Direct exposure
65.1%Indirect exposure
0%Minimal exposure

3,788 buildings are counted in Cut Off, and 65.1% of them are Indirect exposure — ember-driven risk rather than the 34.9% in Direct exposure or the 0% rated Minimal.

How Cut Off compares

Cut Off's risk sits at a similar level relative to Louisiana (34th percentile statewide) as it does nationally (35th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Cut Off ranks 20,387 for wildfire risk (1 is highest) and 4,438 by building count (1 is largest). Within Louisiana alone, it ranks 323 of 488 places by risk. See the full county-by-county picture for Louisiana on its state page.

Cut Off and the insurance market

Cut Off's moderate rating (35th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Lowering exposure, not just insuring around it

With ember exposure the dominant pattern in Cut Off (65.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Cut Off's figures come from

Cut Off's 35th-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 Cut Off's dominant indirect exposure actually means, with real examples from across the dataset.