Garland, TN
How exposed is Garland to wildfire?
Out of every US place USFS scores, Garland lands at the 32nd percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 220 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Garland at the 32nd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Direct exposure dominates in Garland: 92.3% of its 220 buildings, versus 5% Indirect and 2.7% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Garland compares
There's little gap between Garland's 32nd national percentile and its 21st percentile inside Tennessee, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Garland ranks 21,351 for wildfire risk (1 is highest) and 24,138 by building count (1 is largest). Within Tennessee alone, it ranks 395 of 502 places by risk. See the full county-by-county picture for Tennessee on its state page.
What this risk score means for insurance
At the 32nd national percentile, Garland rates moderate 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
Garland's 92.3% 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 Garland's figures come from
Every one of the two percentiles behind Garland's 21,351-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Garland's dominant direct exposure actually means, with real examples from across the dataset.