Martin, GA
Martin, GA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Martin lands at the 69th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 288 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 Martin at the 72nd percentile, close to its 69th-percentile risk score.
Martin's building exposure, zone by zone
288 buildings are counted in Martin, and 89.6% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Martin against the rest of the country
Martin's risk sits at a similar level relative to Georgia (59th percentile statewide) as it does nationally (69th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Martin ranks 9,924 for wildfire risk (1 is highest) and 21,954 by building count (1 is largest). Within Georgia alone, it ranks 273 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
Martin and the insurance market
Martin's 69th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Martin's 89.6% 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 Martin's figures come from
Martin's 69th-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 Martin's dominant direct exposure actually means, with real examples from across the dataset.