Pooler, GA
Pooler wildfire risk explained
Pooler's 10,312 buildings earn a 60th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Pooler's burn probability — fire likelihood with no building count factored in — sits at the 61st percentile nationally.
Pooler's building exposure, zone by zone
10,312 buildings are counted in Pooler, and 45.1% of them are Indirect exposure — ember-driven risk rather than the 41.6% in Direct exposure or the 13.3% rated Minimal. At 10,312 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
How Pooler compares
Inside Georgia, Pooler sits at just the 20th percentile even though it scores 60th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Pooler ranks 12,503 for wildfire risk (1 is highest) and 1,550 by building count (1 is largest). Within Georgia alone, it ranks 536 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
Pooler and the insurance market
At the 60th percentile nationally, Pooler carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Because 45.1% of Pooler's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Pooler's figures come from
Pooler's 60th-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 Pooler's dominant indirect exposure actually means, with real examples from across the dataset.