Saugatuck, CT
How exposed is Saugatuck to wildfire?
USFS scores Saugatuck at the 21st national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 2,684 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Saugatuck at the 22nd percentile, close to its 21st-percentile risk score.
What "at risk" means for the buildings here
Most of Saugatuck's buildings (84.4% of 2,684) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
Where Saugatuck ranks
There's little gap between Saugatuck's 21st national percentile and its 11th percentile inside Connecticut, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Saugatuck ranks 24,951 for wildfire risk (1 is highest) and 5,957 by building count (1 is largest). Within Connecticut alone, it ranks 190 of 214 places by risk. See the full county-by-county picture for Connecticut on its state page.
What this risk score means for insurance
At the 21st national percentile, Saugatuck rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Saugatuck
Even with 84.4% of Saugatuck outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Saugatuck's figures come from
Saugatuck's 21st-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 Saugatuck's dominant minimal exposure actually means, with real examples from across the dataset.