WildfireRiskFinder

Baltic, CT

Baltic, CT's wildfire risk, in USFS's own numbers

Moderate
35thpercentile nationally

USFS scores Baltic at the 35th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 458 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Baltic's burn probability — fire likelihood with no building count factored in — sits at the 32nd percentile nationally.

Baltic's building exposure, zone by zone

458Total buildings
43.5%Direct exposure
56.6%Indirect exposure
0%Minimal exposure

Indirect exposure is dominant in Baltic (56.6% of 458 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 43.5% sit in the Direct zone.

Baltic against the rest of the country

Compare Baltic's two percentiles: 62nd within Connecticut, only 35th nationally — a gap of 27 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Baltic ranks 20,477 for wildfire risk (1 is highest) and 18,096 by building count (1 is largest). Within Connecticut alone, it ranks 83 of 214 places by risk. See the full county-by-county picture for Connecticut on its state page.

Shopping for coverage in Baltic

Baltic'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.

What would actually reduce this score

Because 56.6% of Baltic'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 Baltic's figures come from

The methodology guide shows exactly how USFS turned 458 counted buildings into the percentiles shown above for Baltic. The exposure-zones guide covers what Baltic's dominant indirect exposure actually means, with real examples from across the dataset.