Poplar Plains, CT
How exposed is Poplar Plains to wildfire?
USFS's Wildfire Risk to Communities model puts Poplar Plains at the 29th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 1,209 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Poplar Plains's burn probability — fire likelihood with no building count factored in — sits at the 29th percentile nationally.
What "at risk" means for the buildings here
93.9% of Poplar Plains's 1,209 buildings sit in USFS's Direct exposure zone, roughly 1,135 structures close enough to burnable vegetation for flame contact, not just embers — 0.3% fall in the Indirect, ember-only zone and 5.9% are Minimal.
Where Poplar Plains ranks
Poplar Plains scores 29th nationally and 41st within Connecticut — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Poplar Plains ranks 22,242 for wildfire risk (1 is highest) and 10,594 by building count (1 is largest). Within Connecticut alone, it ranks 127 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
Poplar Plains's moderate rating (29th 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
Poplar Plains's 93.9% 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 Poplar Plains's figures come from
Every one of the two percentiles behind Poplar Plains's 22,242-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Poplar Plains's dominant direct exposure actually means, with real examples from across the dataset.