New London, WI
New London, WI's wildfire risk, in USFS's own numbers
New London sits at the 35th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 3,646 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, New London's burn probability — fire likelihood with no building count factored in — sits at the 36th percentile nationally.
What "at risk" means for the buildings here
Most of New London's buildings (89.6%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
New London against the rest of the country
Compare New London's two percentiles: 83rd within Wisconsin, only 35th nationally — a gap of 48 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, New London ranks 20,376 for wildfire risk (1 is highest) and 4,592 by building count (1 is largest). Within Wisconsin alone, it ranks 136 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
What this risk score means for insurance
New London'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 89.6% of New London'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 New London's figures come from
The methodology guide shows exactly how USFS turned 3,646 counted buildings into the percentiles shown above for New London. The exposure-zones guide covers what New London's dominant indirect exposure actually means, with real examples from across the dataset.