Siasconset, MA
How exposed is Siasconset to wildfire?
Siasconset sits at the 23rd 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 1,126 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Siasconset at the 21st national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS puts 65.6% of Siasconset's 1,126 buildings in the Indirect exposure zone, versus 34.4% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Siasconset compares
Siasconset's risk sits at a similar level relative to Massachusetts (36th percentile statewide) as it does nationally (23rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Siasconset ranks 24,176 for wildfire risk (1 is highest) and 11,109 by building count (1 is largest). Within Massachusetts alone, it ranks 159 of 248 places by risk. See the full county-by-county picture for Massachusetts on its state page.
Shopping for coverage in Siasconset
Siasconset's moderate rating (23rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Siasconset (65.6% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Siasconset's figures come from
The methodology guide shows exactly how USFS turned 1,126 counted buildings into the percentiles shown above for Siasconset. The exposure-zones guide covers what Siasconset's dominant indirect exposure actually means, with real examples from across the dataset.