Merion Station, PA
How exposed is Merion Station to wildfire?
Merion Station's 1,994 buildings earn a 16th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Merion Station at the 17th percentile, close to its 16th-percentile risk score.
Where Merion Station's buildings actually sit
Merion Station rates 68.5% Minimal exposure against just 31.5% Direct and 0% Indirect — of 1,994 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Where Merion Station ranks
There's little gap between Merion Station's 16th national percentile and its 16th percentile inside Pennsylvania, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Merion Station ranks 26,451 for wildfire risk (1 is highest) and 7,495 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,669 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
Merion Station's low rating (16th 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
Even with 68.5% of Merion Station 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 Merion Station's figures come from
Every one of the two percentiles behind Merion Station's 26,451-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Merion Station's dominant minimal exposure actually means, with real examples from across the dataset.