New Baltimore, PA
How exposed is New Baltimore to wildfire?
USFS scores New Baltimore at the 55th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 127 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, New Baltimore's burn probability — fire likelihood with no building count factored in — sits at the 54th percentile nationally.
What "at risk" means for the buildings here
USFS classifies 73.2% of New Baltimore's buildings as Direct exposure, higher than its 26.8% Indirect share and far above its 0% Minimal share — a profile where 93 structures sit close enough to vegetation that lot clearing matters most.
New Baltimore against the rest of the country
Compare New Baltimore's two percentiles: 91st within Pennsylvania, only 55th nationally — a gap of 36 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, New Baltimore ranks 14,166 for wildfire risk (1 is highest) and 27,868 by building count (1 is largest). Within Pennsylvania alone, it ranks 181 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
New Baltimore's elevated wildfire rating (55th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in New Baltimore
New Baltimore's 73.2% 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 New Baltimore's figures come from
The methodology guide shows exactly how USFS turned 127 counted buildings into the percentiles shown above for New Baltimore. The exposure-zones guide covers what New Baltimore's dominant direct exposure actually means, with real examples from across the dataset.