Coalmont, PA
How exposed is Coalmont to wildfire?
USFS's Wildfire Risk to Communities model puts Coalmont at the 53rd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 67 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Coalmont's burn probability — fire likelihood with no building count factored in — sits at the 51st percentile nationally.
What "at risk" means for the buildings here
USFS classifies 100% of Coalmont's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 67 structures sit close enough to vegetation that lot clearing matters most.
Coalmont against the rest of the country
Coalmont's 88th-percentile standing inside Pennsylvania outpaces its 53rd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Coalmont ranks 14,729 for wildfire risk (1 is highest) and 30,395 by building count (1 is largest). Within Pennsylvania alone, it ranks 236 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Coalmont
At the 53rd national percentile, Coalmont rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Coalmont's 100% 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 Coalmont's figures come from
Every one of the two percentiles behind Coalmont's 14,729-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Coalmont's dominant direct exposure actually means, with real examples from across the dataset.