North Philipsburg, PA
How exposed is North Philipsburg to wildfire?
North Philipsburg's 365 buildings earn a 50th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts North Philipsburg at the 49th percentile, close to its 50th-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in North Philipsburg (63% of 365 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 37% sit in the Direct zone.
How North Philipsburg compares
North Philipsburg's 81st-percentile standing inside Pennsylvania outpaces its 50th 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, North Philipsburg ranks 15,930 for wildfire risk (1 is highest) and 19,969 by building count (1 is largest). Within Pennsylvania alone, it ranks 383 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in North Philipsburg
At the 50th national percentile, North Philipsburg rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Because 63% of North Philipsburg'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 North Philipsburg's figures come from
North Philipsburg's 50th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what North Philipsburg's dominant indirect exposure actually means, with real examples from across the dataset.