South Greensburg, PA
South Greensburg, PA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts South Greensburg at the 29th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 1,149 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts South Greensburg at the 31st percentile, close to its 29th-percentile risk score.
South Greensburg's building exposure, zone by zone
1,149 buildings are counted in South Greensburg, and 93.7% of them are Indirect exposure — ember-driven risk rather than the 5.6% in Direct exposure or the 0.8% rated Minimal.
How South Greensburg compares
South Greensburg scores 29th nationally and 36th within Pennsylvania — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, South Greensburg ranks 22,392 for wildfire risk (1 is highest) and 10,969 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,274 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in South Greensburg
At the 29th national percentile, South Greensburg rates moderate 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
With ember exposure the dominant pattern in South Greensburg (93.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where South Greensburg's figures come from
South Greensburg's 29th-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 South Greensburg's dominant indirect exposure actually means, with real examples from across the dataset.