Parkside, PA
Parkside, PA's wildfire risk, in USFS's own numbers
USFS scores Parkside at the 18th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 655 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Parkside at the 19th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Parkside's building exposure, zone by zone
Only 0.5% of Parkside's 655 buildings carry Direct exposure and 0% carry Indirect; the remaining 99.5% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Parkside against the rest of the country
Parkside's risk sits at a similar level relative to Pennsylvania (19th percentile statewide) as it does nationally (18th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Parkside ranks 25,980 for wildfire risk (1 is highest) and 15,139 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,623 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Parkside and the insurance market
At the 18th national percentile, Parkside rates low 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
Parkside's 99.5% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Parkside's figures come from
Parkside's 18th-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 Parkside's dominant minimal exposure actually means, with real examples from across the dataset.