Piney Point, MD
How exposed is Piney Point to wildfire?
USFS's Wildfire Risk to Communities model puts Piney Point at the 58th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 606 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Piney Point at the 58th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Piney Point's building exposure, zone by zone
Of Piney Point's 606 counted buildings, 45.5% carry Direct exposure and only 23.9% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How Piney Point compares
Within Maryland, Piney Point ranks higher (83rd percentile) than it does nationally (58th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Piney Point ranks 13,111 for wildfire risk (1 is highest) and 15,748 by building count (1 is largest). Within Maryland alone, it ranks 89 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Shopping for coverage in Piney Point
At the 58th national percentile, Piney Point 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
With 45.5% of Piney Point in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Piney Point's figures come from
The methodology guide shows exactly how USFS turned 606 counted buildings into the percentiles shown above for Piney Point. The exposure-zones guide covers what Piney Point's dominant direct exposure actually means, with real examples from across the dataset.