Calverton, MD
Calverton, MD's wildfire risk, in USFS's own numbers
Calverton sits at the 21st percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 3,336 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Calverton's burn probability — fire likelihood with no building count factored in — sits at the 21st percentile nationally.
What "at risk" means for the buildings here
USFS classifies 81.5% of Calverton's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 18.5% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Calverton ranks
Calverton's risk sits at a similar level relative to Maryland (27th percentile statewide) as it does nationally (21st) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Calverton ranks 24,961 for wildfire risk (1 is highest) and 4,997 by building count (1 is largest). Within Maryland alone, it ranks 383 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Shopping for coverage in Calverton
Calverton's moderate wildfire rating (21st percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With 81.5% of buildings rated Minimal exposure, Calverton gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Calverton's figures come from
Calverton's 21st-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 Calverton's dominant minimal exposure actually means, with real examples from across the dataset.