Sudlersville, MD
How exposed is Sudlersville to wildfire?
Sudlersville sits at the 23rd 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 279 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sudlersville's burn probability — fire likelihood with no building count factored in — sits at the 23rd percentile nationally.
Where Sudlersville's buildings actually sit
USFS puts 68.1% of Sudlersville's 279 buildings in the Indirect exposure zone, versus 30.5% Direct and 1.4% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Sudlersville compares
There's little gap between Sudlersville's 23rd national percentile and its 33rd percentile inside Maryland, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sudlersville ranks 24,175 for wildfire risk (1 is highest) and 22,219 by building count (1 is largest). Within Maryland alone, it ranks 353 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Sudlersville and the insurance market
At the 23rd national percentile, Sudlersville rates moderate 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 ember exposure the dominant pattern in Sudlersville (68.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Sudlersville's figures come from
Every one of the two percentiles behind Sudlersville's 24,175-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Sudlersville's dominant indirect exposure actually means, with real examples from across the dataset.