Lead, SD
Lead, SD's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Lead lands at the 82nd percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 1,688 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Lead at the 80th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Lead's buildings actually sit
USFS puts 81% of Lead's 1,688 buildings in the Indirect exposure zone, versus 19% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Where Lead ranks
There's little gap between Lead's 82nd national percentile and its 82nd percentile inside South Dakota, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Lead ranks 5,778 for wildfire risk (1 is highest) and 8,464 by building count (1 is largest). Within South Dakota alone, it ranks 82 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
Lead and the insurance market
Lead's 82nd-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Lead
With ember exposure the dominant pattern in Lead (81% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Lead's figures come from
Every one of the two percentiles behind Lead's 5,778-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Lead's dominant indirect exposure actually means, with real examples from across the dataset.