Galva, IL
Galva wildfire risk explained
Galva sits at the 1st percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 1,634 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Galva at the 1st national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Galva's building exposure, zone by zone
USFS classifies 93.3% of Galva's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 6.7% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Galva against the rest of the country
There's little gap between Galva's 1st national percentile and its 11th percentile inside Illinois, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Galva ranks 31,099 for wildfire risk (1 is highest) and 8,634 by building count (1 is largest). Within Illinois alone, it ranks 1,287 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
Shopping for coverage in Galva
At the 1st national percentile, Galva rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Galva
Even with 93.3% of Galva outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Galva's figures come from
The methodology guide shows exactly how USFS turned 1,634 counted buildings into the percentiles shown above for Galva. The exposure-zones guide covers what Galva's dominant minimal exposure actually means, with real examples from across the dataset.