Stanford, IN
How exposed is Stanford to wildfire?
USFS scores Stanford at the 22nd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 242 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Stanford at the 23rd percentile, close to its 22nd-percentile risk score.
Stanford's building exposure, zone by zone
100% of Stanford's 242 buildings sit in USFS's Direct exposure zone, roughly 242 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.
How Stanford compares
Within Indiana, Stanford ranks higher (86th percentile) than it does nationally (22nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Stanford ranks 24,547 for wildfire risk (1 is highest) and 23,386 by building count (1 is largest). Within Indiana alone, it ranks 135 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Shopping for coverage in Stanford
Stanford's moderate wildfire rating (22nd 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.
What would actually reduce this score
With 100% of Stanford 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 Stanford's figures come from
Stanford's 22nd-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 Stanford's dominant direct exposure actually means, with real examples from across the dataset.