Midland, NC
Midland wildfire risk explained
Out of every US place USFS scores, Midland lands at the 45th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 2,390 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Midland at the 47th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Midland's buildings actually sit
Direct exposure dominates in Midland: 76.2% of its 2,390 buildings, versus 23.8% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Midland against the rest of the country
Midland ranks lower within North Carolina (25th percentile statewide) than its 45th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Midland ranks 17,339 for wildfire risk (1 is highest) and 6,531 by building count (1 is largest). Within North Carolina alone, it ranks 577 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Shopping for coverage in Midland
Midland's elevated rating (45th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Midland
With 76.2% of Midland 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 Midland's figures come from
Every one of the two percentiles behind Midland's 17,339-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Midland's dominant direct exposure actually means, with real examples from across the dataset.