The wildland–urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. The WUI is thus a focal area for human– environment conflicts, such as the destruction of homes by wildfires, habitat fragmentation, introduction of exotic species, and biodiversity decline. Our goal was to conduct a spatially detailed assessment of the WUI across the United States to provide a framework for scientific inquiries into housing growth effects on the environment and to inform both national policymakers and local land managers about the WUI and associated issues. The WUI in the conterminous United States covers 719 156 km2 (9% of land area) and contains 44.8 million housing units (39% of all houses). WUI areas are particularly widespread in the eastern United States, reaching a maximum of 72% of land area in Connecticut. California has the highest number of WUI housing units (5.1 million). The extent of the WUI highlights the need for ecological principles in land‐use planning as well as sprawl‐limiting policies to adequately address both wildfire threats and conservation problems.

The US Census provides the primary source of spatially explicit social data, but changing block boundaries complicate analyses of housing growth over time. We compared procedures for reconciling housing density data between 1990 and 2000 census block boundaries in order to assess the sensitivity of analytical methods to estimates of housing growth in Oregon. Estimates of housing growth varied substantially and were sensitive to the method of interpolation. With no processing and areal-weighted interpolation, more than 35% of the landscape changed; 75-80% of this change was due to decline in housing density. This decline was implausible, however, because housing structures generally persist over time. Based on aggregated boundaries, 11% of the landscape changed, but only 4% experienced a decline in housing density. Nevertheless, the housing density change map was almost twice as coarse spatially as the 2000 housing density data. We also applied a dasymetric approach to redistribute 1990 housing data into 2000 census boundaries under the assumption that the distribution of housing in 2000 reflected the same distribution as in 1990. The dasymetric approach resulted in conservative change estimates at a fine resolution. All methods involved some type of trade-off (e.g. analytical difficulty, data resolution, magnitude or bias in direction of change). However, our dasymetric procedure is a novel approach for assessing housing growth over changing census boundaries that may be particularly useful because it accounts for the uniquely persistent nature of housing over time.