Landscape Patterns of Exurban Growth in the USA from 1980 to 2020
David M Theobald, Colorado State University
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In the United States, citizens, policy makers, and natural resource managers alike have become concerned about urban sprawl, both locally and nationally. Most assessments of sprawl, or undesired growth patterns, have focused on quantifying land-use changes in urban and metropolitan areas. It is critical for ecologists to examine and improve understanding of land-use changes beyond the urban fringe—also called exurban sprawl—because of the extensive and widespread changes that are occurring, and which often are located adjacent to or nearby “protected” lands.
The primary goal of this paper is to describe the development of a nationwide, fine-grained database of historical, current, and forecasted housing density, which enables these changes to be quantified as a foundation for inference of possible ecological effects. Forecasted patterns were generated by the Spatially Explicit Regional Growth Model, which relates historical growth patterns with accessibility to urban and protected lands. Secondary goals are to report briefly on the status and trend of exurban land-use changes across the U.S., and to introduce a landscape sprawl metric that captures patterns of land-use change. In 2000, there were 125 729 km2
in urban and suburban (<0.68 ha per unit) residential housing density nationwide (coterminous USA), but there were slightly over seven times that (917 090 km2
) in exurban housing density (0.68–16.18 ha per unit). The developed footprint has grown from 10.1% to 13.3% (1980 to 2000), roughly at a rate of 1.60% per year. This rate of land development outpaced the population growth rate (1.18% per year) by 25%. Based on model forecasts, urban and suburban housing densities will expand to 2.2% by 2020, whereas exurban development will expand to 14.3%.
cross-scale edge; exurban sprawl; forecast model; landscape sprawl metric; land-use change; resilience
Copyright © 2005 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.