Cite as:
Westervelt J, BenDor T, Sexton J, 2011, "A technique for rapidly forecasting regional urban growth" Environment and Planning B: Planning and Design 38(1) 61 – 81
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A technique for rapidly forecasting regional urban growth

James Westervelt, Todd BenDor, Joseph Sexton

Received 8 March 2009; in revised form 24 January 2010

Abstract. Recent technological and theoretical advances have helped produce a wide variety of computer models for simulating future urban land-use change. However, implementing these models is often cost prohibitive due to intensive data-collection requirements and complex technical implementation. There is a growing need for a rapid, inexpensive method to project regional urban growth for the purposes of assessing environmental impacts and implementing long-term growth-management plans. We present the Regional Urban Growth (RUG) model, an extensible mechanism for assessing the relative attractiveness of a given location for urban growth within a region. This model estimates development attraction for every location in a rasterized landscape on the basis of proximity to development attractors, such as existing dense development, roads, highways, and natural amenities. RUG can be rapidly installed, parameterized, calibrated, and run on almost any several-county region within the USA. We implement the RUG model for a twelve-county region surrounding the Jordan Lake Reservoir, an impoundment of the Haw River Watershed (North Carolina, USA). This reservoir is experiencing major water-quality problems due to increased runoff from rapid urban growth. We demonstrate the RUG model by testing three scenarios that assume (1) ‘business-as-usual’ growth levels, (2) enforcement of state-mandated riparian buffer regulations, and (3) riparian buffer regulations augmented with forecast conservation measures. Our findings suggest that the RUG model can be useful not only for environmental assessments, stakeholder engagement, and regional planning purposes, but also for studying specific state and regional policy interventions on the direction and location of future growth pressure.

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