Case Study:

Envision Utah

Methodology

Overall Technical Approach

The various planning models applied in the Envision Utah analysis, and their logical interconnections, are illustrated in Figure 3.

Figure 3. Interconnection of Planning Models

Source: Based on Utah Governor's Office of Planning and Budget (1999).

The land use analysis served as the foundation for the remaining planning models, including transportation, air quality, water supply/demand, and infrastructure cost assessment. The land use analysis allocated regional population and employment to a grid of 50.3-meter-square cells, consistent with different development characteristics and constraints under each scenario. The household and employment data, along with a walk/bike mode split obtained from the calculation of an Urban Index for each cell, were aggregated to Traffic Analysis Zones (TAZs) for transportation and air quality analysis. Land consumption and agricultural conversion also informed both the land use and water use models.

Feedback between transportation and land use was not explicitly modeled, although the scenarios did include different transportation and land use scenarios in combination that were designed to be complementary. The Envision Utah project is currently working to develop and apply UrbanSim, a land use model that interacts with transportation models, to the Greater Wasatch area.

Two rounds of technical analysis were conducted: one for the analysis of the baseline and three alternative scenarios, and one for the comparison of the baseline and Quality Growth scenarios. The methods used were largely similar, but in some cases were refined for the Quality Growth analysis. Relevant differences in technical approaches are noted below.

Envision Utah also commissioned a housing demand study to ensure that the Quality Growth Strategy's housing mix is consistent with the demands of the housing market. The study examined current development trends, constraints on the real estate market such as zoning regulations, and how changes in consumer preferences and regional demographics will affect housing demand in 2020.

The land use analysis, GIS application, air quality model, and infrastructure cost analysis are the primary focus of this case study. The transportation modeling approach, water supply/demand analysis, and housing demand analysis are described more briefly. The scenarios are described to provide background and context.

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