Spatial Analysis of Urbanization in the Salt Lake Valley: An Urban Ecosystem Perspective

Utah State University, Doctoral Dissertation, May 2010

John H. Lowry Jr.

“Because urban areas comprise a variety of biotic (e.g. people, trees) and abiotic (e.g. streets, water) components that interact and are often interdependent upon one another, it is helpful to study urban areas as urban ecosystems.

“Our goal in Chapter 2 is to measure and quantify the spatial and demographic structure of the urbanized portion of Salt Lake County, Utah. We use 18 metrics from four broad categories (density, centrality, accessibility, and neighborhood mix) to measure urban form for three age-based residential neighborhood types. Using analysis of variance (ANOVA) we test for differences in mean values for the 18 urban form metrics. We find measureable differences in the spatial and demographic characteristics of these neighborhoods, suggesting that the rate of urban sprawl in Salt Lake County has been holding steady, if not increasing, during the last 20 years.

“Chapter 3 seeks to better understand how spatial heterogeneity in urban tree canopy is related to household characteristics, urban form, and the geophysical landscape of residential neighborhoods. We consider neighborhood age a factor that moderates the relationship between these determinants of tree canopy, and the abundance of tree canopy observed. Using linear regression analysis with neighborhood age as interaction term, we assess the relationship between tree canopy and 15 determinants of tree canopy abundance at three neighborhood ages. We find that neighborhood age has a significant moderating effect on the relationship between several determinants of canopy cover and the abundance of canopy cover observed.

“While the urban forest provides many benefits to human well-being, it also consumes considerable quantities of water. An important question in Chapter 4 is to determine whether a growing urban forest increases overall residential irrigation demand, decreases demand, or has no apparent effect. Using a water demand model borrowed from agronomy, we estimate irrigation water demand based on the area of three residential landscape types and climatic factors. We project future residential water demand by generating residential landscape scenarios based on predicted urban forest canopy growth. We find that urban forest growth has the effect of stabilizing or potentially decreasing overall residential irrigation water demand.”