Urban Ecosystems

, Volume 15, Issue 1, pp 247–266 | Cite as

Determinants of urban tree canopy in residential neighborhoods: Household characteristics, urban form, and the geophysical landscape

  • John H. LowryJr.Email author
  • Matthew E. Baker
  • R. Douglas Ramsey


The aesthetic, economic, and environmental benefits of urban trees are well recognized. Previous research has focused on understanding how a variety of social and environmental factors are related to urban vegetation. The aim is often to provide planners with information that will improve residential neighborhood design, or guide tree planting campaigns encouraging the cultivation of urban trees. In this paper we examine a broad range of factors we hypothesize are correlated to urban tree canopy heterogeneity in Salt Lake County, Utah. We use a multi-model inference approach to evaluate the relative contribution of these factors to observed heterogeneity in urban tree canopy cover, and discuss the implications of our analysis. An important contribution of this work is an explicit attempt to account for the confounding effect of neighborhood age in understanding the relationship between human and environmental factors, and urban tree canopy. We use regression analysis with interaction terms to assess the effects of 15 human and environmental variables on tree canopy abundance while holding neighborhood age constant. We demonstrate that neighborhood age is an influential covariate that affects how the human and environmental factors relate to the abundance of neighborhood tree canopy. For example, we demonstrate that in new neighborhoods a positive relationship exists between street density and residential tree canopy, but the relationship diminishes as the neighborhood ages. We conclude that to better understand the determinants of urban tree canopy in residential areas it is important to consider both human and environmental factors while accounting for neighborhood age.


Urban vegetation Urban ecology Urban tree canopy Geographic information systems Interaction effects Multi-model inference 



This research was funded by the Intermountain Digital Image Archive Center, Utah State University under grant from NASA (NNX06AF56G). We gratefully acknowledge the helpful critique of earlier drafts of this manuscript by two anonymous reviewers.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • John H. LowryJr.
    • 1
    Email author
  • Matthew E. Baker
    • 2
  • R. Douglas Ramsey
    • 3
  1. 1.School of Geography, Earth Science & Environment, Faculty of Science, Technology & EnvironmentUniversity of the South PacificSuvaFiji Islands
  2. 2.Department of Geography & Environmental SystemsUniversity of Maryland Baltimore CampusBaltimoreUSA
  3. 3.Department of Wildland ResourcesUtah State UniversityLoganUSA

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