The Unresolved Relationship between Street Trees and Road Safety
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The Unresolved Relationship between Street Trees and Road Safety

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      The roadside area where fixed-object hazards are explicitly minimized is called the clear zone, which became standard design practice soon after the 1966 Congressional hearings on road and automobile safety. Mounting evidence, however, is beginning to cast doubt on what we think we know about the impact of roadside clear zones on actual safety outcomes. This is particularly an issue with street trees in urban contexts, which are known to provide economic, environmental, and livability benefits, but are also widely considered a road safety detriment. Part 1 relies on advances in remote sensing to map both tree canopy and street-tree locations in geographic information services (GIS) for the entirety of the city and county of Denver, Colorado. The authors then statistically test the association between street trees and seven years of road safety outcomes while controlling for factors known to be associated with crash outcomes. Despite 50 years as standard design practice, the results suggest that the expected safety benefit of roadside clear zones – at least with respect to street trees in an urban context – may be overstated. In fact, larger tree canopies that extend over the street are associated with fewer injury/fatal crashes, as well as fewer crashes overall while holding all other variables constant. The number of street trees per mile associates with improved safety in wealthier neighborhoods, but it can be detrimental in low-income neighborhoods. This inconsistency represents an equity issue in need of future research. When assessing the safety impact of street trees in the clear zone, municipalities and transportation agencies need to be more cognizant of context and the potential influence of street design changes to road user behaviors, particularly related to issues that more directly affect safety, such as travel speeds and driver awareness. Part 2 investigates the usefulness of 3D volumetric pixels (voxels) and United States Geological Survey (USGS) Quality Level 2 (QL2) Light Detection and Ranging (LiDAR) data to measure features in streetscapes. As the USGS embarks on a national LiDAR database with the goal of covering the entire United States with QL2 data or better, this paper investigates uses of QL2 LiDAR for the 3D measuring of streetscapes. Tree mapping is a common use of QL2 LiDAR data, and street trees are among the most common features within urban streetscapes that transportation and urban designers assess. Traditional remote sensing techniques derive tree polygons from imagery; and traditional uses of LiDAR for tree canopy mapping are based on deriving a 2D canopy polygon with an attribute for elevation height. However, when breaking up streetscapes into 5-ft elevation zones and calculating street-tree voxels at each elevation zone height, 3D characteristics of street trees that become prevalent completely differ from the common 2D LiDAR derived street trees. Statistical tests in this paper display how different the 3D characteristics are from the 2D-derived LiDAR polygons, as this paper introduces a new methodology for measuring streetscape features in 3D, particularly street trees. The appendices include examples of how these issues were integrated into assignments for graduate level civil engineering classes, as well as the output from a foundational master’s report.
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