01701410

Component

https://doi.org/10.1177/0361198119837194

This paper investigates the usefulness of 3D volumetric pixels (voxels) and the 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 of America (U.S.) 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 is 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 become prevalent that 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.

19-02267

English

pp 125-135

2019-4

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

Figures (5) ; Photos; References (41) ; Tables (3)

Aerial surveying; Geographic information systems; Laser radar; Mapping; Measurement; Streetscape; Trees

Data and Information Technology; Highways; Planning and Forecasting

TRIS, TRB, ATRI

Feb 25 2019 11:07AM