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Title:A LiDAR-Based Approach to Quantitatively Assessing Streetscapes
Authors:Yaneev Golombek, Wesley E. Marshall, and Bruce Janson
University:University of Colorado Denver
Publication Date:Mar 2021
Report #:MPC-21-430
Project #:MPC-615
TRID #:01771693
Keywords:built environment, data analysis, data collection, laser radar, streetscape, trees
Type:Research Report – MPC Publications


Over a century of research suggests that the size and spatial location of various streetscape features impacts outcomes such as walkability, livability, and road safety. Current streetscape feature measuring/mapping techniques are limited to subjective audit-based methods, crude feature counts, or simple 2D geographic information system (GIS) processing of roadside features. This project investigates objective methods to extract streetscape features with three different classes of light detection and ranging (LiDAR) processed with 3D volumetric pixels (voxels). Furthermore, this work introduces new methods for creating comprehensive streetscape descriptive statistics from LiDAR data and processed voxel data.

How to Cite

Golombek, Yaneev, Wesley E. Marshall, and Bruce Janson. A LiDAR-Based Approach to Quantitatively Assessing Streetscapes, MPC-21-430. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2021.

NDSU Dept 2880P.O. Box 6050Fargo, ND 58108-6050