A LiDAR-Based Approach to Quantitatively Assessing Streetscapes

This project investigates objective methods to extract streetscape features with two 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. The first part tests the use of United States Geological Survey (USGS) Quality Level 1 (QL1) LiDAR data to measure street trees. In addition to street trees and buildings, which were detectable with lower-quality QL2 LiDAR data, an analyst can also legitimately extract and statistically quantify walls, fences, landscape vegetation, light posts, traffic lights, power poles, power lines, street signs, and miscellaneous street furniture. The second part investigates high-density mobile LiDAR dataset. This facilitated the ability to compartmentalize streetscapes into smaller voxels and, in turn, to measure and quantify signage, signals, light/lampposts, street furniture, building window proportions, awnings, and enclosed courtyard restaurants. The results suggest that mobile LiDAR could supplement or replace conventional audit-based streetscape measuring that urban planners currently use to measure streetscapes. The output of such data collection efforts could help improve transportation studies that consider outcomes such as walkability or safety.

  • Record URL:
  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    University of Colorado, Denver

    Department of Civil Engineering
    1200 Larimer Street, P.O. Box 173364
    Denver, CO  United States  80217-3364

    Mountain-Plains Consortium

    North Dakota State University
    Fargo, ND  United States  58108

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Authors:
    • Golombek, Yaneev
    • Marshall, Wesley E
    • Janson, Bruce
  • Publication Date: 2021-3

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; Photos; References; Tables;
  • Pagination: 63p

Subject/Index Terms

Filing Info

  • Accession Number: 01771693
  • Record Type: Publication
  • Report/Paper Numbers: MPC-615, MPC 21-430
  • Files: UTC, TRIS, ATRI, USDOT
  • Created Date: May 5 2021 12:57PM