Combining Mobile LiDAR and Photogrammetric Remote Sensing for Assets Data Collection in Colorado Roadways
Combining Mobile LiDAR and Photogrammetric Remote Sensing for Assets Data Collection in Colorado Roadways By Roberto A. Avila, Ph.D.1, Dennis R. Sandin, RPP2, Robert S. Dzur, MA2, Roger D. Nelson, PLS, CFedS2 1 Colorado Department of Transportation, 2829 W. Howard Pl., Denver, CO 80204 2 Bohannan Huston Incorporated, 7500 Jefferson St NE, Albuquerque, NM 87109 Date: July 16, 2018 The Colorado Department of Transportation (CDOT) is adapting from 2D to 3D workflows for asset data collection and maintenance options that include remotely-sensed mapping technologies aerial systems aircrafts or drones (Unmanned Aerial Vehicle (UAV) and mobile systems roadside vehicles. This pilot project aims to learn, assess, and evaluate asset data collection and maintenance from remotely sensed methods. Mobile Laser Scanner (MLS) like Light Detection and Ranging (LiDAR) and photogrammetric data was acquired in July 2018 over a stretch of Interstate 70 (I70). The mapping area runs from the Denver Metro Area to 25 miles going west of the Interstate. This stretch of highway has various asset structures on the ground to be mapped that include among other things pavement marking, wall, guardrail, striping, fences, signs, light post, and overhead structures ?vertical clearance like bridges, signage, and power lines. While MLS and photogrammetric source datasets collect vast quantities of point cloud data from which to extract these features, image-based remote sensing techniques offer significant opportunities for roadway asset inventory. Feature data extraction techniques rely on 2D image processing methodologies combined with 3D point cloud surface modeling approaches. These techniques aim to streamline data handling and processing, enhance feature interpretation, and improve overall data quality and reliability. The project is also testing a variety of geodetic control configurations to assess cost savings measures as well as their potential impacts to data quality and accuracy. It is expected mobile and airborne derived by-products will support CDOT asset work among the different disciplines. This work also looks at promoting honed skills among CDOT staff, identify scientific methods, workflow processes, cost analysis, and provide useful information for the consolidation of future assets data collection and maintenance. We believe the option to use LiDAR along with photogrammetric remote sensing data can be a viable alternative to achieve operational asset management needs used and consumed for various business applications within CDOT.