How do you reconstruct an accident using USGS LiDAR? 

Kineticorp Photogrammetry Expert, Toby Terpstra, discusses our latest research “Reconstruction of 3D Accident Sites Using USGS Lidar, Aerial Images, and Photogrammetry.” Toby presented the findings at SAE International’s 2019 World Congress Event (WCX).  A special thanks to Jordan Dickinson,  and Alireza Hashemian for their involvement with the project.

Publication Introduction:

The accident reconstruction community has previously relied upon photographs and site visits to recreate a scene. This method is difficult in instances where the site has changed or is not accessible. In 2017 the United States Geological Survey (USGS) released historical 3D point clouds (LiDAR) allowing for access to digital 3D data without visiting the site. This offers many unique benefits to the reconstruction community including: safety, budget, time, and historical preservation. This paper presents a methodology for collecting this data and using it in conjunction with aerial imagery, and camera matching photogrammetry to create 3D computer models of the scene without a site visit. To determine accuracies achievable using this method, evidence locations solved for using only USGS LiDAR, aerial images and scene photographs (representative of emergency personnel photographs) were compared with known locations documented using total station survey equipment and ground-based 3D laser scanning. The data collected from three different site locations were analyzed, and camera matching photogrammetry was performed independently by 5 different individuals to locate evidence. On average, the resulting evidence for all three test sites was found to be within 3.0 inches (8cm) of known evidence locations with a standard deviation of 1.7 inches (4cm). To further evaluate the quality of the USGS LiDAR, a comparative point cloud analysis of the roadway surfaces was performed. On average, 85% of the USGS LiDAR points were found to be within .5 inches of the ground-based 3D scanning points. ….. Purchase Full Publication

Full Publication:

SAE 2019-01-1005 – Nighttime Visibility in Varying Moonlight Conditions

Authors: 

Toby Terpstra, Jordan DickinsonAlireza Hashemian

Related Case Studies, Content & Research:

SAE 2019-01-0427 – An Optimization of Small Unmanned Aerial System (sUAS) Image Based Scanning Techniques for Mapping Accident Sites

SAE 2019-01-0424 – The Application of Augmented Reality to Reverse Camera Projection

Sports Biomechanics 2018 – Validation of a Videogrammetry Technique for Analysing American Football Helmet Kinematics

SAE 2017-01-1422 – An Evaluation of Two Methodologies for Lens Distortion Removal When EXIF Data is Unavailable

SAE 2016-01-1478 – Determining Position & Speed through Pixel Tracking and 2D Coordinate Transformation in 3D Environment 

SAE 2016-01-1475 – A Survey of Multi-View Photogrammetry Software for Documenting Vehicle Crush

SAE 2016-01-0415 – Nighttime Videographic Projection Mapping to Generate Photo-Realistic Simulation Environments 

SAE 2016-01-1467 – Evaluation of the Accuracy of Image Based Scanning as a Basis for Photogrammetric Reconstruction of...

SAE 2013-01-0788 – Video Projection Mapping Photogrammetry through Video Tracking

SAE 2011-01-0286 – Photogrammetric Measurement Error Associated with Lens Distortion

SAE 2010-01-0292 – Evaluation of Photometric Data Files for Use in Headlamp Light Distribution

SAE 2009-01-0110 – Simulating Headlamp Illumination Using Photometric Light Clusters

SAE 2006-01-0723 – Image Analysis of Rollover Crash Tests Using Photogrammetry

SAE 2004-01-1221 – A Video Tracking Photogrammetry Technique to Survey Roadways for Accident Reconstruction

SAE 2001-01-3313 – Determining Crash Data Using Camera Matching Photogrammetric Technique

I CRASH 2000 – Using Digital Photogrammetry to Determine Crash Severity

SAE 1999-01-0439 – Using Digital Photogrammetry to Determine Vehicle Crush and Equivalent Barrier Speed (EBS)

SAE 1997-970944 – Accident Scene Diagramming Using New Photogrammetric Technique

NAFE, REF:308S, Photogrammetric Accident Analysis – Forensic Engineering Comparison of Two & Three Dimensional Photogrammetric Accident Analysis

Back to Top