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Survey Grade LiDAR Technologies for Transportation Engineering

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This presentation was given during the 2013 Annual Civil Engineering Conference by Tim Stagg of AeroMetric. It covers system/sensor configurations, application advantages/disadvantages, analysis from sensor data, feature extraction/deliverables, and client pains in relation to survey grade LiDAR technologies for transportation engineering.

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Survey Grade LiDAR Technologies for Transportation Engineering

  1. 1. WELCOME TO THE ASCE 143RD ANNUAL CIVIL ENGINEERING CONFERENCE Survey Grade LiDAR Technologies for Transportation Engineering
  2. 2. Overview • • • • • • System / Sensor Configurations Application Advantages/Disadvantages Analysis from Sensor Data Feature Extraction / Deliverables Client Pains Questions
  3. 3. System/Sensor Configurations • Mobile Systems • Helicopter Systems
  4. 4. Mobile System Mounting Can be mounted on most platforms easily •SUV •Truck •Rail Car •ATV •Boat Only requires 12 volt power – marine battery- lasts about 7 to 10 hours with out charge.
  5. 5. Mobile Sensor Configuration GPS and Inertial Sensors LiDAR Sensor DMI Calibrated Digital Cameras
  6. 6. Mobile Mapper System Configurations Minimize laser shadowing-optimize field of view (FOV) • Sensor will see everything behind the vehicle • Sensor will see ~45° in front of vehicle • Full 360° area coverage
  7. 7. HAMS LiDAR High Accuracy Mapping System Helicopter or Fixed Wing Trimble AP50 Inertial POS system Equivalent 610 IMU Phase One IXI 80mp Camera – 55mm lens 800 feet – 1in pixel Reigl 480i LiDAR Sensor – 550khz 800 feet – Approx. 32ppm single pass Accuracy – 1 to 2 cm vertically
  8. 8. System Advantages/ Disadvantages
  9. 9. System accuracies and expected point resolutions • Fixed Wing – Can achieve 5 to 9.25cm vertical 1 to 80 points per meter • Helicopter – 1 to 3 cm vertical accuracy – 40 to 150 points per meter • Mobile – 1 cm or better depending on control – 1000 to 4000 points per meter
  10. 10. Mobile System Considerations • GPS receivers are set approximately 16 to 20 miles apart (no more than 8 to 10 miles from receiver to MMS unit) • End data will only be as accurate as the control targets established • For high accuracy vertical projects, digital levels must be established on the targets • Target spacing should average 800’ between point pairs • Targets must be placed within sensor view, i.e. “Roadway”
  11. 11. HAM System Considerations • Target spacing should average 1500’ between point pairs • Targets can be placed anywhere within project corridor
  12. 12. Application Advantages/Disadvantages • • • • • Multiple Mission Capability Rich datasets Survey coverage limits Accuracies Future data usage
  13. 13. Mobile LiDAR Advantages Over Conventional Survey
  14. 14. Advantage of Helicopter for Shadowed Vertical Features
  15. 15. Advantage of Mobile for Vertical Features
  16. 16. HAM Imagery
  17. 17. Mobile Mapping Imagery
  18. 18. Multiple Data Sources • A high resolution, geo-coded digital imagery is collected with every survey • Use LiDAR and digital photography together to generate true color point clouds automatically from scan data
  19. 19. Analysis from Sensor Data
  20. 20. Bridge Decking Analysis
  21. 21. Pot Hole Detection Cross Section 11” x 21” Pot Hole 2.1 Inches Deep I-55, Hinds County, Mississippi
  22. 22. Pavement Joint Failures Joint Failure I-95, Brevard County, Florida
  23. 23. Clearance Analysis Vertical Clearance 17.56-Feet Vertical Clearance 22.60-Feet Vertical Clearance 22.43-Feet
  24. 24. Slope Analysis Point to Point Slope (Water Flow) • • • • Red – Less than 1% Slope Yellow – 1 - 2% Slope Green – 2 - 4% Slope Cyan – 4 - 20% Slope
  25. 25. Slope Analysis Steel Plate Pavement Ruts
  26. 26. Slope Analysis
  27. 27. Classification of LiDAR Point Cloud
  28. 28. Elevation by Intensity Color
  29. 29. Feature Extraction
  30. 30. Traditional Vector Mapping
  31. 31. Asset Mapping
  32. 32. Points and Line Work
  33. 33. 3D modeling of Bridges
  34. 34. Point Cloud Rendering/Modeling
  35. 35. Feature Collection – Rail Road Corridor
  36. 36. Processed Intensity Image
  37. 37. Intensity Image fused with RGB Values
  38. 38. Point Cloud data fused with RGB Values
  39. 39. Client Pains • • • • Large File Sizes Rich Data Sets Difficulty with work Flow Issues Software always lags behind Hardware
  40. 40. Software Solutions • Dashboards for analysis in 3D environment • Point Cloud Software for transportation data • Asset Management Software
  41. 41. THANK YOU FOR ATTENDING THE ASCE 143RD ANNUAL CIVIL ENGINEERING CONFERENCE WE LOOK FORWARD TO SEEING YOU NEXT YEAR IN PANAMA! Tim Stagg - AeroMetric Vice President, Transportation Solutions Phone: (410) 310-9534 Email: tstagg@aerometric.com

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