LIDAR Accuracy on Asphalt Road - PowerPoint PPT Presentation

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LIDAR Accuracy on Asphalt Road

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LIDAR Accuracy on Asphalt Road
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LIDAR Accuracy on Asphalt Road

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  1. LIDAR Accuracy on Asphalt Road Arttu Soininen Terrasolid Ltd

  2. Case story • Task: • produce an accurate asphalt road surface model • Purpose: • asphalt is going to be resurfaced • machinery is going to be automatically guided by total station positioning • Note: • we assume that total station network is perfect • 481 total station points on asphalt for control • surrounding terrain is not important

  3. Coordinate setup • TerraScan uses integer coordinate system • Sentimeter steps OK for general terrain mapping • Use millimeter or 1/10 of a millimeter for best accuracy work

  4. Laser scanning • 15 km of road • TopEye measured in October 2003 with a scanner measuring about 7000 points per second • Digital camera images with 2 cm resolution • Flown in two directions at 100 m altitude

  5. Initial laser data accuracy • IMU / scanner misalignment angles carefully calibrated from data set • TerraMatch gives no real HRP improvement • Average difference between surfaces from different flightlines 3.689 cm • Average difference on asphalt 3.440 cm

  6. Dz correction for whole flightlines • TerraMatch gave dz corrections for whole flightlines: • -1.7 cm line 1 • +0.7 cm line 2 • +0.8 cm line 3 • +0.4 cm line 4 • -0.2 cm line 5 • Average difference between surfaces from different flightlines after correction 3.299 cm, on asphalt 2.997 cm

  7. Fluctuating elevation correction • Corrects for inaccuracy of trajectory elevations • TerraMatch computed elevation difference of each flightline to others at 1 second intervals • Each 1 second interval was corrected with the average of 3 consecutive seconds • Correction limited to max 2 cm • Average difference between surfaces from different flightlines 3.070 cm

  8. Find Fluctuations • Correction will modify laser points of each interval with a unique dz correction • User can select: • how correction curve is averaged from consecutive intervals • what is the maximum correction to apply

  9. Find Fluctuations - Before

  10. Find Fluctuations - After

  11. Cutting edges of scan lines • TerraScan cut edges of scan lines where accuracy is not as good as at the center of scan lines

  12. Geoid correction • Transform from GRS80 ellipsoid to orthometric height • Average elevation difference between LIDAR surface and total station points was computed for each 1 km interval

  13. Smoothing of laser surface • Classify points within 10 cm from ground to ground • Smoothen laser surface • Std dev asphalt against total station points 2.32 cm

  14. Smoothing 10 cm spread • Improves accuracy on hard surfaces • Requires interactive work -- draw polygons • Raises laser data on hard surfaces: • systematic biases on different surfaces closer • Example before: • laser data 5 cm too high on asphalt • laser data 9 cm too high in terrain • Example after: • laser data 7 cm too high on asphalt • laser data 9 cm too high in terrain

  15. Breaklines on asphalt • 2D breaklines drawn on orthophoto were draped to laser point surface • smoothenes variations in longitudinal direction • Std dev of resulting TIN model: • fix points 2.02 cm, min -5.60, max +5.30

  16. Summary of steps • Match laser strips internally: • HRP misalignment  3.440 cm • Dz per flightline  2.997 cm • Elevation fluctuations  2.705 cm • Cut overlap • Classify ground • Geoid correction based on local points  2.48 cm • Classify 10 cm spread and smoothen  2.32 cm • Drape breaklines on laser surface • Model breaklines + surrounding terrain  2.02 cm