Lidar 101: Intro to Lidar. Jason Stoker USGS EROS / SAIC

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1 Lidar 101: Intro to Lidar Jason Stoker USGS EROS / SAIC

2 Lidar Light Detection and Ranging Laser altimetry ALTM (Airborne laser terrain mapping) Airborne laser scanning

3 Lidar Laser IMU (INS) GPS Scanning Mirror On board computer

4 Laser Pulse laser Records distance to target Time * c / 2 Laser wavelengths can differ 1064 nm khz systems available today

5

6 Lidar Laser L A S E R L A S E R

7 IMU Inertial Measurement Unit Gyroscopes and accelerometer Roll Pitch Records roll, pitch, yaw of aircraft Yaw Courtesy of NASA

8 GPS Global positioning system Differentially corrected Provides cm accuracy of aircraft Allows cm accuracy of laser pulse

9 Scanning Lidar Courtesy of Dodson & Associates

10

11 Records data Photon detector (intensity) Laser timing IMU info GPS info Mirror scan angle Converts into XYZ Millions of points On-board display On-board Computer

12 X r X r G o r X G LIDAR Equation r r = X o + R φ, κ RΔ ω, Δφ, Δκ PG + Rω, φ, κ RΔ ω, Δφ, Δ 0 ρ ω, κ Rα, β 0 ground coordinates of object point under consideration ground coordinates of GPS antenna phase center P r G offset between laser unit and phase center w.r.t. the laser unit coordinate system R ω, φ, κ rotation matrix that needs to be applied to the ground coordinate system until it is parallel to the IMU coordinate system R rotation matrix that needs to be applied to the IMU coordinate system until it is parallel to the Δ ω, Δφ, Δκ laser unit coordinate system R α,β rotation matrix that needs to be applied to the laser unit coordinate system until it is parallel to the laser beam coordinate system Ayman Habib

13 Error Sources Bore-sighting offset error (P G ) Bore-sighting angular error (Δω, Δφ, and Δκ) Laser range error (ρ) Laser beam angular error (α, β) Laser range noise (ρ) GPS noise (X o ) IMU noise (ω, φ, and κ) Laser beam angular noise (α, β) Ayman Habib

14 Error Budget Detector Bias and gain Diff b/w electronical and mechanical sensor origin Fluctuations in pulse caused by atmosphere Variance caused by SNR, variance of pulse length and variance of sampling frequency Pointing Jitter Horizontal position dependent on stability of mirror (tan of terrain slope- high relief, higher error) INS (IMU) errors Misalignment and time-dependent gyro-drift

15 Error Budget (cont) GPS Errors Orbit Errors Ionospheric and tropospheric delays, Phase ambiguities Multipath returns Atmospheric influences Propagation delays Defraction, absorption and scattering Dependent on flying height, moisture

16 Slope and flight line effects: FLIGHT LINE dz dz dz

17 Error Budget (cont) Reflectivity of target Influences SNR and consequently point precision GPS and INS integration When use the same clock, errors are minimal When don t, asychronation in the clocks cause positioning errors in the order of the velocity of the aircraft time the sync error

18 Courtesy of Amar Nayegandhi

19 Platform type Lidar Differences Profile or scanning Single, multiple, or waveform returns Footprint Size Posting density Atmospheric / terrestrial / bathymetric

20 Space- based Platforms Atmospheric Airborne Ground

21 Courtesy of Robert Kayen

22 Pulses vs Returns

23 Courtesy of Dave Harding

24 Returns Single Return Multiple returns Waveform Returns

25 Returns Single Return Multiple returns Waveform Returns 1 st return 2 nd return 3 rd return 4 th return

26

27 Courtesy of Amar Nayegandhi

28 Intensity Intensity = amount of energy reflected for each return Different surfaces reflect differently Hard to quantify DNs

29 Returns Single Return Multiple returns H E I G H T Waveform Returns Energy Returned

30 Returns Single Return Multiple returns H E I G H T Waveform Returns Energy Returned

31 Footprints Different types of systems: Large footprint

32 Footprints Different types of systems: Large footprint Small footprint

33 Beam Divergence Light tends to spread out Laser is coherent light, but spreads too Beam divergence Measured in mrads Higher up, the larger the footprint will be

34 Beam Divergence Light tends to spread out Laser is coherent light, but spreads too Beam divergence Measured in mrads Higher up, the larger the footprint will be

35 Posting Density Returns called postings Function of: Laser pulse rate Hz or khz Flying ht/speed Scan angle Not regular interval 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 1.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m 0.5m

36 Courtesy of Amar Nayegandhi

37 Raw lidar returns

38

39 Introduction Most commercial systems today are: Small footprint Multiple return Collecting imagery simultaneously Large footprint continuous waveform operated by NASA Some systems sample in the waveform

40 Current Lidar Representations Point Cloud of 3D data Triangulated Irregular Network (TIN) Raster

41

42

43 Current Lidar Representations Point Cloud of 3D data Triangulated Irregular Network (TIN) Raster

44 Converting Points to TIN

45 TIN Without Breaklines Not Hydro-Enforced Courtesy of Dave Maune

46 TIN With Breaklines Hydro Hydro- Enforced Courtesy of Dave Maune

47 Current Lidar Representations Point Cloud of 3D data Triangulated Irregular Network (TIN) Raster (Grid)

48 Interpolating a Raster- IDW

49 Research and Applications

50 A wealth of information derived from lidar Volcano monitoring Vegetation / Biomass Land Cover Earthquake faults Hydrologic / Hydraulic Urban / Suburban Response Coastal Studies Carbon studies

51 Lidar Applications Visualization Vendor Data Dissemination Bare Earth Analyses Vegetative Analyses Structural Analyses

52 Bare Earth Analysis Primary focus of commercial sector $$$$$ Technology is become widely accepted More cost effective / accurate than photogrammetry

53

54 1-arc-second resolution 1/3-arc-second resolution 1/9-arc-second resolution

55 Multi-resolution NED: 1-arc-second 1/3-arc-second 1/9-arc-second

56 Multi-Resolution NED 1 arc second 1/3 arc second 1/9 arc second

57 Manual Post-Processing

58 Northern San Andreas LIDAR: fault geomorphology Courtesy of Carol Prentice

59 Vegetation

60 Bare Earth Filtering

61

62 Vegetation Identified

63 Canopy Height

64 Canopy Height

65 Canopy Height Model Leon County, FL

66 Canopy Height

67

68 Crown Base Height Distance from the ground to the lowest needle-bearing branch Important in fire modeling Surface fire / crown fire Crown Base Height

69 Length Length of of live live crown crown Crown base height

70 Multi-temporal LIDAR As LIDAR collections increase, there will be more availability to use LIDAR for monitoring change detection purposes

71 Monitoring Growth with LIDAR Individual Tree LIDAR Datasets m height growth Courtesy of Hans-Erik Andersen

72 Mount Saint Helens Courtesy of Dave Harding

73

74 Bare earth difference

75

76 Bare earth difference

77 Lidar / Spectral Fusions

78

79 Intensity information Trees Roof types Grass Water

80 Lidar point cloud of Structures

81

82 Feature Extraction using Lidar

83 National Lidar Initiative Meeting February th 2007, USGS headquarters

84

85

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