overview and user perspective of usgs 3 dep lidar

1. Overview and
User Perspective
of 3DEP LidarJohn J. Kosovich
U.S. Geological Survey
Denver, CO
jjkosovich@usgs.gov
September 22, 2016

2. Disclaimer
Any use of trade, product, or firm
names is for descriptive purposes
only and does not imply
endorsement by the U.S.
Government.

3. Terminology
IfSAR = interferometric synthetic aperture radar
- Radar = radio detection and ranging.
- Radar (microwave) pulses spread over surface perpendicular to airplane (side look).
- Accurate DEM obtained from phase difference & timing of returning pulses.
- Also get Radar DOQ (ORI) from magnitude (intensity) of returning pulses.
- Active sensing: can collect at night.
- Can see through typical cloud cover.
lidar = light detection and ranging (topographic)
- Laser pulse hits surface thousands of times each second as airplane flies.
- Main product is an irregularly spaced “point-cloud” of lidar hits (“returns”).
- Very accurate gridded DEM is derived from ground returns.
- Can get lidar intensity image (ortho-rectified, grayscale).
- Active sensing: can collect at night.
- Cannot see through typical cloud cover.
- Typically called “linear lidar”.
- Also have bathymetric lidar, uses different wavelength to penetrate water.
- Latest technologies: multispectral, single-photon (SP), and Geiger-mode (GM) lidar.

4. From EarthData, Inc. original
• Lidar = light
detection and
ranging
• Active sensing: can
collect at night
• Cannot “see”
through typical cloud
cover
• Timing of returned
pulse gives elevation
• Magnitude of
returned pulse gives
intensity
• Minimum of
thousands of pulses
per second (KhZ+)
• Multiple returns
potentially from each
transmitted pulse
Lidar Collection

5. From EarthData, Inc. original
Multiple Returns per pulse
Multiple Returns

6. Lidar Terminology
“Linear” = traditional, where laser pulses are sent and returned in sequence. Can be
aerial-, tripod-, or satellite-based.
Terrestrial = tripod, close range, extremely dense (~1000s of points / m ).
Waveform = Entire pulse’s returned energy signature digitized, peaks typically become
the discrete points. Waveforms are not always saved unless required by customer.
Discrete returns = Points from pulse where returned energy from waveform is greatest.
Multiple returns = each pulse may hit more than one object and continue down, resulting
in several discrete returns (points) per pulse.
Point cloud = all returns from all pulses. Points located in X,Y,Z coordinate space.
Point density = nominal number of points per unit area (2D space, usually 1st
returns).
Point (pulse) spacing = nominal spacing between points (2D space, usually 1st
returns).
DSM = digital surface model, gridded raster, contains canopy, buildings, etc.
DTM = digital terrain model, gridded raster, bare-earth ground DEM.
Intensity = grayscale raster made from energy intensity of return points.
2

7. Waveform vs. Discrete
Courtesy of Optech, Incorporated and Remote Sensing Open Access Journal
Ussyshkin, V., and Theriault, L., Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping. Remote Sens. 2011, 3, 416-434, Figure 6.

8. Gridded Lidar DEMs (canopy height model and bare-earth ground) do not contain true 3D structure,
but the point cloud does:
Gridded Lidar DEMs (canopy height model and bare-earth ground) do not contain true 3D structure,
but the point cloud does:
Why Use Point Cloud?
Lidar digital surface model (DSM) =
Canopy Height Model (CHM)
for forested areas
Lidar point cloud
Lidar digital terrain model (DTM) =
bare-earth ground surface

9. X-band IfSAR
Typical lidar:
topo ~1064 nm,
bathy ~400 - 532 nm
Electromagnetic Spectrum
P-band IfSAR
EM spectrum image from Intermap Technologies, Inc. original

10. Electromagnetic Spectrum
EM spectrum image from Intermap Technologies, Inc. original
Time
Time
Longer wavelength, lower frequency (wave)
Lower photon energy (quantum particle)
Shorter wavelength, higher frequency (wave)
Higher photon energy (quantum particle)
Speed of light ≈ 3.0 x 10 meters/sec
≈ (186,000 miles/sec)
c = λ x ν = wavelength x frequency
8
(in a vacuum)

11. 10m USGS DEM

12. 1m Lidar Terrain Model

13. DEM Horizontal Resolution
10m
2m
30m
1m
Photo by John Kosovich,
USGS

14. 3DEP
(3D Elevation Program)
Products

15. 3DEP Products
http://nationalmap.gov/3DEP

16. 3DEP Products

17. 3DEP Products

18. 3DEP Products

19. 3DEP Product Availability
http://nationalmap.gov/3DEP

20. 3DEP Product Availability
http://nationalmap.gov/3DEP/3dep_prodavailability.html#/

21. 3DEP Product Availability

22. 3DEP Product Availability

23. 3DEP Product Availability

24. 3DEP Quality Level (QL)
Point density = nominal number of points per unit area (pts/m ).
Point (pulse) spacing = nominal spacing between points (m).
2
point density =
1
(point spacing)
2
point spacing =
1
point density
0 1m 2
QL1: 8 pts/m density
0.35m spacing
2
0 1m 2
QL2: 2 pts/m density
0.7m spacing
2
0 1m 2
QL3: 0.5 pts/m density
1.4m spacing
2

25. 3DEP Product Availability

26. 3DEP Product Availability

27. 3DEP Product Availability

28. 3DEP Product Availability

29. 3DEP Product Availability

30. 3DEP Product Availability

31. 3DEP Product Availability

32. 3DEP Product Availability

33. 3DEP Product Availability

34. 3DEP Product Availability

35. 3DEP Product Download
http://nationalmap.gov/3DEP/3dep_prodavailability.html#/

36. http://viewer.nationalmap.gov/basic/?basemap=b1&category=ned,nedsrc&title=3DEP%20View
3DEP Product Download

37. http://viewer.nationalmap.gov/basic/?basemap=b1&category=ned,nedsrc&title=3DEP%20View
3DEP Product Download

38. http://viewer.nationalmap.gov/basic/?basemap=b1&category=ned,nedsrc&title=3DEP%20View
3DEP Product Download

39. 3DEP Products
Delivered
By Vendor

40. NGP Lidar Deliverables
Required by USGS Lidar Base Spec v1.2 (2014):
http://pubs.usgs.gov/tm/11b4/
Quality Level 2 or better (0.7m spacing, 2 pts/m )
Raw Point Cloud (flight line swaths, .LAS file format)
Classified Point Cloud (tiled .LAS as per project,
includes intensity values for each return)
Bare-Earth Surface DEM (= DTM, 32-bit raster format)
Breaklines used in hydro-flattening (ESRI vector)
Metadata (FGDC-compliant)
2

41. Raw Point Cloud
All points are unclassified

42. Classified Point Cloud

43. Point Cloud Classes
Required by USGS Lidar Base Specification 1.2 (pg. 11)

44. Point Cloud Classes
ASPRS LAS Specification, Version 1.4 – R13, July 15, 2013, pg. 17
http://www.asprs.org/a/society/committees/standards/LAS_1_4_r13.pdf

45. Lidar Point Cloud

46. Noise hit: ~400 m
(~1300 ft) above
ground
(Not classified as
Noise, had to be
edited)
Noise hit: ~700 m
(~2300 ft) below
ground
(Not classified as
Noise, had to be
edited)
Contrails ~2000m
(~6500 ft) above
ground:
(These were
classified as Noise
by vendor)
Contrails ~2000m
(~6500 ft) above
ground:
(These were
classified as Noise
by vendor)
Noise (2011 ARRA)

47. Classified Point Cloud

48. Non-Lidar Comparison Image
(not a deliverable product)

49. Lidar Digital Terrain Model
(DTM)

50. Products
Derivable
From
Point Cloud

51. Lidar Digital Surface Model
(DSM)

52. Lidar Digital Terrain Model
(DTM) - from Vendor

53. DSM-DTM Diff Grid
Output product -- Lidar Digital Surface Model minus Digital Terrain Model difference surface

54. DSM-DTM Diff Image
Output product -- 5-color Digital Surface Model minus Digital Terrain Model difference image

55. DSM-DTM Diff Image
Interactive ArcMap transparency over DSM hillshade

56. DSM – DTM Difference
Difference surface derived from lidar: normalized (topography removed) canopy heights above groundDifference surface derived from lidar: normalized (topography removed) canopy heights above ground

57. Edited Point Cloud

58. Lidar Intensity –
1st Returns

59. Lidar Intensity –
2nd Returns

60. Lidar Intensity –
3rd Returns

61. Lidar Intensity –
Last Returns

62. 11-band Image
Derived from Lidar Intensity
Bands 11,1,4 as R,G,B: unaltered 1st
returns, 1st
-to-Last returns, 2nd
-to-Last returns ratios

63. Delineate Features for Map
Bands 11,1,4 as R,G,B: unaltered 1st
returns, 1st
-to-Last returns, 2nd
-to-Last returns ratios

64. Make Map
Polygons solely from lidar intensity images, power lines from point cloud, hillshade from DTM)
Ü

65. Comparison Image
ArcGIS Basemap image

66. Latest
Lidar
Technologies

67. Multispectral Lidar
From Teledyne Optech: http://www.teledyneoptech.com/index.php/product/titan/
IR 1550 nmNIR 1064 nmBathy 532 nm

68. Single Photon (SP)
Single Photon Counting Lidar
- Sigma Space Corporation (Hexagon Geospatial) developed HRQLS (high resolution
quantum lidar system).
- 532nm green laser transmitted pulses are diffracted into 10 x 10 beamlets.
- Receiver array can detect single photons.
- Topographic and bathymetric collection.
- Decent vegetation penetration (per USGS evaluation reported at 2016 ILMF).
- Company has since improved HRQLS for better vegetation penetration.
- Reflectance image made from photon count per pixel, ~ similar to intensity image
from “linear” lidar.
Courtesy of Sigma Space Corp. and LaserFocusWorld
http://www.laserfocusworld.com/articles/print/volume-47/issue-9/world-news/lidar-photon-counting-3d-imaging-lidar-measures-biomass-and-the-cryosphere.html

69. Geiger-Mode (GM)
Geiger-Mode Lidar
- Harris Corporation developed IntelliEarth sensor (Palmer scanner, SP Avalanche
Photodiode).
- 1064nm IR laser pulses produce elliptical sweep over flight line.
- Sensor samples the same ground area multiple times.
- Multi-angle illumination of target area.
- Receiver consists of 32 x 128 array of photon-counting detectors (= 4096 total).
- Topographic collection.
- Poor vegetation penetration (per USGS evaluation), but improvements promised.
- Reflectance image made from photon count per pixel, ~ similar to intensity image
from “linear” lidar.
TM
Courtesy of Harris Corporation
http://asprs.org/a/publications/proceedings/IGTF2015/5H[4]-slides.pdf

70. SP and GM Links
ILMF Write-up of USGS Evaluation Report:
http://www.spar3d.com/news/lidar/single-photon-and-geiger-mode-vs-linear-mode-lidar/
Single Photon Lidar:
http://www.spar3d.com/news/lidar/single-photon-lidar-proven-forest-mapping/
Geiger Mode Lidar:
http://asprs.org/a/publications/proceedings/IGTF2015/5H[4]-slides.pdf

71. Terrestrial
Lidar
(Not in 3DEP)

72. Photo by John Kosovich,
USGS
Terrestrial Laser Scanning

73. Photo by John Kosovich,
USGS
Spherical Targets

74. Slide by John Kosovich,
USGS
Terrestrial Lidar Data
Terrestrial and Aerial Lidar

75. Slide by John Kosovich,
USGS
Terrestrial vs. Aerial Lidar

76. Slide by John Kosovich,
USGS
Terrestrial vs. Aerial Lidar

77. Slide by John Kosovich,
USGS
Terrestrial vs. Aerial Lidar

78. Slide by John Kosovich,
USGS
Terrestrial vs. Aerial Lidar

79. Photo by Dick Grauch,
USGS
August, 2007
Slump
Change Detection

80. Slide by John Kosovich,
USGS
M2_2007
Slump
Change Detection - 2007

81. Slide by John Kosovich,
USGS
Slump
New Slump
M2_2008
Change Detection - 2008

82. Slide by John Kosovich,
USGS
2008 – 2007 Difference
2008 minus 2007:
Old Slump
New Slump

83. QUESTIONS?