2016 asprs track: overview and user perspective of usgs 3 dep lidar by john kosovich

Overview and User Perspective

of 3DEP LidarJohn J. Kosovich

U.S. Geological SurveyDenver, CO

jjkosovich@usgs.govSeptember 22, 2016

Disclaimer

Any use of trade, product, or firm names is for descriptive purposes

only and does not imply endorsement by the U.S.

Government.

TerminologyIfSAR = 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.

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

From EarthData, Inc. original

Multiple Returns per pulseMultiple Returns

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

Waveform vs. Discrete

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

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

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

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)

10m USGS DEM

1m Lidar Terrain Model

DEM Horizontal Resolution

10m

2m

30m

1m

Photo by John Kosovich, USGS

3DEP(3D Elevation Program)

Products

3DEP Productshttp://nationalmap.gov/3DEP

3DEP Products

3DEP Products

3DEP Products

3DEP Product Availabilityhttp://nationalmap.gov/3DEP

3DEP Product Availabilityhttp://nationalmap.gov/3DEP/3dep_prodavailability.html#/

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

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) 2point 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

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Availability

3DEP Product Downloadhttp://nationalmap.gov/3DEP/3dep_prodavailability.html#/

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

3DEP Product Download

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

3DEP Product Download

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

3DEP Product Download

3DEP ProductsDelivered By Vendor

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

Raw Point Cloud

All points are unclassified

Classified Point Cloud

Point Cloud ClassesRequired by USGS Lidar Base Specification 1.2 (pg. 11)

Point Cloud ClassesASPRS LAS Specification, Version 1.4 – R13, July 15, 2013, pg. 17

http://www.asprs.org/a/society/committees/standards/LAS_1_4_r13.pdf

Lidar Point Cloud

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)

Noise (2011 ARRA)

Classified Point Cloud

Non-Lidar Comparison Image(not a deliverable product)

Lidar Digital Terrain Model (DTM)

ProductsDerivable

FromPoint Cloud

Lidar Digital Surface Model (DSM)

Lidar Digital Terrain Model (DTM) - from Vendor

DSM-DTM Diff GridOutput product -- Lidar Digital Surface Model minus Digital Terrain Model difference surface

DSM-DTM Diff ImageOutput product -- 5-color Digital Surface Model minus Digital Terrain Model difference image

DSM-DTM Diff ImageInteractive ArcMap transparency over DSM hillshade

DSM – DTM DifferenceDifference surface derived from lidar: normalized (topography removed) canopy heights above

ground

Edited Point Cloud

Lidar Intensity – 1st Returns

Lidar Intensity – 2nd Returns

Lidar Intensity – 3rd Returns

Lidar Intensity – Last Returns

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

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

Make MapPolygons solely from lidar intensity images, power lines from point cloud, hillshade from DTM)

Ü

Comparison ImageArcGIS Basemap image

LatestLidar

Technologies

Multispectral Lidar

From Teledyne Optech: http://www.teledyneoptech.com/index.php/product/titan/

IR 1550 nmNIR 1064 nmBathy 532 nm

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 LaserFocusWorldhttp://www.laserfocusworld.com/articles/print/volume-47/issue-9/world-news/lidar-photon-counting-3d-imaging-lidar-measures-biomass-and-the-cryosphere.html

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 Corporationhttp://asprs.org/a/publications/proceedings/IGTF2015/5H[4]-slides.pdf

SP and GM LinksILMF 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

TerrestrialLidar

(Not in 3DEP)

Photo by John Kosovich, USGS

Terrestrial Laser Scanning

Photo by John Kosovich, USGS

Spherical Targets

Slide by John Kosovich, USGS

Terrestrial Lidar Data

Terrestrial and Aerial Lidar

Slide by John Kosovich, USGS

Terrestrial vs. Aerial Lidar

Slide by John Kosovich, USGS

Terrestrial vs. Aerial Lidar

Slide by John Kosovich, USGS

Terrestrial vs. Aerial Lidar

Slide by John Kosovich, USGS

Terrestrial vs. Aerial Lidar

Photo by Dick Grauch, USGS

August, 2007

Slump

Change Detection

Slide by John Kosovich, USGS

M2_2007

Slump

Change Detection - 2007

Slide by John Kosovich, USGS

Slump

New Slump

M2_2008

Change Detection - 2008

Slide by John Kosovich, USGS

2008 – 2007 Difference2008 minus 2007:

Old Slump

New Slump

QUESTIONS?