This document provides an overview of an Eastern West Virginia LiDAR acquisition project. Key details include the project was 100% complete, products are being delivered as completed, and specifications were designed to meet FEMA and USGS requirements. Contact information is provided for several project managers from Dewberry and USGS.

1. Eastern West Virginia LiDAR Acquisition
Josh Novac
Project Manager
Dewberry (Tampa, FL)
jnovac@dewberry.com

2. Project Overview

3. Project Overview
• LiDAR Acquisition Scheduled for Winter/Spring 2012
• LiDAR Acquisition is 100% Complete
• Products are currently being delivered as they are completed
• Collection designed to meet FEMA needs and USGS V13
Specifications for LiDAR

4. Project Overview- Specifications
• Nominal Pulse Spacing < 1 meter
• Vertical Accuracy
– RMSEZ 12.5 cm
– Fundamental Vertical Accuracy (FVA): 24.5 cm
– Consolidated Vertical Accuracy (CVA): 36.3 cm
– Supplemental Vertical Accuracy (SVA): 36.3 cm
• Relative Accuracy
– Within an Individual Swath ≤ 7 cm
– Between Swaths ≤ 10 cm

5. Project Overview- Specifications
• Spatial Reference System
– Horizontal
• North American Datum of 1983
• UTM Zone 18N
• Meters
– Vertical
• North American Vertical Datum of 1988
• Geoid 2009
• Meters

6. Project Overview – Specifications
• Breaklines
– Inland Ponds and Lakes:
• 2 acres or greater
• Flat and level (each vertex must have the same elevation)
• Water surface must be at or just below adjacent ground
– Inland Streams and Rivers:
• 100’ nominal width
• Flat and level bank to bank
• Should flow continuously downhill (monotonic)

7. Project Overview - Specifications
• LiDAR Classification
– LAS format (v1.2) with ASPRS classification scheme
• Class 1 – Processed, Unclassified
• Class 2 – Bare-Earth, Ground
• Class 7 – Noise (High/Low Points)
• Class 9 – Water (Classified Using Breaklines)
• Class 10 – Ignored Ground (Breakline Proximity)

8. Project Overview – Deliverables
• Raw Point Cloud
– LAS V1.2
– Georeference Information in Header Files
– GPS times recorded as Adjusted GPS Time
– Intensity Values
– Full Swaths
– Size not to exceed 2GB per swath

9. Project Overview - Deliverables
• Classified Point Cloud
– LAS V1.2
– Meet V13 Specifications for Classification (The new V1 specs are now
out)
– Tiled at 1500 m x 1500 m to U.S. National Grid
• Bare Earth Surface (Raster DEM)
– Cell Size of 1 meter
– ERDAS .IMG format (32-bit floating point)
– Depressions/Sinks not filled (Hydro-flattened DEM not Hydro-enforced
DEM)

10. Project Overview - Deliverables
• Control
– Supplemental Ground Control – Used to control the LiDAR collection
and processing
– Ground Control Quality Checkpoints
• Minimum of 20 points across 5 land cover types
– Bare Earth/ Open Terrain
– Urban
– Tall Weeds/Crops
– Brush and Trees
– Forested
• Must be on flat or uniformly sloping terrain

11. Project Overview - Deliverables
• Metadata
– FGDC Compliant
– Overview of processing steps and procedures
• Project Report
– Detailed records of collection, production, and quality assurance
processes

12. Project Overview - Schedule
Deliverable Description Due Date Status
Mobilization 12/16/2012 Complete
LiDAR Acquisition 03/09/2012 Complete
Survey (QA/QC Points) 02/10/2012 Complete
LiDAR Calibration 05/11/2012 Complete
Pilot Deliverable 05/25/2012 Complete
Full Deliverable 11/15/2012 In Progress
Final Acceptance 12/15/2012

13. Project Overview - Contacts
• USGS State Liaison – Craig A. Neidig
Charleston, WV
304-347-5130 x237
cneidig@usgs.gov
• USGS Project Manager – Patrick Emmett
Rolla, MO
573-308-3587
pemmett@usgs.gov
• Dewberry – Josh Novac
Tampa, FL
813-421-8632
jnovac@dewberry.com

14. LiDAR Technology

15. What is LiDAR
• Light Detection and Ranging
• Active Scanning System
– Uses its own energy source to produce pulses of laser
(light) which are emitted, reflected and then received from
surfaces
• Measures range distances
– Based on time between emission, reflection and receive
time
• Direct terrain measurements, unlike photogrammetry
which is inferred
• Day or night operation except when coupled with
digital camera
• In addition to ranging, LiDAR systems can provide:
– Additional information about the target (for classification)
– Information about the transmission path (e.g. DIAL to
measure concentration of elements in the atmosphere)

16. What LiDAR is NOT
• The answer to all your elevation requirements
• All-weather
– Target must be visible within the selected EM spectrum
– No rain or fog
– Must be below clouds
• Able to “penetrate vegetation”
– LiDAR can penetrate openings in the vegetation cover but
cannot see through closed canopies

17. Airborne LiDAR System Components
 LiDAR Transmitter, Scanner, and
Receiver
 Aircraft Positioning – Differential
GPS (with post-processing)
 Aircraft Attitude – Pitch, Roll, Yaw –
Inertial Navigation System (GPS-
Aided)
 Data System

18. Operating Wavelengths
Wavelength (not to scale) 100µm
0.0001µm 0.01µm 0.2µm 0.3 0.4 0.7 1.5 5.6µm 20µm 100µm 1cm 10cm 1m
0.1cm
Gamma X-Rays Ultraviolet Visible Infrared Microwave TV/Radio
Rays
Passive Microwave
Film Active RADAR
Electro-optical Sensors
Thermal IR
 In theory, any light source can be used to create a LiDAR instrument
 Near-Infrared wavelength
 Used by most airborne terrestrial LiDAR systems
 Easily absorbed at the water surface (unreliable water surface reflections).
 Wavelengths utilized: 1000 – 1500 nm
 Blue-Green Wavelength
 Used by all airborne bathymetric and “topobathymetric” systems (532 nm)
 Can penetrate water, but signal strength attenuates exponentially through the
water column

19. Laser system characteristics
• Pulse width (or duration) is usually defined as the time
during which the laser output pulse power remains
continuously above half its maximum value (FWHM).
Pulse width
intensity
“short”
pulse
“long” pulse
time (ns)
pulse width

20. Multiple Scanning Patterns (two most common)
It is common to withhold the data for a
few percent at the tips of the zig-zags
where elevations are less accurate

21. Various LiDAR Formats
Threshold
Short Duration
Laser Pulse
Digitized Discrete Pulse- Photon
Backscatter Return Width Counting
Waveform Leading-
Edge
Image courtesy Dave Harding, NASA

22. Discrete return vs. waveform-resolving and the “dead zone”
effect
Discrete-return LiDAR Waveform-resolving LiDAR
 most discrete-return systems require a minimum vertical object separation to
register consecutive returns from the pulse separately, thereby being blind to
canopy material within this dead zone

23. Flight Planning Considerations
Maximum scan angle? Leaf-on or leaf-off?

24. Laser Penetration

25. Discrete Return LiDAR systems
Image courtesy Hans-Erik Anderson

26. LiDAR Systems Manufacturers
• Leica Geosystems
• Optech Inc.
• Riegl

27. Enabling Technologies: Aircraft Position and Attitude
Determination

28. Lidar System Components
• Lidar Transmitter, Scanner,
and Receiver
• Aircraft Positioning –
Differential GPS (with
post-processing)
• Aircraft Attitude –
Pitch, Roll, Yaw – Inertial
Navigation System (GPS-
Aided)

29. Differential GPS
•
•
•
•

30. Inertial Measurement Unit - IMU
•
•
•
•
•

31. IMU - Orientation
Pitch Yaw Roll

32. LiDAR Data Processing

33. LiDAR Data Processing Workflow
DGPS Data
Lidar range
Calibration and
IMU Data mounting
Scan Angles
parameters
Post-processed GPS trajectory and INS
solutions
Point Cloud Data
X, Y, Z data

34. Data Processing Steps
• Initial processing done in field
• Process GPS/IMU
• Process calibration data
• Process waveform data (if available)
• Process full point cloud to calibration
• Verify data (i.e. flight line comparison, coverage,
accuracy, etc.)
• Post Processing – Classification; auto and manual
filtering

35. LiDAR: Raw Data Processing
• Data collected by flight
• Monitored during collection
– Sensor operation
– Flight line holidays
– Data voids
– Gross data errors
• Calibration flight at start and end
of flight for adjustment of system
and systematic drift
• GPS Data processing (kinematic
post-processing aircraft GPS to
reference station)
• Results in X Y Z, Scan Angle,
Intensity, Return# ASCII or Binary
files – Typically LAS

36. LiDAR post-processing creates a point cloud

37. LiDAR: Post Processing - Classification
• Separating ground from non-ground
– Automated Processing
– Manual Processing

38. Post Processing - Classification
• Automated scripts
– Classifies approximately 80 – 85% and takes 20% of the time
– Algorithm must be balanced to classify correctly - May cut into slopes too
much, or leave too much artifacts
– Color coding orange = ground, green = other

39. Post Processing - Classification
• Manual Classification
– Impossible to classify to the 100% level
– Manual classification takes 80% of the post processing time (to get that last
20%)
– Color coding orange = ground, green = other

40. ASPRS Standard LiDAR Point Classes
Classification Meaning
Value
(bits 0:4)
0 Created, never classified
1 Unclassified
2 Ground
3 Low Vegetation
4 Medium Vegetation
5 High Vegetation
6 Building
7 Low Point (noise)
8 Model Key-point (mass point)
9 Water
10 Reserved for ASPRS Definition
11 Reserved for ASPRS Definition
12 Overlap Points

41. LAS Classified by Class

42. Elevation Data Challenges
• Large number of elevation records can require long processing
times
• Exploitation of LiDAR has typically required specialized software
such as
• GeoCUE
• QT Modeler
• Terrascan/Terramodeler
• Many new LiDAR programs are being introduced which will allow more
users access to the data
• ArcGIS – Version 10.1
• FugroViewer – Free
• LAS Reader for ArcGIS – Free
• PointView LE - Free

43. LiDAR Software Tools
• ArcGIS (10.1)
• Geocue (Geocue)
• LP 360 (GeoCue)
• Quick Terrain Modeler (Applied Imagery)
• Terrascan (Terrasolid)
• LASTools
• FugroViewer
Sample list – no endorsement is inferred or implied

44. Data Verification & Quality Control (QA/QC)

45. Data Verification & Quality
Three fundamental questions MUST BE
ASKED
1. Did the LiDAR system work
2. Are the data classified properly and free of
artifacts to support the intended product?
3. Is the dataset complete?

46. Types of Analysis
• Quantitative Analysis
– Utilize survey checkpoints to verify TIN accuracy
– FEMA only “requires” quantitative analysis
• Qualitative Analysis
– Subjective analysis to assess the quality which can include
cleanliness, usefulness for the intended product etc.
• Completeness
– Are tiles complete with no voids, correct location,
projection information, classified to the correct classes etc.

47. Dewberry’s Approach to QA/QC

48. Dewberry’s Approach to QA/QC
• Inventory (completeness)
• Quantitative
• Qualitative
• Reporting

49. Quantitative Verification
• Ground truth surveys
– Utilize GPS and conventional survey checkpoints (cp)
– Place checkpoints in strategic locations based on flight line pattern
– Verify data in varied land cover categories
– Compare CP with interpolated TIN value

50. Qualitative Assessment - Techniques
• Utilize different software and tools
• Use imagery
• Create pseudo imagery •
•
• Combine images or techniques •
•
•
•
•
•
•
•

51. Derivative Products

52. Intensity Images
• Measures the amount of light
returning to the sensor
• Useful for QA/QC & Research
– Identify conditions at time of
collection
• Can be used for stereo-
compilation to generate 3D
breaklines
(“LiDARgrammetry) or 2D
features

53. Breaklines
• Linear features that control surface behavior
• Can be 2D or 3D
• Traditionally derived from stereo photogrammetry or from
surveys
• Can use LiDAR and Intensity to create breaklines
• 2D breaklines with assigned elevations for hydro-flattening are
typically used.

54. Terrain Dataset
 A Terrain Datasets is a multi-resolution
TIN-based surface build on-the-fly from
feature classes stored in a feature dataset
of a geodatabase.
 Terrain Datasets are more effective for
storing and visualizing large point data
sets.
 A Terrain Datasets resides in the same
feature dataset where the feature classes
(used to construct it) reside.
 Terrain Datasets can be used to obtain
TINs and grids.

55. Terrain Dataset
 In a Terrain Dataset, feature classes
include:
 Mass points (e.g., LiDAR);
 Breaklines (hard and soft);
 Clipping polygons (hard and soft);
 Erase polygons (hard and soft);
 Replace polygons (hard and soft).
 A Terrain Dataset is composed of a series
of TINs, each of which is used within a
map-scale range. For each map-scale
range, a level of detail (i.e., z resolution)
and pyramid level are defined.

56. Different Treatments of LiDAR DTMs and DEMs
• Traditional Stereo DTM (Topographic Surface)
• Pure LiDAR (Topographic Surface)
• Hydro-Flattened (Topographic Surface)
• Full Breaklines (Topographic Surface)
• Hydro-Enforced (Hydrologic Surface)
• Hydro-Conditioned (Hydrologic Surface)

57. Traditional Stereo DTM (Topographic Surface)
• Reference image of the
traditional stereo-
compiled DTM
• Built from Masspoints
and Breaklines
• Much coarser resolution
than LiDAR
• Demonstrates the familiar
and usually expected
character of a
topographic DEM
• Most notably, the “flat”
Stream Waterbody water surfaces

58. Pure LiDAR (Topographic Surface)
• DEM created only using bare-
earth LiDAR points
• Surface contains extensive
triangulation artifacts
(“TINning”).
• Cause by the absence of:
– LiDAR returns from water
– Breakline constraints that
would define buildings, water,
and other features (as in the
Stereo DTM).
• Aesthetically and
cartographically unacceptable
to most users
TINning in Water Areas

59. Hydro-Flattened (Topographic Surface)
• The goal of the v13 Spec
• Intent is to support the development of
a consistent, acceptable character
within the NED
• Removes the most offensive pure LiDAR
artifacts: those in the water.
– Constant elevation for waterbodies.
– Wide streams and rivers are flattened
bank-to-bank and forced to flow
downhill (monotonic).
• Carries ZERO implicit or explicit
accuracy with regards to the
represented water surface elevations –
It is ONLY a cartographic/aesthetic
enhancement.
• Building voids are not corrected due to
high costs
• Most often achieved via the
development and inclusion of hard
Stream Waterbody breaklines.

60. Full Breaklines (Topographic Surface)
• A further possible
refinement of the hydro-
flattened surface
• Removes artifacts from
building voids
• Refines the delineation of
roads, single-line
drainages, ridges, bridge
crossings, etc.
• Requires the development of
a large number of additional
detailed breaklines
• A higher quality topographic
surface, but significantly
more expensive.
Buildings Roads • Not cost effective for the
NED.

61. Hydro-Enforced (Hydrologic Surface)
• Surface used by engineers in
Hydraulic and Hydrologic
(H&H) modeling.
• Similar to Hydro-Flattened
with the addition of Single
Line Breaklines: Pipelines,
Culverts, Underground
Streams, etc…
• Terrain is then cut away at
bridges and culverts to model
drain connectivity
• Water Surface Elevations
(WSEL) are often set to known
Culverts Cut Through Roads values (surveyed or historical).

62. Hydro-Conditioned (Hydrologic Surface)
• Another type of surface
used by engineers for H&H
modeling.
• Similar to the hydro-
enforced surface, but with
sinks filled
• Flow is continuous across
the entire surface – no
areas of unconnected
internal drainage
• Often achieved via
ArcHydro or ArcGIS Spatial
Analyist

63. Common Data Upgrades to USGS V13 Spec.
1. Independent 3rd party QA/QC
2. Higher Nominal Pulse Spacing (NPS)
3. Increased Vertical Accuracy
4. Full waveform or topo/bathy collection with red/green lasers
5. Tide coordination, flood stage, plant growth cycle, shorelines
6. Top-of-canopy (1st return) Digital Surface Model (DSM)
7. More detailed LAS classification for vegetation, buildings
8. Hydro enforced and/or hydro conditioned DEMs
9. Single-line hydro feature breaklines; other breaklines
10. Building footprints with elevations/heights
11. Additional data products such as contours

64. Generating Contours from LiDAR
Contours are produced
Not aesthetically pleasing from LiDAR mass points
and breaklines

65. ASPRS’ “DEM Users Manual”
1. Intro to DEMs, 3-D Surface Modeling,
Tides
2. Vertical Datums
3. Accuracy Standards
4. National Elevation Dataset
5. Photogrammetry
6. IFSAR
7. Topographic & Terrestrial Lidar
8. Airborne Lidar Bathymetry
9. Sonar
10. Enabling Technologies
11. DEM User Applications
12. DEM Quality Assessment
13. DEM User Requirements
14. Lidar Processing & Software
15. Sample Elevation Datasets

67. Final Report for NEEA Study available at
www.dewberry.com
http://www.dewberry.com/Consultants/GeospatialMapping/FinalReport-
NationalEnhancedElevationAssessment

68. THANK YOU
Josh Novac
Project Manager
Remote Sensing Services Line
Dewberry (Tampa, FL)
jnovac@dewberry.com
Ph: 813.421.8632