Eastern WV LiDAR Acquisition


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Presented by Josh Novac Project Manager Dewberry (Tampa, FL) at EPAN User Group Meeting in August 2012 in Martinsburg, WV

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Eastern WV LiDAR Acquisition

  1. 1. Eastern West Virginia LiDAR Acquisition Josh Novac Project Manager Dewberry (Tampa, FL) jnovac@dewberry.com
  2. 2. Project Overview
  3. 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. 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. 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. 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. 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. 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. 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. 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. 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. 12. Project Overview - Schedule Deliverable Description Due Date StatusMobilization 12/16/2012 CompleteLiDAR Acquisition 03/09/2012 CompleteSurvey (QA/QC Points) 02/10/2012 CompleteLiDAR Calibration 05/11/2012 CompletePilot Deliverable 05/25/2012 CompleteFull Deliverable 11/15/2012 In ProgressFinal Acceptance 12/15/2012
  13. 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. 14. LiDAR Technology
  15. 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. 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. 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. 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 0.1cmGamma 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. 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 widthintensity “short” pulse “long” pulse time (ns) pulse width
  20. 20. Multiple Scanning Patterns (two most common)It is common to withhold the data for afew percent at the tips of the zig-zagswhere elevations are less accurate
  21. 21. Various LiDAR Formats Threshold Short Duration Laser Pulse Digitized Discrete Pulse- Photon Backscatter Return Width Counting Waveform Leading- EdgeImage courtesy Dave Harding, NASA
  22. 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. 23. Flight Planning Considerations Maximum scan angle? Leaf-on or leaf-off?
  24. 24. Laser Penetration
  25. 25. Discrete Return LiDAR systems Image courtesy Hans-Erik Anderson
  26. 26. LiDAR Systems Manufacturers• Leica Geosystems• Optech Inc.• Riegl
  27. 27. Enabling Technologies: Aircraft Position and AttitudeDetermination
  28. 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. 29. Differential GPS••••
  30. 30. Inertial Measurement Unit - IMU•••••
  31. 31. IMU - Orientation Pitch Yaw Roll
  32. 32. LiDAR Data Processing
  33. 33. LiDAR Data Processing Workflow DGPS Data Lidar range Calibration and IMU Data mounting Scan Angles parametersPost-processed GPS trajectory and INS solutions Point Cloud Data X, Y, Z data
  34. 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. 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. 36. LiDAR post-processing creates a point cloud
  37. 37. LiDAR: Post Processing - Classification• Separating ground from non-ground – Automated Processing – Manual Processing
  38. 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. 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. 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. 41. LAS Classified by Class
  42. 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. 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. 44. Data Verification & Quality Control (QA/QC)
  45. 45. Data Verification & QualityThree 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. 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. 47. Dewberry’s Approach to QA/QC
  48. 48. Dewberry’s Approach to QA/QC• Inventory (completeness)• Quantitative• Qualitative• Reporting
  49. 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. 50. Qualitative Assessment - Techniques• Utilize different software and tools• Use imagery• Create pseudo imagery • •• Combine images or techniques • • • • • • • •
  51. 51. Derivative Products
  52. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 63. Common Data Upgrades to USGS V13 Spec.1. Independent 3rd party QA/QC2. Higher Nominal Pulse Spacing (NPS)3. Increased Vertical Accuracy4. Full waveform or topo/bathy collection with red/green lasers5. Tide coordination, flood stage, plant growth cycle, shorelines6. Top-of-canopy (1st return) Digital Surface Model (DSM)7. More detailed LAS classification for vegetation, buildings8. Hydro enforced and/or hydro conditioned DEMs9. Single-line hydro feature breaklines; other breaklines10. Building footprints with elevations/heights11. Additional data products such as contours
  64. 64. Generating Contours from LiDAR Contours are producedNot aesthetically pleasing from LiDAR mass points and breaklines
  65. 65. ASPRS’ “DEM Users Manual”1. Intro to DEMs, 3-D Surface Modeling, Tides2. Vertical Datums3. Accuracy Standards4. National Elevation Dataset5. Photogrammetry6. IFSAR7. Topographic & Terrestrial Lidar8. Airborne Lidar Bathymetry9. Sonar10. Enabling Technologies11. DEM User Applications12. DEM Quality Assessment13. DEM User Requirements14. Lidar Processing & Software15. Sample Elevation Datasets
  66. 66. Final Report for NEEA Study available atwww.dewberry.comhttp://www.dewberry.com/Consultants/GeospatialMapping/FinalReport-NationalEnhancedElevationAssessment
  67. 67. THANK YOU Josh Novac Project Manager Remote Sensing Services Line Dewberry (Tampa, FL) jnovac@dewberry.com Ph: 813.421.8632