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GIS in the Rockies                          presentsIntroduction to LiDAR                                                 ...
Presenter Bio       Bruce Adey, GISP       • LiDAR/Photogrammetry Discipline Lead         (GeoSpatial Solutions, Merrick &...
Presenter Bio       Mark Stucky, GISP       •       MARS® Technical Support Specialist               Senior GIS Analyst (G...
Corporate Overview          Corporate headquarters: Aurora, Colorado          Founded in 1955; employee-owned          ...
Office Locations            Aurora, CO          (Headquarters)                                                         Ott...
Workshop Agenda                                      Workshop                  Objectives                                ...
Workshop Objectives          • Provide an objective and practical review of project               requirements and technic...
LiDAR Technology OverviewPREXXXX 8Copyright © 2010 Merrick & Company All rights reserved.
What is LiDAR?        LiDAR      (Light Detection And Ranging) is an active            optical technology that uses pulse...
LiDAR Data AcquisitionPREXXXX 10Copyright © 2010 Merrick & Company All rights reserved.
Laser Scan Patterns  Elliptical Pattern   Rotating Optical Pattern   Sinusoidal Pattern   Saw Tooth Pattern  Used by the A...
LiDAR Return Display                                   First Returns          Second Returns                              ...
Profile View            Cross-section view of trees, rendered by return valuesPREXXXX 13Copyright © 2010 Merrick & Company...
Advantages of LiDAR         Accessibility:     LiDAR is a non-intrusive method to              collect data in areas of l...
Advantages of LiDAR          Multiple    Collection Platforms: LiDAR can be collected              from fixed-wing aircra...
Challenges of LiDAR            Data     density increasing rapidly! Data volumes                 growing exponentially!! ...
Common LiDAR Misconceptions           LiDAR is a raster data product.             False – LiDAR refers to a randomly dis...
Data Acquisition PlatformsPREXXXX 18Copyright © 2010 Merrick & Company All rights reserved.
Data Acquisition PlatformsPREXXXX 19Copyright © 2010 Merrick & Company All rights reserved.
Airborne SystemsFixed Wing    Typical Altitude: 3,000’ – 12,000’ feet / 1,000 – 4,000 meters (AGL)    Mainly used for la...
Airborne LiDAR – Fixed-WingPREXXXX 21Copyright © 2010 Merrick & Company All rights reserved.
Airborne LiDAR - HelicopterPREXXXX 22Copyright © 2010 Merrick & Company All rights reserved.
Data Differences – Higher LiDAR Density       Fixed-Wing LiDAR Example                           Helicopter LiDAR Example ...
Mobile LiDAR – Road CorridorPREXXXX 24Copyright © 2010 Merrick & Company All rights reserved.
Terrestrial LiDAR – Electric SubstationPREXXXX 25Copyright © 2010 Merrick & Company All rights reserved.
LiDAR ApplicationsPREXXXX 26Copyright © 2010 Merrick & Company All rights reserved.
Floodplain Mapping / Inundation ModelingPREXXXX 27Copyright © 2010 Merrick & Company All rights reserved.                 ...
Water Resources Modeling  Sediment plume in wetlands from the creek, can’t see this from imagery orPREXXXX 28 remotely der...
Watershed Delineation                         Streams (blue)                        Catchments (red)
Transmission Line MappingPREXXXX 30Copyright © 2010 Merrick & Company All rights reserved.
Utility Vegetation ManagementPREXXXX 31Copyright © 2010 Merrick & Company All rights reserved.
Transportation - RailroadPREXXXX 32Copyright © 2010 Merrick & Company All rights reserved.                                ...
Land Cover ClassificationPREXXXX 33Copyright © 2010 Merrick & Company All rights reserved.
Land & Commercial DevelopmentPREXXXX 34Copyright © 2010 Merrick & Company All rights reserved.
InfrastructurePREXXXX 35Copyright © 2010 Merrick & Company All rights reserved.
Historic Preservation / Urban Planning
Geologic Mapping – Karst Study
3D Visualization - Planning
…More Applications…!!!                       Homeland                           Security                       Disaster ...
Data Processing WorkflowPREXXXX 40Copyright © 2010 Merrick & Company All rights reserved.
Raw LiDAR LiDAR  is collected in a proprietary format, based on the sensor’s manufacturer. This data is typically referre...
Post-Processing Coverage      Check     Identifies data voids and verifies that LiDAR dataset covers the entire      pro...
LAS File Format The LAS file format is an open, public file format for the interchange of 3D point cloud data between use...
Which LAS File Format?        The    LAS file format and Point Data Record Format            determine what information c...
LAS File (Header) Properties
LAS Point Properties
LiDAR Classification (aka Filtering)                     LiDAR data classification is a filtering process                 ...
ASPRS LiDAR Data Classifications*                   Classification Code                                Class              ...
Point Cloud Classification          The    LiDAR data classification value is the only point              cloud attribute...
Project Data DeliverablesPREXXXX 50Copyright © 2010 Merrick & Company All rights reserved.
Project Data Deliverables                     Raw,                   boresighted LiDAR (organized by flight line)        ...
Derivative Surface Models         DSM                                                 DTM                                 ...
Breaklines Definition:            Linear vector features that describe an abrupt change in the elevation of the terrain w...
Breaklines - Waterbodies
Elevation Contours (Topography)
15 minute Break
LiDAR Data DemonstrationPREXXXX 57Copyright © 2010 Merrick & Company All rights reserved.
Project Planning                                                          (Airborne)PREXXXX 58Copyright © 2010 Merrick & C...
Project Objective?            Understanding & communicating the project objective            allows the vendor to properly...
Project Specifications LiDAR    - Ground Sample Distance (GSD)    Average distance between LiDAR points on the ground  ...
Point Density vs. Point Spacing                      Point Density = 1 / Point Spacing2                                   ...
Flight Plan Example   LiDAR / Ortho Collection Parameters              131.13 square miles              34 flight lines;...
PREXXXX 63Copyright © 2010 Merrick & Company All rights reserved.                                                         ...
‘Forgotten’ Project Issues        Data                  Quality Control (QC)              Who is responsible for verifyi...
‘Forgotten’ Project Issues        Human                         Resources                  End-user training - clients s...
Other Challenges            Optimal      weather conditions necessary for data                 collection            Lea...
Keys to a Successful Project Understand your mapping requirements and the purpose for completing a LiDAR project. Utiliz...
Keys to a Successful Project Dedicate the appropriate number of internal resources to the project. Know exactly how the ...
Keys to a Successful Project Hybrid accuracy standards should only be used as long as there is very detailed metadata and...
Factors that Affect Price        Size                 of Project Area                  Area-of-Interest (AOI) size      ...
Factors that Affect Price           Weather                             / Flying Conditions                      Air tra...
Factors that Affect Price           Project                        Data Deliverables / Delivery Schedule           Map  ...
LiDAR Quality ControlPREXXXX 73Copyright © 2010 Merrick & Company All rights reserved.
QC Introduction          Many      automated steps and mechanical devices              that can cause systematic error   ...
QC Recommendations        Require     a QC plan & a report as part of the project            deliverables!       A     w...
True or False?PREXXXX 76Copyright © 2010 Merrick & Company All rights reserved.
Quality vs. Cost?         Poor quality data is often the trade-off to push the price         down                    Data...
Quality vs. Cost?                    Some vendors “cheat” to get around proper calibration and                     other ...
Potential Sources of Error        Planning              Incorrect project boundary (missing buffer)              Wrong h...
Potential Sources of Error        During the Mission              Electrical problem or equipment failure (ground-based o...
Visual QC ApproachesPREXXXX 81Copyright © 2010 Merrick & Company All rights reserved.
Flight Line Information   • Flight line info allows for a quality control check to be performed in overlap areas   • If a ...
Other Visual QC Methods          Viewing                             LiDAR points by classification values          Over...
Visual Hillshade Analysis (Ground)          Allows     users to visually inspect the ground classification for           ...
Visual Analysis - Profile View                                            Profile of Ground & Vegetation Classes          ...
Quantitative QC ApproachesPREXXXX 86Copyright © 2010 Merrick & Company All rights reserved.
LAS File Statistics       A simple method to analyze LiDAR data deliverables       is to review the statistics of the poin...
Control Report        To    verify compliance to the project’s vertical accuracy            specification, vendors compar...
USGS-NGP LiDAR Base Specification                    Version 1.0PREXXXX 89Copyright © 2010 Merrick & Company All rights re...
Purpose and Scope        USGS:      “The U.S. Geological Survey (USGS)            intends to use this specification to ac...
USGS LiDAR Specification        “Unlike most other “lidar data procurement specifications”,            which are focused ...
Collection Requirements                          Returns                         (minimum of three)                      ...
Data Processing & Handling Requirements                                LAS                      Format (v1.2 or v1.3)    ...
Data Processing & Handling Requirements                                  Point                  Families (return informat...
Hydro-Flattening                                                   Visual only – no automated testing yet                L...
Other StandardsPREXXXX 96Copyright © 2010 Merrick & Company All rights reserved.
Industry Accuracy Standards          Guidelines    for Digital Elevation Data (released by the              NDEP (Nationa...
Industry Accuracy Standards          The     USGS (United States Geologic Survey) publishes              an accuracy stan...
Questions?
Contact Information Bruce   Adey, GISP         LiDAR/Photogrammetry Discipline Lead    E-mail:   bruce.adey@merrick.com ...
Online LiDAR Resources USGS-NGP          LiDAR Base Specification Version 1.0    http://pubs.usgs.gov/tm/11b4/TM11-B4.pdf...
Online LiDAR Resources International    LiDAR Mapping Forum (ILMF)    http://www.lidarmap.org   SPAR Point Group    http...
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2012 Workshop, Introduction to LiDAR Workshop, Bruce Adey and Mark Stucky (Merrick & Company)

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Transcript of "2012 Workshop, Introduction to LiDAR Workshop, Bruce Adey and Mark Stucky (Merrick & Company)"

  1. 1. GIS in the Rockies presentsIntroduction to LiDAR September 19, 2012 Engineering | Architecture | Design-Build | Surveying | GeoSpatial Solutions
  2. 2. Presenter Bio Bruce Adey, GISP • LiDAR/Photogrammetry Discipline Lead (GeoSpatial Solutions, Merrick & Company) • Geospatial professional since 1999  Professional experience includes working directly with Project Managers in developing schedules and budgets for current & future projects, supervising the production staff to ensure that the data collected and delivered meets or exceeds industry/client standards, and also technical support and development of MARS® software.PREXXXX 2Copyright © 2010 Merrick & Company All rights reserved.
  3. 3. Presenter Bio Mark Stucky, GISP • MARS® Technical Support Specialist Senior GIS Analyst (GeoSpatial Solutions, Merrick & Company) • Geospatial professional since 1990 • Professional experience includes MARS® software sales, licensing, design, testing, and technical support; ArcGIS geodatabase design, editing, and QC; extensive work with the FEMA DFIRM flood map modernization effortPREXXXX 3Copyright © 2010 Merrick & Company All rights reserved.
  4. 4. Corporate Overview  Corporate headquarters: Aurora, Colorado  Founded in 1955; employee-owned  $115M annual revenue (FY11)  ~ 500 employees at 10 national + 3 international offices  Market Focus  Energy  Security  Life Sciences  Infrastructure  Business Units  GeoSpatial Solutions Civil Engineering Solutions  Military / Gov’t Facilities Fuels & Energy  Science & Technology Nuclear Services & TechnologyPREXXXX 4Copyright © 2010 Merrick & Company All rights reserved.
  5. 5. Office Locations Aurora, CO (Headquarters) Ottawa, Canada Washington, DC Colorado Springs, CO Charlotte, NC Los Alamos, NM Oak Ridge, TN Duluth, GA Albuquerque, NM Atlanta, GA San Antonio, TX Guadalajara, Mexico (MAPA) Mexico City, Mexico (MAPA)PREXXXX 5Copyright © 2010 Merrick & Company All rights reserved.
  6. 6. Workshop Agenda  Workshop Objectives  LiDAR Technology Review  LiDAR Applications  Data Processing Workflow  Project Data Deliverables  <<< 15 minute Break >>>  LiDAR Data Demonstration  Project Planning (Airborne)  LiDAR QC Q &A  Online ResourcesPREXXXX 6Copyright © 2010 Merrick & Company All rights reserved.
  7. 7. Workshop Objectives • Provide an objective and practical review of project requirements and technical information regarding airborne LiDAR data acquisition projects • Educate, communicate and evangelize the benefits of airborne remote sensing, especially as it pertains to LiDAR and the practical applications of laser scanning technologies • Informal conversation  feel free to ask questions!PREXXXX 7Copyright © 2010 Merrick & Company All rights reserved.
  8. 8. LiDAR Technology OverviewPREXXXX 8Copyright © 2010 Merrick & Company All rights reserved.
  9. 9. What is LiDAR?  LiDAR (Light Detection And Ranging) is an active optical technology that uses pulses of laser light to strike the surface of the earth and measure the time of each pulse return to derive an accurate elevation.  LiDAR data acquisition system includes: • LiDAR sensor • Digital camera(s) • Airborne GPS • IMU (Inertial Measurement Unit) • Power Supply / Data Storage • Pilot / Flight OperatorPREXXXX 9Copyright © 2010 Merrick & Company All rights reserved.
  10. 10. LiDAR Data AcquisitionPREXXXX 10Copyright © 2010 Merrick & Company All rights reserved.
  11. 11. Laser Scan Patterns Elliptical Pattern Rotating Optical Pattern Sinusoidal Pattern Saw Tooth Pattern Used by the AHAB Used by Riegl / TopoSys Used by Leica Used by OptechDragonEye and TopEye• Advantages and disadvantages with each scan pattern (ex. data uniformity, power consumption, duplicate points, accuracy along edge, field of view, etc.)• Some LiDAR data will look different, based on the sensor
  12. 12. LiDAR Return Display First Returns Second Returns Third Returns Fourth ReturnsPREXXXX 12Copyright © 2010 Merrick & Company All rights reserved.
  13. 13. Profile View Cross-section view of trees, rendered by return valuesPREXXXX 13Copyright © 2010 Merrick & Company All rights reserved.
  14. 14. Advantages of LiDAR  Accessibility: LiDAR is a non-intrusive method to collect data in areas of limited, risky, or prohibited access  Day or Night: LiDAR data collection not limited to daylight hours  Collection Area: Large areas may be collected in a short timeframe (ex. 300 – 500 square miles per lift)  Simultaneous Collection: Shortens overall project schedules and reduces post-processing rectificationPREXXXX 14Copyright © 2010 Merrick & Company All rights reserved.
  15. 15. Advantages of LiDAR  Multiple Collection Platforms: LiDAR can be collected from fixed-wing aircraft, helicopter, unmanned aerial vehicle (UAV), truck, train, tripod, etc.  Canopy Penetration: LiDAR can penetrate vegetation canopy to derive ground detail better than traditional photogrammetric approaches  Better Accuracy: LiDAR accuracy is much better in vegetation compared to traditional photogrammetric methods; ±10 cm horizontal, ±15 cm verticalPREXXXX 15Copyright © 2010 Merrick & Company All rights reserved.
  16. 16. Challenges of LiDAR  Data density increasing rapidly! Data volumes growing exponentially!!  Optimal weather conditions necessary for data collection  Large point cloud data sets are cumbersome to store, manage, analyze and distribute  Water / snow typically absorbs or scatters laser pulsesPREXXXX 16Copyright © 2010 Merrick & Company All rights reserved.
  17. 17. Common LiDAR Misconceptions  LiDAR is a raster data product.  False – LiDAR refers to a randomly distributed point cloud data set  First return points are always canopy or last return points are always ground.  False – First and last returns can either be ground or canopy  ‘Middle’ return information is unnecessary.  False – Client should require that all returns (1 – 4) are present within LiDAR data deliverables (raw and classified)  LiDAR ≠ GIS  users Should Not (and cannot in most software) add, delete, or move LiDAR points!PREXXXX 17Copyright © 2010 Merrick & Company All rights reserved.
  18. 18. Data Acquisition PlatformsPREXXXX 18Copyright © 2010 Merrick & Company All rights reserved.
  19. 19. Data Acquisition PlatformsPREXXXX 19Copyright © 2010 Merrick & Company All rights reserved.
  20. 20. Airborne SystemsFixed Wing  Typical Altitude: 3,000’ – 12,000’ feet / 1,000 – 4,000 meters (AGL)  Mainly used for large, wide-area collections  1 – 8 points per square meter  Common to collect LiDAR & digital imagery simultaneouslyRotary (Helicopter)  Typical Altitude: 500’ – 2,500’ feet / 200 – 1,000 meters (AGL)  Well-suited for narrow corridors (ex. utility, transportation) and small area, high-density collections  10 – 1,000+ points per square meter!  System may include digital cameras, video camera, meteorological sensors, thermal sensors, etc.
  21. 21. Airborne LiDAR – Fixed-WingPREXXXX 21Copyright © 2010 Merrick & Company All rights reserved.
  22. 22. Airborne LiDAR - HelicopterPREXXXX 22Copyright © 2010 Merrick & Company All rights reserved.
  23. 23. Data Differences – Higher LiDAR Density Fixed-Wing LiDAR Example Helicopter LiDAR Example Approx. 1 - 2 points / square meter Approx. 20 - 30 points / square meterPREXXXX 23Copyright © 2010 Merrick & Company All rights reserved.
  24. 24. Mobile LiDAR – Road CorridorPREXXXX 24Copyright © 2010 Merrick & Company All rights reserved.
  25. 25. Terrestrial LiDAR – Electric SubstationPREXXXX 25Copyright © 2010 Merrick & Company All rights reserved.
  26. 26. LiDAR ApplicationsPREXXXX 26Copyright © 2010 Merrick & Company All rights reserved.
  27. 27. Floodplain Mapping / Inundation ModelingPREXXXX 27Copyright © 2010 Merrick & Company All rights reserved. © 2010 URISA
  28. 28. Water Resources Modeling Sediment plume in wetlands from the creek, can’t see this from imagery orPREXXXX 28 remotely derived elevation sources, heavy vegetation in the area otherCopyright © 2010 Merrick & Company All rights reserved.
  29. 29. Watershed Delineation Streams (blue) Catchments (red)
  30. 30. Transmission Line MappingPREXXXX 30Copyright © 2010 Merrick & Company All rights reserved.
  31. 31. Utility Vegetation ManagementPREXXXX 31Copyright © 2010 Merrick & Company All rights reserved.
  32. 32. Transportation - RailroadPREXXXX 32Copyright © 2010 Merrick & Company All rights reserved. © 2010 URISA
  33. 33. Land Cover ClassificationPREXXXX 33Copyright © 2010 Merrick & Company All rights reserved.
  34. 34. Land & Commercial DevelopmentPREXXXX 34Copyright © 2010 Merrick & Company All rights reserved.
  35. 35. InfrastructurePREXXXX 35Copyright © 2010 Merrick & Company All rights reserved.
  36. 36. Historic Preservation / Urban Planning
  37. 37. Geologic Mapping – Karst Study
  38. 38. 3D Visualization - Planning
  39. 39. …More Applications…!!!  Homeland Security  Disaster / Emergency Preparedness & Response  Pipeline Mapping  Forensic Investigations  Conservation Management  Mining  Levee Recertification  Airfield Obstructions (Approach / Take-off)  Vegetation Mapping  ArchaeologyPREXXXX 39Copyright © 2010 Merrick & Company All rights reserved.
  40. 40. Data Processing WorkflowPREXXXX 40Copyright © 2010 Merrick & Company All rights reserved.
  41. 41. Raw LiDAR LiDAR is collected in a proprietary format, based on the sensor’s manufacturer. This data is typically referred to as “raw” (unprocessed) LiDAR point cloud data. Sensormanufacturers have their own post-processing software that combines raw scan data with GPS (position) data and IMU (orientation) data to produce a georeferenced LiDAR file (LAS). Atthis point, the point cloud data is “dumb” – no data classifications have been assigned; typically organized by individual flight lines
  42. 42. Post-Processing Coverage Check  Identifies data voids and verifies that LiDAR dataset covers the entire project extent Generate LAS files from hardware vendor’s post-processing software (i.e. merge GPS, IMU and LiDAR sensor inputs based on time) Validate & adjust relative accuracy of adjacent flight lines  Adjust flight line data for roll bias and/or other data collection issues Shift entire LiDAR point cloud to match ground control points
  43. 43. LAS File Format The LAS file format is an open, public file format for the interchange of 3D point cloud data between users (as defined by ASPRS) Developed by ASPRS in conjunction with LiDAR vendors and industry members of the ASPRS Standards Committee Binary format (smaller); high performance (faster) http://www.asprs.org/society/committees/standards/LiDAR_ exchange_format.html
  44. 44. Which LAS File Format?  The LAS file format and Point Data Record Format determine what information can be stored at the file level and point level (e.g.; GPS time, RGB info, waveform data)  Includes all relevant LiDAR attributes  classification, intensity, return info, timestamp, flightline info, RGB values, etc.  LAS Versions 1.0, 1.1, 1.2, 1.3, 1.4, 2.0 (under review)PREXXXX 44Copyright © 2010 Merrick & Company All rights reserved.
  45. 45. LAS File (Header) Properties
  46. 46. LAS Point Properties
  47. 47. LiDAR Classification (aka Filtering) LiDAR data classification is a filtering process by which raw laser data is organized into logical collections (i.e. data layers). The filtering process is based on the point’s attributes and geometric relationships of the laser data in the point cloud.PREXXXX 47Copyright © 2010 Merrick & Company All rights reserved.
  48. 48. ASPRS LiDAR Data Classifications* Classification Code Class 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 Keypoints 9 Water 10 Reserved for ASPRS Definition 11 Reserved for ASPRS Definition 12 Overlap Points 13 - 31 Reserved for ASPRS Definition *Source: LAS Specification, Version 1.2PREXXXX 48Copyright © 2010 Merrick & Company All rights reserved.
  49. 49. Point Cloud Classification  The LiDAR data classification value is the only point cloud attribute that can be modified  The number, name and description of the point cloud data classifications is project-specific and must be defined by the client  Typical data classifications include: 1 = Unclassified, 2 and/or 8 = Ground, 3/4/5 = Vegetation, 6 = Buildings, 7 = Low Points / Noise, 9 = Water, 13 = Superseded (junk)PREXXXX 49Copyright © 2010 Merrick & Company All rights reserved.
  50. 50. Project Data DeliverablesPREXXXX 50Copyright © 2010 Merrick & Company All rights reserved.
  51. 51. Project Data Deliverables  Raw, boresighted LiDAR (organized by flight line)  Classified, georeferenced, tiled LiDAR (LAS) data  Color Digital Orthophotography  Digital Elevation Model – DEM (grids)  Linear / polygonal breaklines (hydro-enforcement)  Digital Terrain Model – DTM  Elevation Contours (topography)  Tile Scheme  Control Report  Project Metadata (FGDC-compliant)  Project Summary ReportPREXXXX 51Copyright © 2010 Merrick & Company All rights reserved.
  52. 52. Derivative Surface Models DSM DTM DTM, showing DEM breaklinesPREXXXX 52Copyright © 2010 Merrick & Company All rights reserved.
  53. 53. Breaklines Definition: Linear vector features that describe an abrupt change in the elevation of the terrain which might affect contours, hydrology and other engineering models Natural breaklines (hard):  Ridge lines  Toe of hill  Edge of water body (ex. pond, lake) or stream Soft (man-made) breaklines:  Roads  Retaining Walls  Dams
  54. 54. Breaklines - Waterbodies
  55. 55. Elevation Contours (Topography)
  56. 56. 15 minute Break
  57. 57. LiDAR Data DemonstrationPREXXXX 57Copyright © 2010 Merrick & Company All rights reserved.
  58. 58. Project Planning (Airborne)PREXXXX 58Copyright © 2010 Merrick & Company All rights reserved.
  59. 59. Project Objective? Understanding & communicating the project objective allows the vendor to properly scope the data collection plan to meet stated project requirements!  What is the purpose of this project?  We need updated elevation data for new floodplain modeling program…  The county engineer requires updated terrain model for storm water / surface water runoff and hydrologic modeling…  The county assessor needs to update GIS system with more accurate elevation data and generate new 2’ contours for the cadastral system…PREXXXX 59Copyright © 2010 Merrick & Company All rights reserved.
  60. 60. Project Specifications LiDAR - Ground Sample Distance (GSD)  Average distance between LiDAR points on the ground  Can also be expressed in ‘points per square meter’ (PPSM)  Example: One (1) meter GSD to support generation of 2’ contours LiDAR - Vertical Accuracy  Absolute accuracy of LiDAR points to known ground surface  Example 1: ± One (1) foot vertical accuracy at 95% confidence  Example 2: Root Mean Squared Error (RMSEZ) = 0.60 foot = 7.2 inches Orthophotography (pixel resolution)  Example: One (1) foot orthophotos (typically georectified using LiDAR-derived surface model)
  61. 61. Point Density vs. Point Spacing Point Density = 1 / Point Spacing2 1 meter Point Spacing 1 meter 1 meter 1 meter Point Density = 1 point / sq. meter 2 meter Point Spacing 0.5 meter Point Spacing 0.5 meter 2 meters1 meter 2 meters 0.5 meter Point Density = 4 points / sq. meter Point Density = 0.25 points / sq. meter
  62. 62. Flight Plan Example LiDAR / Ortho Collection Parameters  131.13 square miles  34 flight lines; 389 flight miles  1 meter GSD  1’ foot color imagery  13,500’ MSL / 5,930’ AGL  34 flight lines; 2,516 photos  12 flight hours  18 photo control / control points  100 knot flight speedPREXXXX 62Copyright © 2010 Merrick & Company All rights reserved.
  63. 63. PREXXXX 63Copyright © 2010 Merrick & Company All rights reserved. © 2010 URISA
  64. 64. ‘Forgotten’ Project Issues  Data Quality Control (QC)  Who is responsible for verifying compliance to the project specifications?  How will QC be completed?  What tools are needed to perform comprehensive data QC?  Hardware Resources  Data Storage - clients must plan to receive, manage, distribute and store LiDAR, imagery, and other data deliverables Examples: Classified LAS – 400 MB / mile2 ESRI raster grid (2-foot cell size) - 7 MB / mile2  PC workstations – do users have the proper PC equipment to efficiently visualize, analyze, and process LiDAR deliverables?PREXXXX 64Copyright © 2010 Merrick & Company All rights reserved.
  65. 65. ‘Forgotten’ Project Issues  Human Resources  End-user training - clients should train & prepare employees on basic LiDAR concepts prior to data delivery  Clients should obtain necessary LiDAR viewing/processing software in advance to allow time for employees to learn to properly exploit the data  For first-time projects, expect some “ramp-up” time as with any new technology or softwarePREXXXX 65Copyright © 2010 Merrick & Company All rights reserved.
  66. 66. Other Challenges  Optimal weather conditions necessary for data collection  Leaf-off preferred for best ground penetration  Ground conditions - snow cover and standing water/saturated ground typically absorb or scatter laser pulses  Nearest secure airport with necessary services (ex. fuel)  Accessibility and safety for the crewPREXXXX 66Copyright © 2010 Merrick & Company All rights reserved.
  67. 67. Keys to a Successful Project Understand your mapping requirements and the purpose for completing a LiDAR project. Utilize a qualification-based selection process to select your LiDAR consultant. Stayaway from low price bid projects! Price-based selection causes some firms to cut corners (ex. offshore labor) to lower project cost. Hire a photogrammetric firm that owns a LiDAR sensor. Request a quality control plan.
  68. 68. Keys to a Successful Project Dedicate the appropriate number of internal resources to the project. Know exactly how the quality control is going to be performed by the consultant and internally. Understand the differences in LiDAR technology. The age of the sensor determines capabilities; pulse rate, roll compensation, field of view are unique to each system. Determinewhich accuracy specification is going to be adhered to (i.e. ASPRS, NDEP, etc.)
  69. 69. Keys to a Successful Project Hybrid accuracy standards should only be used as long as there is very detailed metadata and documentation that clearly explain the accuracy results. Do not exclude the ground truth surveying from a project. Request a LiDAR flight plan in the Request For Qualifications that clearly demonstrates the consultant’s understanding of the data acquisition issues.
  70. 70. Factors that Affect Price  Size of Project Area  Area-of-Interest (AOI) size  Very small areas (< 50 square miles) tend to be more expensive  Larger areas tend to cost less per square mile  AOI Shape – irregularly shaped AOIs may increase project cost  Equipment Mobilization (aka ‘mobe’)  Cost to move equipment & personnel to/from project area  Weather en route can cause delays  Vendors seek to ‘bundle’ work in same area to reduce mobilization feesPREXXXX 70Copyright © 2010 Merrick & Company All rights reserved.
  71. 71. Factors that Affect Price  Weather / Flying Conditions  Air traffic, inclement weather, dust, humidity affect ability to acquire airborne data  Platform Choice  Helicopter is much more expensive than fixed-wing  Project Specifications (ex. GSD, accuracy, etc.)  More aggressive specifications usually cost more to deliver  Greater overlap or cross flights may be needed (vegetation)PREXXXX 71Copyright © 2010 Merrick & Company All rights reserved.
  72. 72. Factors that Affect Price  Project Data Deliverables / Delivery Schedule  Map Accuracy Specifications  ASPRS, FEMA, USGS…….select one!  Accuracy reporting specifications  Example: USGS - Fundamental Vertical Accuracy (FVA)  Quality Control Process  Project & client specific – requires coordinationPREXXXX 72Copyright © 2010 Merrick & Company All rights reserved.
  73. 73. LiDAR Quality ControlPREXXXX 73Copyright © 2010 Merrick & Company All rights reserved.
  74. 74. QC Introduction  Many automated steps and mechanical devices that can cause systematic error  Good LiDAR companies understand both their procedures and equipment  Knowing sources of error can help prevent issues and check for them  Known mechanical / system error can often be correctedPREXXXX 74Copyright © 2010 Merrick & Company All rights reserved.
  75. 75. QC Recommendations  Require a QC plan & a report as part of the project deliverables! A well-written quality control plan must be tailored to properly analyze data deliverables, especially as it relates to meeting / exceeding the project objective and vertical accuracy specifications  QC analysis must be quantifiable and representative of the entire data set  Client / end-users must have sufficient technical knowledge to understand QC results (and how issues can be mitigated!)PREXXXX 75Copyright © 2010 Merrick & Company All rights reserved.
  76. 76. True or False?PREXXXX 76Copyright © 2010 Merrick & Company All rights reserved.
  77. 77. Quality vs. Cost? Poor quality data is often the trade-off to push the price down  Data providers vary the procedure, frequency, and extent of their LiDAR calibration  Less-skilled (cheaper) technicians and operators may not recognize when problems, failures, and errors occur  Often times, little or no documented QA / QC procedures to validate approach or allow for testing duplication  Vendor may not provide a summary report or ground control reportPREXXXX 77Copyright © 2010 Merrick & Company All rights reserved.
  78. 78. Quality vs. Cost?  Some vendors “cheat” to get around proper calibration and other QC tasks  Clipping off or reclassifying edge lap to avoid dealing with LiDAR boresight  Shifting tiles to a custom geoid (derived from the vertical error to ground control)  Some vendors can hide error through other creative techniques (especially if they discover problems after the plane has left the project site!!!)PREXXXX 78Copyright © 2010 Merrick & Company All rights reserved.
  79. 79. Potential Sources of Error Planning  Incorrect project boundary (missing buffer)  Wrong horizontal and/or vertical datum  Coordinate conversions & translations (ex. US foot vs. international survey foot)  GSD inadequate to meet accuracy expectations  Pulse rate not correct for desired flying altitude and vertical accuracy  Field of view too wide for adequate penetration in vegetation  Too small edge lap could cause data voids (missing data)PREXXXX 79Copyright © 2010 Merrick & Company All rights reserved.
  80. 80. Potential Sources of Error During the Mission  Electrical problem or equipment failure (ground-based or airborne)  System operator error  Pilot error (not following flight plan)  Weather and/or ground conditions Post-processing  Incorrect boresighting  Auto and manual classification (filtering)  Poor breakline compilationPREXXXX 80Copyright © 2010 Merrick & Company All rights reserved.
  81. 81. Visual QC ApproachesPREXXXX 81Copyright © 2010 Merrick & Company All rights reserved.
  82. 82. Flight Line Information • Flight line info allows for a quality control check to be performed in overlap areas • If a shift is detected within a flight line, this shift can be corrected if flight line information is present • You should request unique flight line information in your LiDAR dataset Unique flight line IDs. Flight line ID 4 Non-unique flight line IDs. Flight line ID (pink) is shifted +1 foot. Flight line ID 5 1 (green) is shifted +1 foot. Flight line ID (yellow) is not shifted. This data can be 1 (green) is not shifted. This data corrected. cannot be corrected.PREXXXX 82Copyright © 2010 Merrick & Company All rights reserved.
  83. 83. Other Visual QC Methods  Viewing LiDAR points by classification values  Overlaying contours generated by flight line  Comparing same X,Y location from adjacent flight lines ( Z or flight line separation)  Hillshade analysis of ground classifications – “pits” and “spikes”PREXXXX 83Copyright © 2010 Merrick & Company All rights reserved.
  84. 84. Visual Hillshade Analysis (Ground)  Allows users to visually inspect the ground classification for anomalies. Quickly identifies the effectiveness of bare-earth extraction capabilities of the vendor. Points rendered by data Hillshade image of classification the ground classPREXXXX 84Copyright © 2010 Merrick & Company All rights reserved.
  85. 85. Visual Analysis - Profile View Profile of Ground & Vegetation Classes Profile of Ground ClassPREXXXX 85Copyright © 2010 Merrick & Company All rights reserved.
  86. 86. Quantitative QC ApproachesPREXXXX 86Copyright © 2010 Merrick & Company All rights reserved.
  87. 87. LAS File Statistics A simple method to analyze LiDAR data deliverables is to review the statistics of the point cloud.  Zmin & Zmax  provide insight into data filtering results  Point Density  Average Ground Sample Distance (GSD)  Return Information (1st, 2nd, 3rd, etc.)  Data Classifications – has the data been classified into the specified classes?  Flightline information – is it present?  Statistics allow users to thematically map results in GIS applications, which can help identify “problem” areas, trends or data anomaliesPREXXXX 87Copyright © 2010 Merrick & Company All rights reserved.
  88. 88. Control Report  To verify compliance to the project’s vertical accuracy specification, vendors compare ground control “checkpoints” to the derived ground classification / surface  American Society of Photogrammetry and Remote Sensing (ASPRS), National Map Accuracy Standards (NMAS) and National Standard for Spatial Data Accuracy (NSSDA) maintain their own vertical accuracy specifications  Can also be used to report the attainable accuracy of contours generated from smoothed, gridded LiDAR dataPREXXXX 88Copyright © 2010 Merrick & Company All rights reserved.
  89. 89. USGS-NGP LiDAR Base Specification Version 1.0PREXXXX 89Copyright © 2010 Merrick & Company All rights reserved.
  90. 90. Purpose and Scope  USGS: “The U.S. Geological Survey (USGS) intends to use this specification to acquire and procure light detection and ranging (lidar) data, and to create consistency across all USGS National Geospatial Program (NGP) and partner funded lidar collections, in particular those undertaken in support of the National Elevation Dataset (NED).”  The USGS specification is the basis for most of the American Recovery and Reinvestment Act (ARRA, 2009) funded LiDAR projects in the U.S.; often used as a SOW document for many non-ARRA funded LiDAR projectsPREXXXX 90Copyright © 2010 Merrick & Company All rights reserved.
  91. 91. USGS LiDAR Specification  “Unlike most other “lidar data procurement specifications”, which are focused on the products derived from lidar point cloud data; such as the bare-earth Digital Elevation Model (DEM), this specification places unprecedented emphasis on the handling of the source lidar point cloud data.”  Defines minimum parameters for compliance; additional project upgrades listed (ex. increased vertical accuracy)  Specification divided into four (4) main sections:  Collection  Data Processing and Handling  Hydro-Flattening Requirements  Data DeliverablesPREXXXX 91Copyright © 2010 Merrick & Company All rights reserved.
  92. 92. Collection Requirements  Returns (minimum of three)  Intensity values  Point Density / Nominal Point Spacing (NPS)  Data Voids  Spatial Distribution Verification  Scan Angle  Vertical Accuracy  Relative Accuracy  Flightline Overlap  Collection Area (coverage check)  Collection Conditions (weather)PREXXXX 92Copyright © 2010 Merrick & Company All rights reserved.
  93. 93. Data Processing & Handling Requirements  LAS Format (v1.2 or v1.3)  Waveform Data (*.wdp auxiliary files)  GPS Time Type  Datums (horizontal & vertical)  Projections  Units of Measure  File Sizes  File Source ID (unique per swath)PREXXXX 93Copyright © 2010 Merrick & Company All rights reserved.
  94. 94. Data Processing & Handling Requirements  Point Families (return information)  Swath Coverage  Noise Classes & Withheld Points  Overlap Points  Positional Accuracy Validation  Classification Accuracy / Consistency  Tiles (orientation and overlap)PREXXXX 94Copyright © 2010 Merrick & Company All rights reserved.
  95. 95. Hydro-Flattening Visual only – no automated testing yet LiDAR only – no breaklines Hydro-Flattened defining water boundaries LiDARPREXXXX 95Copyright © 2010 Merrick & Company All rights reserved.
  96. 96. Other StandardsPREXXXX 96Copyright © 2010 Merrick & Company All rights reserved.
  97. 97. Industry Accuracy Standards  Guidelines for Digital Elevation Data (released by the NDEP (National Digital Elevation Program.) Guidelines are available online at http://www.ndep.gov/NDEP_Elevation_Guidelines_Ver1 _10May2004.pdf  ASPRS Guidelines Vertical Accuracy Reporting for LiDAR Data. Guidelines were subsequently adopted from NDEP, and are available online at http://www.asprs.org/society/committees/LIDAR/Downlo ads/Vertical_Accuracy_Reporting_for_LIDAR_Data.pdfPREXXXX 97Copyright © 2010 Merrick & Company All rights reserved.
  98. 98. Industry Accuracy Standards  The USGS (United States Geologic Survey) publishes an accuracy standard called the NMAS (National Map Accuracy Standard.) This document is available online at http://rockyweb.cr.usgs.gov/nmpstds/nmas.html  The FGDC (Federal Geographic Data Committee) is an interagency committee that created the NSSDA. This set of guidelines are available online at http://www.fgdc.gov/standardsPREXXXX 98Copyright © 2010 Merrick & Company All rights reserved.
  99. 99. Questions?
  100. 100. Contact Information Bruce Adey, GISP LiDAR/Photogrammetry Discipline Lead  E-mail: bruce.adey@merrick.com  Direct: (303) 353-3949 Mark A. Stucky, GISP MARS® Technical Support Specialist Senior GIS Analyst  E-mail: mark.stucky@merrick.com  Direct: (303) 353-3933 Thank You!
  101. 101. Online LiDAR Resources USGS-NGP LiDAR Base Specification Version 1.0 http://pubs.usgs.gov/tm/11b4/TM11-B4.pdf FEMA Guidelines and Specifications for Flood Hazard Mapping Partners http://www.fema.gov/plan/prevent/fhm/gs_main.shtm ASPRS LAS Specification http://www.asprs.org/society/committees/standards/lidar_exchange_f ormat.html USGS Center for LiDAR Information Coordination and Knowledge (CLICK) http://lidar.cr.usgs.gov/
  102. 102. Online LiDAR Resources International LiDAR Mapping Forum (ILMF) http://www.lidarmap.org SPAR Point Group http://www.sparpointgroup.com/ LiDAR News http://lidarnews.com/ National LIDAR Dataset (USA) http://en.wikipedia.org/wiki/National_LIDAR_Dataset_-_USA USGS National Elevation Dataset (NED) http://ned.usgs.gov/
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