Lidar Data Applications for Natural Resource Management

1. Lidar Data Applications for Natural Resource Management Tom Bobbe, Mark Finco, Ken Brewer, Denise Laes USDA Forest Service Remote Sensing Applications Center Salt Lake City, Utah Geospatial 2007 Conference Thursday - May 10, 2007

2. Presentation Outline • Lidar system fundamentals • Resource management applications • Digital Terrain Models • Vegetation Models • Lidar applications in the Forest Service • Lidar acquisition specifications

3. Fundamentals of Lidar Lidar Basics: • Lidar = Light Detection And Ranging • Scanning Infrared Laser Rangefinder • 80-150 thousand pulses per second result in typical point densities between 8 per 1-m2 to 1 per 4-m2 (called post spacing) • Multiple returns from a single pulse are possible • Coupled with IMU/GPS provides very accurate X,Y,Z point clouds (~15-cm in Z).

4. Characteristics of Lidar Data • Point data, but … • Large volume of data • Assume: 1 to 4 pulses / m2 • Assume: 2 returns per pulse • Assume: 6 values per return • Equals: 0.38 – 1.52 GB per acre, or 3.71 – 14.84 TB per 10,000 acres • Because of data volume • Often standard GIS analyses don’t work • Require special pre-processing for analysis

5. Points Colored by Height Highest Lowest Examples of Lidar Point Clouds This lidar point cloud transect crosses a forest road In this 3-D perspective of a lidar point cloud note the buildings

6. 1st Return 2nd Return 3rd Return 4th Return All Returns Multiple return lidar • Multiple return lidar contributes to forest structure measurements • 1st return is not just top of canopy • Last (4th) return is not just the ground • First analytical step typically filters ground returns from all returns Figures Courtesy of PNW Seattle Laboratory

7. Primary Application – High Resolution DTM

8. 10-m DEM / 1-m Lidar DTM Comparison USGS 10-meter Digital Elevation Model (DEM) Lidar-derived 1-m Digital Terrain Model (DTM) New and important features are recognizable on the 1-meter digital terrain model (micro-hydrologic patterns, roads / trails, and other man-made features) Site A Site A Site B Site B

9. Comparison Areas USGS 10-meter Digital Elevation Model (DEM) Lidar-derived 1-m Digital Terrain Model (DTM) Site A Site B

10. DTM’s are just the beginning however … Tools are being developed in the Forest Service and commercial sector to extract information about the vegetation • Individual Tree Measurements(potentially height, crown base height, crown diameter depending on crown spacing) • Canopy Height, Cover, Density • Vegetation Structural Characteristics

11. Fusion Software • Developed by USDA Forest Service Pacific Northwest (PNW) Research Station (McCaughey, Reutebuch & Andersen) • Originally intended for PNW internal use • RSAC agreed to distribute and provide support for FS users • Capabilities include: • View lidar data quickly and easily • Handles almost any format of lidar data • Creates surfaces (bare earth models (DTMs), canopy surface models) • QA/QC of vendor-processed data • Easily measures heights of features • Large number of forestry-related measurements • And much more…

12. Fusion Tutorial

13. Lidar Tutorial

14. USFS PNW’s FUSION Software Individual Tree Measurements

15. Lidar and ground measurements relationships • Strong relationships with ground measured variables • Height, Basal Area, Volume, Crown Bulk Density, etc. • Relationships verified by numerous researchers • McGaughy, Reutebuch & Andersen (USFS PNW) • Hudak and Evans (USFS RMRS) • Lefsky (Colorado State) • Evans (Mississippi State) • Wynne (Virginia Tech) • Popescu (Texas A&M) • Naesset (Norway) • Many others … Dominant height (r 2 = 0.98) Figures Courtesy of PNW Seattle Laboratory

16. Lidar Applications in the USFS • Recent tally of lidar applications in the USFS(Lachowski and Reutebuch) • More detail and full report at http://fsweb.rsac.fs.fed.us/documents/0073-RPT2.pdf

17. Government Specs QA / QC Vendor Lidar Mission Specifications • Wide lidar usage (in resource mapping) is just in its infancy • Like aerial photos – specifications are linked to information requirements • Currently no industry standards for specific applications • 2 Areas to specify • Acquisition specs • Processing and Delivery specs

18. Lidar Specifications – Acquisition Acquisition Specifications • Point density (post spacing) • DTM -> based on vertical accuracy requirements • Vegetation Applications • 1.5 point per square meter absolute minimum • 4-6 points per square meter are preferable • Specify whether collected leaf on or leaf off • Multiple returns per pulse • Maximum 15-degree off nadir scan angle unfiltered data • Flight lines should have 50% “side lap” (30% minimum) • Cross flights for calibration • Attributes delivered: X, Y, Z, Intensity, Scan Angle, Return # • High resolution digital imagery (if possible)

19. Lidar Specifications – Processing and Delivery Vendor Processing and Delivery Specifications • Lidar data delivered in overlapping tiles • GIS dataset of the tiling system • GIS dataset of the flight lines • Report on GPS ground station locations • Geographic projection information (including vertical datum) • Heights should be orthometric heights • Report that lists all files delivered • Optional: • Tiled points filtered for bare earth returns • A high resolution DTM

20. Approximate Costs of Acquisition Mobilization • $8k – $15k • Administration • Project and flight planning • Weather contingency • Pre-collection tasks Basic Data Collection and Post-processing • Depends on study area size ($0.50 -$2.50/acre for 1M – 15k acres) • ~$1/acre for a 250K acre project • Raw lidar data • Bare earth • First surface Advanced Processing • Additional $3 – $7/acre • Canopy cover • Tree height • Forest biomass • Other vegetation derivatives

21. Summary • Lidar is an exciting (relatively) new technology • Provides measurements! • Vegetation structural information are its strengths • Existing research provides a strong foundation • Lidar processing requires special skills/tools • Data volume can be an issue • Specialized software (not just ESRI products) required for efficient large scale analysis • Lidar missions • Specifications becoming better understood • Still expensive, but costs coming down • Multiple resource applications & consortia allow for cost sharing