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Lidar Data Applications for Natural Resource Management Tom Bobbe, Mark Finco, Ken Brewer, Denise Laes USDA Forest Service Remote Sensing Applications.

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Presentation on theme: "Lidar Data Applications for Natural Resource Management Tom Bobbe, Mark Finco, Ken Brewer, Denise Laes USDA Forest Service Remote Sensing Applications."— Presentation transcript:

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 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 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-m 2 to 1 per 4-m 2 (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). 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-m 2 to 1 per 4-m 2 (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 / m 2 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 dont work Require special pre-processing for analysis Point data, but … Large volume of data Assume: 1 to 4 pulses / m 2 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 dont work Require special pre-processing for analysis

5 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 Points Colored by Height Highest Lowest

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

7 Primary Application – High Resolution DTM

8 10-m DEM / 1-m Lidar DTM Comparison New and important features are recognizable on the 1-meter digital terrain model (micro-hydrologic patterns, roads / trails, and other man-made features) USGS 10-meter Digital Elevation Model (DEM) Lidar-derived 1-m Digital Terrain Model (DTM) Site A Site B Site A 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 DTMs 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 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… 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 Vegetation information starts with DTMs Raw lidar returns (Colored by height) DTM All returns normalized by the DTM Raw lidar returns (Colored by height) DTM All returns normalized by the DTM

15 USFS PNWs FUSION Software Individual Tree Measurements

16 Lidar and ground measurements relationships Dominant height (r 2 = 0.98) Figures Courtesy of PNW Seattle Laboratory 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 … 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 …

17 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

18 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 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 Government Vendor Specs QA / QC

19 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) 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)

20 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 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

21 Approximate Costs of Acquisition 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 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 Mobilization $8k – $15k Administration Project and flight planning Weather contingency Pre-collection tasks Mobilization $8k – $15k Administration Project and flight planning Weather contingency Pre-collection tasks Advanced Processing Additional $3 – $7/acre Canopy cover Tree height Forest biomass Other vegetation derivatives Advanced Processing Additional $3 – $7/acre Canopy cover Tree height Forest biomass Other vegetation derivatives

22 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 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


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