An Introduction to Lidar & Forestry May 2013

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1 An Introduction to Lidar & Forestry May 2013

2 Introduction to Lidar & Forestry Lidar technology Derivatives from point clouds Applied to forestry Publish & Share Futures

3 Lidar Light Detection And Ranging

4 Different Types of Lidar Atmospheric Lidar Bathymetric: Senses up to 50 meters deep BUT requires clear water! Terrestrial: Tripod mounted or mobile Airborne Laser Scanner (ALS)

5 Lidar Light Detection And Ranging Similar in concept to Radar & Sonar Measures distances (through laser pulses) that strike and reflect off of features on the surface of the earth Converts scanning angle and distance-fromsensor information into georeferenced data points Current sensors can collect hundreds of thousands of positions each second ( point clouds )

6 energy or echoes of light

7 ALS - Lidar Systems

8 Airborne Lidar System Components Scanning laser emitter-receiver unit Differentially-corrected GPS in the plane pitch roll IMU yaw Inertial measurement unit (IMU) Computer to control the system and store data z GPS y X Imagery often collected simultaneously Color and/or Color Infrared Imagery

9 Lidar Characteristics

10 Lidar Data Characteristics A Return is a portion of the Lidar pulse that is reflected back to the sensor Most laser systems can record several returns or multiple returns for each pulse - Multiple returns occur when the laser beam is only partially blocked - The remaining laser energy continues downward until it is reflected back by the next feature Up to 4 returns per pulse, but typically only receive 2-3 returns

11 Lidar Data Characteristics Lidar point classification

12 1st Return (Canopy Ht) Intermediate Return Intermediate Return Last Return (Ground)

13 Lidar Data Characteristics 1 st returns (69%)

14 Lidar Data Characteristics 2 nd returns (26%)

15 Lidar Data Characteristics 3 rd returns (4%)

16 Lidar Data Characteristics 4 th returns (<0.1%)

17 Lidar Data Characteristics All returns (100%)

18 Lidar Data Characteristics All returns (100%) 1 st returns (69%) 2 nd returns (26%) 3 rd returns (4%) 4 th returns (<0.1%)

19 Lidar Data Characteristics Lidar Data Resolution (PPM) The only consistent measure of Lidar data resolution (when considering the full point cloud) is the number of pulses per unit area or Pulse Density (pulses/m2). Return density can vary depending on the target being scanned.

20 Lidar Data Characteristics Lidar Data Resolution (PPM) is dependent on: Laser scan rate (more same speed higher resolution) Flying height and speed (higher or faster lower resolution) Side-lap coverage (e.g. 50% side-lap will result in 2x resolution)

21 1 Meter 1 Meter

22 Lidar Pulse Density & Products $$ $$$ Low Pulse Density ( 1 Pulse/m 2 ) - Product: Moderate Resolution Topographic Products ( 2 meter Grid) Moderate Pulse Density (1-3 Pulses/m 2 ) - Products: Stand Level Vegetation Metrics (e.g. canopy height, canopy cover) and High Resolution Topographic Products High Pulse Density ( 3 Pulses/m 2 ) - Products: Forest Structure $$$$

23 Lidar Data Characteristics Spatial accuracies depend on: Slope (flat vs. steep) Ground cover (pavement vs. trees) Acquisition altitude Quality of instruments Capabilities of provider Best case: +/- 5cm vertical

24 Lidar Point Data True 3D Data!

25 Lidar Point Data True 3D Data!

26 Lidar Point Data Return data colored by height

27 LIDAR Intensity Image Copyright Optech Incorporated. All rights reserved.

28 Lidar Point Clouds to Derivatives

29 Our Sample Data Set 9 Tiles: N.W. Montana, U.S. Collected 2009 PPM: +/ million points Approximately 1,600 acres/650ha Almost 1GB NAIP Aerial Photography Collected meter per pixel Data Thanks Go To Montana State Library & NRIS for making the dataset available and the acquiring organizations including: Montana DNRC, Lake County, the Flathead Basin Commission, and the City of Whitefish.

30 Lidar Point Clouds to Derivatives Digital Elevation Model (DEM) Bare Earth (DTM) Contours Can also be viewed in 3D Lidar Point Cloud to Derivatives

31 Digital Surface Model DSM

32 Lidar Point Clouds to Derivatives Digital Surface Model (DSM)

33 Lidar Point Clouds to Derivatives Canopy Height Model (CHM) After generating the 1st return (DSM) and bare earth (DEM) rasters, use the Minus geoprocessing tool to determine the difference The difference represents the canopy height.

34 Lidar Point Clouds to Derivatives Canopy Density Model (CDM) The ratio of all returns to ground returns as seen from the air Applications include the estimation of biomass, forest extent and condition, and biodiversity

35 Additional Derived Layers Slope Aspect Hydrography Stand Delineation Roads (historic, new design) Cultural features (i.e. buildings)

36 Lidar Applications for Forestry Topographical analysis Roads: Design and operations 3D viewshed analysis Quantify forest stand characteristics - Biomass estimates - Fire fuel modeling Landslide analysis Change over time

37 Roads: Evaluation & Design Creating Profile Transects: - Assess construction complexities - Quickly identify areas of concern due to slope Calculating Road Slope - Create road vector (2D or 3D) - Use existing 2D road vectors Mapping Side Slope Risk - Identify locations where upslope (rock, mud, snow slides) or downhill hazards may exist

38 Roads: Creating Profile Transects Use ArcMap to digitize proposed routes and quickly assess any issues relating to slope Easily done with existing 2D road vectors

39 Roads: Calculating Road Slope Display based on maximum road segment slope

40 Viewshed Analysis The Goal: View the proposed cutblocks from multiple observation positions to determine potential visual impacts

41 Roads: Viewshed Analysis Remove the vegetation within the proposed cutblock(s) Clip the surface values inside the cutblock polygon(s) from the DEM Replace the cells in the DSM with the values removed from the DEM. This modified DSM represents the resulting surface after completing harvest activities (assumes all trees within the cutblock are removed)

42 Viewshed Analysis Using the modified DSM, run the 3D Analyst tool Viewshed with a selected observer position.

43 The Output is a raster map Repeat from other observer positions Viewshed Analysis

44 3D Visualization Inspect the point cloud

45 3D Visualization Profile View & Measure

46 3D Visualization Measure & Inspect Individual Trees

47 Publish & Share Take your Lidar data into the field. Go mobile. Easy to do with derivative data sets. Leave your point clouds at home. Publish with ArcGIS Server Share with ArcGIS On-Line

48 Lidar Procurement Considerations What will the Lidar be used for? - Pulse density - Spatial accuracy - Laser sensor scan angle - Point cloud classification - Flight line overlap (i.e. 50%) Deliverables? Combine with high resolution imagery? Fused?

49 Futures Existing Lidar Technology - Faster pulse rates - Multiple sensors in one box New Lidar Technologies Better Feature Extraction Software - More automation - Improved results Change Detection (PC to PC)

50 Lidar For Forestry - Summary Airborne LIDAR is a tool that provides Foresters with: - Highly accurate topographical data - Forest stand information including canopy height and density - 3D visualization and measurements of the ground and land cover - A source of accurate GIS information, even in remote areas - A quantifiable and repeatable data source One flight = Many GIS data layers (derivatives)

51 Acknowledgements U.S.D.A. Forest Service Pacific Northwest Research Station - Bob McGaughey and Steve Reutebuch U.S.D.A. Forest Service Remote Sensing Applications Center (RSAC) - Brent Mitchell Optech Incorporated

52

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