Processing LiDAR data: Fusion tutorial

Transcription

1 Processing LiDAR data: Fusion tutorial Douglas Bolton Rory Tooke Nicholas Coops University of British Columbia

2 Tutorial Objectives Open/Visualize LiDAR data in Fusion Derive surface products (2 m) - Digital elevation model (DEM) - Digital surface model (DSM) - Canopy height model (CHM) Extract LiDAR data for polygons and plots - Calculate LiDAR metrics for plots Calculate gridded LiDAR metrics - Apply existing models in ArcGIS to derive biomass, volume, etc. from gridded metrics Learn to work with multiple LiDAR tiles 2

3 LiDAR data used in this tutorial Discrete return LiDAR data collected in 2010 over the Malcolm Knapp Research Forest - Collected by McElhanney Consulting Services Ltd using a ALS50-II Leica system - Average of 3.1 pulses/m 2 - Multiple returns per pulse - Aerial photos were collected on the same flight Malcolm Knapp Research Forest - UBC Research Forest - Located in the Coast Western Hemlock biogeoclimatic subzone near Maple Ridge, BC 3

4 Tutorial Objectives Open/Visualize LiDAR data in Fusion Derive surface products (2 m) - Digital elevation model (DEM) - Digital surface model (DSM) - Canopy height model (CHM) Extract LiDAR data for polygons and plots - Calculate LiDAR metrics for plots Calculate gridded LiDAR metrics - Apply existing models in ArcGIS to derive biomass, volume, etc. from gridded metrics Learn to work with multiple LiDAR tiles 4

5 Digital Elevation Model (DEM) Step 1: Extract probable ground returns (Groundfilter) Step 2: Create surface from ground returns (GridSurfaceCreate) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 5

6 Digital Surface Model (DSM) Create a digital surface model (CanopyModel) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 6 6

7 Digital Surface Model (DSM) Create a digital surface model (CanopyModel) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 7 7

8 Digital Surface Model (DSM) Create a digital surface model (CanopyModel) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 8 8

9 Digital Surface Model (DSM) Visualization for Malcolm Knapp Research Forest Create a digital surface model (CanopyModel) 9

10 Digital Surface Model (DSM) Create a digital surface model (CanopyModel) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 10

11 Canopy Height Model (CHM) Point elevation Surface elevation Height (m) Point height above surface Lidar visualizations produced with FUSION/LDA software USDA Forest Service 11

12 Canopy Height Model (CHM) Height (m) m 35.9 m 34.4 m 35.6 m 40.7 m 34.8 m Lidar visualizations produced with FUSION/LDA software USDA Forest Service 12

13 Plot level analysis Lidar Point Cloud for Alex Fraser Research Forest Extract LiDAR data for plots (Clipdata) Lidar visualizations produced with FUSION/LDA software USDA Forest Service 13

14 Plot level analysis Lidar Point Cloud for Alex Fraser Research Forest Extract LiDAR data for plots (Clipdata) 14

15 Height (m) Calculating Lidar metrics Calculate Cover Metrics % 16% Cover Above 2 m Calculate metrics (Cloudmetrics) 5 0 High Volume Site Low Volume Site 15

16 Height (m) Calculating Lidar metrics Calculate Height Metrics m 15.6 m Mean Height Calculate metrics (Cloudmetrics) 5 0 High Volume Site Low Volume Site 16

17 Height (m) Calculating Lidar metrics Calculate Height Metrics m 21 m 75 th Percentile Calculate metrics (Cloudmetrics) 5 0 High Volume Site Low Volume Site 17

18 Height (m) Calculating Lidar metrics Calculate Height Metrics m 29 m 95 th Percentile Calculate metrics (Cloudmetrics) 5 0 High Volume Site Low Volume Site 18

19 Height (m) Calculating Lidar metrics Coefficient of Variation Measure of the structural diversity m 0.50 m 10 Calculate metrics (Cloudmetrics) 5 0 High Volume Site Low Volume Site 19

20 Plot Level Analysis Lidar Metrics 75 th height percentile 95 th height percentile Mean Standard deviation Coefficient of variation Cover above 2 meters Linear model Forest Attributes Gross Stem Volume Basal Area Mean height Dominant height Loreys height Wood biomass Bark biomass Stem biomass Foliage biomass Branches biomass Crown biomass Total above-ground biomass Forest Attribute = exp(b 0 + b 1 ln(x 1 ) + b 2 ln(x 2 ) b n ln(x n ) 20

21 Calculating Gross Stem Volume Step 1: Calculate gridded metrics Step 2: Apply Statistical model 21

22 Example model to apply Model form we often use: Attribute = exp(b 0 + b 1 ln(x 1 ) + b 2 ln(x 2 ) + b n ln(x n )) X BCF Model to derive net volume (m 3 /ha) for Malcolm Knapp Net Volume = exp( ( * Ln("Elevation_P95.asc")) + ( * Ln("Elevation_Cover_at_2m.asc"))) *