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Integration of New Technologies and Tools for Forest Inventory and Assessment DEMO 2016 Nicholas Coops, Canada Research Chair in Remote Sensing Integrated Remote Sensing Studio: Forest Sciences Centre. 2424 Main Mall. University of British Columbia. Vancouver, BC., Canada V6T 1Z4
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What are some of the technologies relevant for forest inventory and assessment today ?
Enhanced Forest Inventories Use of Airborne LiDAR Technology Photogrammetric Point Clouds New Data Streams New Platforms UAV / Drones
Enhanced Forest Inventories
• As covered by previous speakers enhanced inventories aim to provide accurate and spatially explicit understanding of – Timber Characteristics – Desired fiber attributes – Capacity to separate trees for particular end uses.
• Many forest inventories across the country are more than 20 years old, and were not designed to optimize each link in the forest value chain.
• Some conventional tools and methods are simply unable to support today’s needs for accuracy, spatial detail and timely updates.
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Data for Enhanced Forest Inventories
• Light Detection And Ranging
• Active form of remote sensing
• Measures the distance to target surfaces using narrow beams of near-infrared light
• Primarily operated on airborne platforms for forestry applications
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TRIM II DEM (25 m)
2,0001,5001,0005000
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LiDAR DEM (1 m)
2,0001,5001,0005000
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Ortho Image
Wet Areas Mapping
LIDAR Digital Terrain Model
Wet Areas Mapping
Locations of expected water bodies (predicted streams.
Wet Areas Mapping
Cartographic Depth to Water (wet areas)
Wet Areas Mapping
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Stream segments and gradient
• Segments represent stream parts that have a homogenous gradient
• They are created by finding the break points in the longitudinal profiles of stream elevation data
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Stream width and class
• Stream width was determined by expanding stream lines into areas of homogenous elevation using object based image analysis tools
• Accessibility for fish and derived stream width were used to assign stream class, using the official guidelines for British Columbia
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Accessibility for fish
• Based on stream gradient at a distance of 100 m or more (shorter segments excluded)
• Based on stream network – segments of high gradient are treated as barriers
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Hinton Forest Management Area
• Hinton Wood Products, West Fraser Mills • ~1 million ha; est. 1951
• Pure coniferous: 80% by area • Lodgepole pine: 65% by volume
Data: • Lidar: ~1 point/m2
• 735 ground calibration plots
Enhanced forest inventory (2011): • Predict Attributes:
• Height (top, mean, 75th) • QMD, BA • Volume (merchantable, total) • Biomass (total)
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Validation: Volume
• Weight-scaled volume from 272 cut blocks harvested since LiDAR acquisition
• Compared volume estimates from EFI to
Cover Type Volume Table (CVT) estimates • CVT underestimated volume by an average
of 19.8% and EFI overestimated volume by 0.6%
16 Canadian Wood Fiber Centre / CFS / UBC
Northern Vancouver Island
• ~120,000 ha of LiDAR
• Cooperative acquisition between BC Timber Sales (BCTS) and Western Forest Products
• Highly productive, temperate rainforest dominated by western hemlock
• Lidar: 11.6 points/m2
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Augmenting productivity estimates
• Stand dominant height calculated based on ALS data
• Revised site index value was generated
• Calculated projected stand volume at 80 years
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Time series of satellite imagery Airborne laser scanning
Stand age Dominant height
Chronosequence
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Developing productivity models
Reference age = 32 years
• Estimating site productivity for young stands
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Downscaling Plot Volume to Individual Tree Lists
• Additional information on individual tree volume extracted for every cell
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Uptake
• British Columbia – NVI – BCTS and WFP (~120,000 ha)
– Island Timberlands (~255,000 ha)
– Alex Fraser Research Forest (~3,487 ha)
– Okanagan – BCTS and Tolko (450,000 ha)
– East Quesnel TSA (~490,000 ha)
– Scheldt Community Forest
– Cross-border sharing of expertise WA
– FPInnovations developing business case for lidar
• Alberta – Hinton (~1 Mha)
– Grande Prairie (1.2 Mha)
– Spray Lakes (~0.5 Mha)
– Lidar for all forest lands
– Wet Areas Mapping (WAM); many companies are now using this product
– Structural metrics to inform biodiversity
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Photogrammetric Point Clouds / Digital Aerial Photogrammetry
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• Facilitated by high forward overlap (60 - 80%) • Requires an accurate DEM. Which can be an issue. • LIDAR at Time 1 and DAP at time 2.
• High resolution images with ~80% overlap
• Conjugate pixels stitched
• Pixels combined in three dimensional space
• Point cloud product
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Digital Aerial Photogrammetry
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Comparing model outcomes: LiDAR vs. Digital Photogrammetry
• LiDAR performs better, but differences in RMSE are not statistically significant
• DAP is not producing biased outcomes, relative to LIDAR
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27 Updating residual stem volume estimates using ALS- and UAV-acquired stereo-photogrammetric point clouds. Goodbody et al., (2016) International Journal of Remote Sensing. doi: 10.1080/01431161.2016.1219425
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AWARE Assessment of Wood Attributes using Remote sEnsing
5 year, $3M Industrial / University / Government Research Program
Co-investigators on project here in:
• Michael Wulder
• Joanne White
• Piotr Tompalski
• Tristan Goodbody
• Christop Stepper
• Barry White / Chris Bater
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Nicholas Coops, nicholas.coops@ubc.ca Canada Research Chair in Remote Sensing Integrated Remote Sensing Studio: Forest Sciences Centre. 2424 Main Mall. University of British Columbia. Vancouver, BC., Canada V6T 1Z4
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