integration of new technologies and tools for forest ... · integration of new technologies and...
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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
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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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170
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LiDAR DEM (1 m)
2,0001,5001,0005000
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Ortho Image
Wet Areas Mapping
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LIDAR Digital Terrain Model
Wet Areas Mapping
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Locations of expected water bodies (predicted streams.
Wet Areas Mapping
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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
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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.
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• 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
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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, [email protected] 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