a uas for plantation forestry research in...
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A UAS for plantation forestry research in NZAuthors:
Jonathan Dash, Marie Heaphy, Toby Stovold, Michael Watt, Brian Clement, Bryan Graham
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Overview
1. NZ forest industry
2. Where do UAS fit in
3. Scion’s UAS programme
4. A few case studies
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• ~ 2 million ha
• ~ 600,000 ha post-1990
• 93% in private ownership
• Majority FSC certified
• 89% Pinus radiata
• 28 year rotation
New Zealand’s third largest export earner:
$4.5 billion (2012).
Plantation Forestry in New Zealand
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High Productivity and Intensively Managed
High productivity mean MAI = 30 m3ha-1y-1
Intensive forest management practices
needed to achieve this:
– Site preparation
– Genetically improved tree stocks
– Competition control
– Forest health monitoring
– Intensive measurement
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Scion – New Zealand Forest Research Institute, Rotorua
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Where do UAS fit in to plantation forest management?
Monitoring wilding conifers
Fire monitoring (hotspots)
Health Monitoring
Forest inventory
Event monitoring
(wind / harvesting)
Health & safety
Increased frequency and improved resolution remote sensing-data
We require cost effective data acquisition and analytics.
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Scion’s UAV fleet
Bot– Payload = 1 kg
– Long flight endurance ~ 40
minutes
– Quick and easy deployment.
– Used for imaging / video
“Sci-fly”– Large UAV (10 kg)
– Modified Aeronavics Falcon XL
– Larger payload (2.5 kg+)
– Increased stability
– Laser scanning / spraying
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Training and Certification
Flight training and H&S systems developed
CAA rules limit UAV flight parameters in NZ
Scion have achieved certification under Part
102 of the CAA Act.
This provides the possibility of
– Flights above 120 m;
– Flying beyond line of sight;
– Aerial chemical application.
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Routescene LidarPod
Intergrated RTK GNSS and INS.
Velodyne HDL-32e scanner:32 laser / detector pairs905 nm wavelength700,000 pulses per second2 returns per pulse
Max. range = 100 m, Weight = 2.5 kg.
Onboard solid state storage.
Routescene Ground Station;Transmits RTK corrections to the LidarPod.Downloads quality assurance information.
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MicaSense RedEdge 3
5 narrow band multi-spectral camera
Blue, Green Red, Red-edge, NIR
1 capture per second (all bands) 12-bit RAW
Weight 150 g
GSD = 8.2 cm (per band) at 120 m
Image calibration by imaging a reflectance panel (empirical line
method).
Downwelling light sensor to monitor ambient light changes
during flights. Stored in file metadata
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Our datasets - High density Lidar data
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Our datasets - Multi-spectral imagery
Mature P. radiata canopy Wilding conifers in alpine tussock
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Our datasets - Image-based point clouds
Point cloud derived from
dense overlapping imagery
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A few case studies
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A time-series dataset for monitoring disease expression –
Study design
Simulate a disease outbreak by invoking changes in
foliar colour and needle retention.
Trees poisoned in different sized clusters (0, 1, 2, 4,
8, 16) with 5 replicates.
Regular (weekly) monitoring from the ground
(conventional tree health scoring) and from a UAV.
LAI measurements using LiCOR 2200.
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A time-series dataset for monitoring disease expression –
Early results
Lidar CHM with delineated tree crowns
mNDVI
Before the study Last week
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Can we monitor fire fuel load and predict fire behaviour in
wilding conifers?
Wilding conifers present an
additional fuel source in areas of high
ecological value.
No understanding of fire behaviour in
these areas.
Coupling UAV data with destructive
field sampling could provide a
solution.
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Using UAS data to parametrise a fire behaviour model for
wilding conifers
Laser scanning
Multispectral imagery
Biomass & Structure
Moisture content
Fire fuel load Fire behaviour model
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We monitored a controlled burn of the wilding conifers to
validate model predictions
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Concluding comments
UAVs have tremendous potential for the plantation forest
industry.
There is a very wide range of applications requiring
research & development.
Scion have a UAS programme in place to deliver tools to
help the industry take advantage of this emerging
technology.
Initial developments have been encouraging.
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www.scionresearch.com
www.gcff.nz
Jonathan Dash
Scientist, Geomatics
Thank you…