taming drones for forestry - cif-ifc · taming drones for forestry 1 ... no over-flight of persons...
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Denis Cormier, Research Manager
Udaya Vepakomma, Remote Sensing Scientist
Unmanned Aerial Vehicles and Unmanned Aerial Systems in the
Natural Resources Sector Workshop
Corner Brook, Nfld, 24 February , 2017
Taming Drones for Forestry
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Remote sensing niche
Validation trials
Taming implementation (workflow and post-
treatment automation for regeneration
assessments)
Taming costs
Untamed challenges
Outline
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A shoe for a tighter fit?
3 Time
Sca
le
Forest operations – Data needs
Operational
Strategic
Tactical
• Monitoring
• Control
• Decision
• Automation
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Drone / Unmanned aerial vehicle
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A new degree of freedom: Drone
5 5
Reso
luti
on
/ d
eta
ils
Unrestricted views
Forested area
Conifer stand
Regeneration
Inexpensive
Simple logistics - deployment
Quick turnaround
Centimetric imaging
Multi-view, variable altitudes
Live video streaming
Multiple sensors
Vehicles off the shelf
Overview – 120m
Nadir – 60m
Oblique -20m
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Dispersed small blocks
Varying and changing
conditions
Sampling vs census
Safety, inaccessibility
Time and cost inefficient
Data challenges
6 6
Roadside pile burning
Herbicide treatment
Regeneration assessment
Preharvest assessment Image interpretation Sample survey
Vis
ua
l A
rea
ba
se
d
De
taile
d
Post harvest assessment
Data needs
Conventional means
Visual assessment
Details Frequency, Coverage
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FPInnovations focus
• Niche (feasibility)
• Accuracy
• ROI
• Best practices
• New applications
• Partnership
7 http://donextension.e-monsite.com/
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Potential applications
Visual Inspections
• Live video feed on tablet/computer
Replace helicopter flyovers for inspection, compliance, control, prescription, hazard detection
Area Based
• From orthomosaic
Planimetric estimations
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Potential applications (2)
3-D Point Cloud Analysis
• Heights and volumetric estimations
Multi spectral
• Health, species
Thermal analysis (IR)
• Hot spots: wildfire; post slash piles burning; hogfuel piles
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3.5m
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Taming implementation – Workflow
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ROI
Applications
Planning
Flights
Post processing
Training
Permits
Validation trials
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Standard workflow - Planning
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• Environment
• Safety
• Accessibility
• …..
SFOC
Trial / Application Site selection
Vehicle /Sensors
Constraints
Prelim. plan Exemptions / Permission
Transport Canada
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Regulation
UAV Exemptions
Two (2) exemptions approved to permit lower-risk UAV operations without an SFOC
o 2kg or less has 37 conditions
o 2kg - 25kg has 58 conditions
SFOC
Applications evaluated on a case-by-case basis based on associated risks of the mission
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Examples of Safety Conditions
At least 5nm away from any aerodrome or built-up area
Below 300 feet
Daylight only
Only in Class G airspace (no forest fire, restricted airspace, air shows)
Maintain visual contact – No First Person View
Always give way to manned aircraft
Safe distances from people, buildings, vehicles etc.
No over-flight of persons
Weather limits
Notification requirements before flight
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FUTURE Regulatory approach
UAVs 25kgs or less, operated within visual line-of-sight
Define Categories
o Small – Complex
o Small – Limited
o Very Small
o Micro
SFOC process remains for operations not covered by the amendment (larger than 25kg, BVLOS, etc)
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Validation trials (application features)
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3D point cloud
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Unprecedented details
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Species classification
Canopy height
Height class
% T
ree
s p
er
sp
ecie
s
0 28 m
Image mosaic – 2.2 cm GSD
200 X 100m
Poplar Spruce Fir Tamarack
Pre-harvest assessment
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Quick turnaround
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Harvested block
Temporary bridge
Stream network
Disturbance : 15%
Disturbed area
Post-harvest assessment
20 ha
Altitude: 100 m; RGB images
Visual inspection – live streaming: 5 mins
HR image + mosaic: 2-3 hours
Image interpretation: 1 hour
Additional details
Slash pile
Height: 4m; Volume: 182.5m3
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Realistic 3D structure – visualisation
200
244 m
50 150 100 200 250 m
Harvested block
Log pile
Log pile
Regenerating stand
Hardwood stand
Height profile along a transect
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Accurate volumetric analysis
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C2A
C1A
3D model of a mill yard
Log piles Pile height Log stack volume
Mill inventory
0 6 m
Height : 13.2 m
Volume: 12 570 m3
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Stems of all height distinguishable
Ground Image DSM
Single stem identification
Single stem extraction Regular space 21.2 m
3 - 6 m 0.4 – 1.4 m
Tree height distribution
Irregular space
4 - 36 m
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Census not survey
Regeneration standards
Spruce
Pine 48 X 40 m Na
tura
l re
ge
ne
ration
Pla
nta
tion
20 X16 m
Stem density
Space occupancy
5000 5000 – 20,000 > 20,000 stems per ha
94 % stocked
Gap
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Situational awareness
Thermal IR Ground / Sol RGB
Mosaic - 85 images
300 cm2
In partial canopy – 120 m
Under full canopy – 120 m
Exposed - 120 m
Road side pile burn Hot spot detection
Altitude: 100 m; Area: 20 ha; IR scanning: 30 mins
Detection – in all directions Detection – up to 200 m
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Taming implementation Post-treatment automation
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3D point cloud
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Image size
Single image size:
Sunex (RGB) – JPEG 8 bit – 6.28 MB (32. 3 MB RAW)
(Acquired at nadir in a 22 ha. block at different altitudes)
Flying altitude (High to low)
Purple: Total Image size (MB)
Red: # of images
Green: Time of flight (min)
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Data processing (Photoscan, Pix4D)
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All images
Alignment
NFO (geotags)
Reference (Targets - GPS)
Image matching
Feature extraction
Bundle adjustment
Dense Point Cloud
DSM
DTM
Orthomosaics
Feature extraction
Height Volume Type
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Outputs – Photogrammetry
Orthomosaic
3D Point cloud
DSM
Time to process (hrs)
Workstation – 16 GB RAM + 8 core
Photoscan photogrammetry s/w
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Regeneration assessment
Ortho mosaic Conifer stand (Quesnel, BC)
Size: 19 ha
Display window: 5.3 ha
Age: 4 yrs since drag sip
3D rendering
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Regeneration assessment
Stocking Stocking
& Density
2500 100000 / ha
Stem – height
0.3 m
0.3 - 0.4
0.4 - 0.5
0.5 - 0.1
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Regeneration assessment
5000 5000 – 20,000 > 20,000
Extension to mixedwood stands
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Free-to-grow assessment 10 year old block
43 ha
1 ha
Ortho
CIR mosaic
Single trees
Species group Free-to-Grow
Model
Canopy height
4 m 5 m
1
2 3
4
Ground
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Regeneration assessment
Model
Free-to-Grow Single trees
Extension to larger spaces with high res. satellite
Pleiades – Multi spectral (2m) Pleiades – Panchromatic (50cm)
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• Reconnaissance and inspection
Visual flyovers
Harvesting inspections
Safety audits and hazards
identification
Live streaming for onsite feedback
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Taming costs
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3D point cloud • Detailed Costing Analysis
UAV Pilot and support crew
Machine (Platform) hourly rate based on
depreciation
Travel and preparation
Data handling and processing
Local and out-of-region
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Taming costs
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3D point cloud • Assumptions for Costing Analysis
Fixed wing and high-end VTOL UAVs for mapping and
3D model production (with 75% overlap)
More productive with fixed wing over larger area
Low-cost VTOL UAVs for reconnaissance and visual
inspection (video and images, no overlap needed)
Altitude 90m
Automated data treatment (i.e., unsupervised
processing time not included)
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Taming costs
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3D point cloud
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Taming costs
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3D point cloud
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Untamed challenges
Clear ROI is needed
Constraints related to regulations
Data management strategy
Automate post-processing
Service provider to avoid pilot issues and specialized data processing
Disruptive technology with huge unexplored potential
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