Environmental Remote Sensing by Drone Laboratory

The TED Lab combines the benefits of remote sensing (quality and quantity of information) with the flexibility of drones. In doing so, it enables researchers to collect new, otherwise inaccessible data respecting:

• Spectral characteristics: broad spectral range, higher spectral resolution
• Temporal characteristics: frequent and timely deployment
• Spatial characteristics: Adjustable spatial scope and resolution depending on requirements, ability to fly over inaccessible areas

Lab equipment includes software, drones, sensors, and a mobile laboratory.

Software

• PIX4Dmapper Pro
• Geomatica
• ArcGIS
• RESONON Inc.
• Matlab
• Unscrumbler
• FME
• Ecognition
• Envisat

Drones

ALTIGATOR HYDRA-12

• 12-rotor multicopter
• Flight time
  • 30 min with no payload
  • 8 min with 12 kg payload
• Max. payload: 12 kg
• Max. weight at takeoff: 25 kg

ING RESPONDER

• Single-rotor helicopter
• Flight time: 20 min. with no payload
• Max. payload: 7 kg
• Max. weight at takeoff: 20 kg

OBSERVER-6 (several drones)

• 6-rotor multicopter
• Flight time
  • 20 min with no payload
  • 10-17 min depending on the batteries/payload
• Max. payload: 2 kg
• Max. weight at takeoff: 6 kg

ALTIGATOR ALG-EOS

• 4-rotor multicopter
• Training drone
• Flight time: 30 min with no payload

Sensors

LiDAR sensor – system under development, made up of:

Velodyne Puck

• Range: 100 m
• Wavelength: 905 nm
• Points/sec: 600,000
• Accuracy: +/- 3 cm

RGB camera: SONY A6000

• Resolution: 24 Mpx (6000 x 4000 pixels)

Hyperspectral cameras

RESONON PIKA II

• Spectral range: 400 – 900 nm
• Number of spectral channels: 240
• Focal length: 12 mm
• Spatial resolution @ 100 m = 6 cm
  Coverage @ 100 m = 40 m

RESONON PIKA NIR

• Spectral range: 900 – 1700 nm
• Number of spectral channels: 164
• Focal length: 25 mm
• Spatial resolution @ 100 m = 12 cm
• Coverage @ 100 m = 39 m

Spectrometers

• Ocean Optics USB2000+: Spectral range: 400 – 900 nm
• Ocean Optics NIRQuest: Spectral range: 900 – 1700 nm

Accessories for the proximal spectroscopy device

• Optical fiber
• Light source
• Calibration source
• Optical fiber
• Stand
• Spectralon

Multispectral cameras

TETRACAM MICRO-MCA6 SNAP

• Sensors (x6): 1.3 Mpx
• Focal length: 9 mm
• 12 visible bandwidth and near infrared filters
• Spatial resolution @100 m = 5 cm
• Coverage @ 100 m = 70 m

Parrot Sequoia

• 16 Mpx (4608 x 3456 pixel) RGB sensor
• 1.2 Mpx narrow band and synchronized sensors (x4: green, red, red-edge, and near infrared)
• Spatial resolution @ 100 m = 9.4 cm (RGB = 2.7 cm)
• Coverage @ 100 m = 120 m (RGB = 126 m)

RGB camera – SONY A6000

• Resolution: 24 Mpx (6000 x 4000 pixels)
• Focal length: 16 mm
• Spatial resolution @ 100 m = 2 cm
• Coverage @ 100 m = 130 m

Thermal infrared camera – Optris Pi 640

• Resolution: 0.3 Mpx (640 x 480 pixels)
• Temperature range: -20°C to 900°C
• Spectral range: 7.5 to 13 μm
• Spatial resolution @ 100 m = 9 cm
• Coverage @ 100 m = 60 m

Infrared thermometer – FLIR

• Temperature range: -30ºC to 650ºC
• Accuracy: ±1 ºC or 1% of the reading
• Resolution: 0.1ºC
• Thermocouple (accuracy: ±2ºC or 1% of the reading)

Benchtop hyperspectral imaging system

• Lighting system
• Mounting tower
• Mobile platform
• Data acquisition software
• Proximal acquisition lenses

Positioning system

Trimble 5800

• 2 RTK GPS dual-frequency receivers
• Pacific Crest radio transmitter
• Horizontal accuracy = 1 cm, vertical accuracy = 2 cm

Garmin, Magellan

• GPS receiver
• Code measurement
• Accurate to within 2 to 5 m

3D printer – Makerbot Replicator+

• Dimensions: 29.5 L x 19.5 W x 16.5 H (cm)
• Resolution: 100 microns

Weather station

Davis Vantage Pro2

• Variables measured: precipitation, wind, temperature, humidity, UV radiation

Campbell Scientific

• SR50A acoustic distance sensor
• CS230 temperature profiler

Miscellaneous

• Honda 2200 W inverter generator
• In-the-field computers
• Satellite telephone
• Avionic communication system
• Calibration cables for reflectance

Repair and storage shed – Mobile laboratory

The TED Lab also has a fully equipped trailer for work in the field. The trailer can serve as a command station when drones are in the air or as a laboratory, as needed. Because it has its own power supply, it can be up and running quickly and easily almost anywhere.

• Precision agriculture (fertilization, irrigation, erosion, plant protection)
• Aquatic ecosystem monitoring
• Water quality
• Habitat characterization
• Public safety (flooding, ice jams, spills)
• Geomorphology
• Invasive plant detection
• Mining
• Forestry
• Spectroscopy (soil, snow, minerals)
• Orthophotography and 3D modelling
• Satellite data simulations

Funding

The TED Lab was created in 2016 through grants from the Canada Foundation for Innovation and the Government of Quebec.

Partners

• Agriculture and Agri-Food Canada
• Agriculture, Pêcheries et Alimentation Québec
• Centre de géomatique du Québec
• Drone Experts
• Génidrone
• Research and Development Institute for the Agri-Environment
• Québec City
• Université de Sherbrooke

Recent and current projects

Development of a drone-embedded system for taking surface water samples

Funding: Natural Sciences and Engineering Research Council of Canada (NSERC)

Partner: DroneXperts

Risk assessment of metals determined using remote sensing of dissolved organic carbon ISK

Funding: International Copper Association (ICA), Natural Sciences and Engineering Research Council of Canada (NSERC)

DAVE ice jam monitoring and warning device (dispositif d’alerte et de vigilance pour les embâcles de glace)

Funding: Department of National Defence (Canada)

Past projects

Detection and monitoring of blue-green algae bloom (cyanobacteria) by remote sensing

Funding: Natural Sciences and Engineering Research Council of Canada (NSERC)

Hyperspectral remote sensing for environmental applications

Funding: Natural Sciences and Engineering Research Council of Canada (NSERC)

Automatic detection of the Colorado potato beetle using ultrahigh-resolution images from a drone

Funding: Patates Dolbec, MITACS

Intraseasonal management of nitrogenous potato fertilization using drones

Funding: Ministère de l’Agriculture, des Pêcheries et de l’Alimentation du Québec (MAPAQ)

Use of drone-based hyperspectral imaging to calibrate and validate an algorithm based on Sentinel-2 imaging to monitor freshwater algae blooms and/or cyanobacteria in southern Quebec

Funding: Canadian Space Agency (CSA)

Use of drone-based thermal imaging to monitor methane emissions at landfills

Funding: MITACS, Telops, Natural Sciences and Engineering Research Council of Canada (NSERC)

Study on the relationship between thermal imaging data collected by drone and agrometeorological indicators of water stress in potato crops

Funding: Research and Development Institute for the Agri-Environment (IRDA), MITACS