UAV applications for oil spill detection, suspended matter distribution and ice monitoring first tests and trials in Estonia 2015/2016

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UAV applications for oil spill detection, suspended matter distribution and ice monitoring first tests and trials in Estonia 2015/2016 Sander Rikka Marine Systems Institute at TUT 1.11.2016 1

Outlook Introduction Oil spill detection Drone operations Sensors Suspended matter distribution Waves Ice monitoring Drones Summary 2

Introduction - drone DJI Inspire 1 Flight time 10 20 min RGB camera (RAW+jpg) Wind resistance 10 m/s Temperature range -10 C to 40 C Relativly cost effective Different camera/gimbal systems and sensors available 3

Introduction - drone Total flight time over 100h since August 2015 Total flight distance over 400 km Great variability of weather conditions and locations Minimum temp approx. -24 C Maximum wind speed approx. 15 m/s Maximum altitude 500 m above sea level Operations carried out mostly from shore, but also include small rowboat and research vessels Operations both above open water and ice covered sea 4

Oil spill detection Visual camera sensor not perfect for oil spill detection - Difficult to distinguish oil from the background - Sun glint - Wind sheen - Sea weeds - Cannot operate at night - No methods to ensure the positive detection + Useful for documentation + Cheap and widely available + Easy to operate - The angle of the light - Seasonal differences - Reflections from waves and surface - Flight height - Wind, rain, snow etc 5

Oil spill detection Drone photo from above, viewing remaining of the main engine of MS VOLARE wreck, arrows point on detectable oil slicks originating from the wreck Near shore pollution as registered by UAV camera 6

MS Volare 7

MS Volare wreck after the salvage 8

Sensors Visual sensors airborne and satellite Infrared and thermal infrared sensors Probably the most applicable sensor to different types of UAVs Fluorosensors Good pontential SAR Many positive sides Lidar 9

Sensors Hyper-spectral + Large spectral coverage = lot of information - Not applicable to every type of UAVs Usage of filter to have different spectral bans Lightweight Saves image location Takes approx. 10 s to capture the image 10

Sensors airborne fluorosensor (LDI Innovation) Heavy Maximum detection height approx. 10m Information from single point = underwater buoy stations 11

Sesnors Lidar (LDI Innovation) Very heavy Single point measurements Gives specific parameters of oil 12

Other activities 13

Suspended matter distribution 14

Suspended matter distribution 15

Suspended matter distribution 16

River runoff 17

Ship maneuvering 18

Pixel DN value Reflectance (RAMSES) Pixel DN value Reflectance (RAMSES) Pixel DN value Reflectance (RAMSES) Field tests RGB spectrum Inspire 1 pixel values are compared with RAMSES (Radiation Measurements with Enhanced Spectral resolution) measurements Four diferent ground types were measured sand, peat, grass and soil (not presented here) RGB values from aircraft are in good agreement with same values from RAMSES instrument in terms of shape 200 150 100 50 Sand 0-5 300 400 500 600 700 800 900 1000 Wavelength (nm) Aircraft Ramses Ramses all Peat 150 5 4 100 3 50 2 1 0 0 300 400 500 600 700 800 900 1000 Wavelength (nm) Aircraft Ramses Ramses All 15 10 5 0 Grass 200 50 150 40 100 30 20 50 10 0 0 300 400 500 600 700 800 900 1000 Wavelength (nm) Aircraft Ramses Ramses All 19

Waves As known, waves are important aspect of oil spill behavior Wavelength estimations quite straightforward Wave height estimation is extremly demanding, but possible 20

Wave height from camera image Extremly demanding task UAV attitude (roll, pitch, yaw) and altitude, camera orientation must be known UAV should able to fly around 1h over the wave buoy Gamma corrections made by camera not known Illumination of the scene A sky panorama is needed Complete cloud cover or completely clear sky needed Atmospheric conditions must be known Measured 2D spectra from a wave buoy 21

Ice monitoring Mostly used for determing whether there is ice or not validation against SAR imagery Lots and lots of images of ice and its formations in different locations and conditions Monitoring of ice breaking activities 22

SAR image over the GoR 23

Ice classification map 24

SAR image over Väinameri 25

Ice classification map 26

Drones Fixed wings Great flight distances Great coverage Can carry many sensors Real time information might not be available Wave height analysis not available Takeoff and landing might be problematic Multirotor Able to measure at certain location Can carry many sensors Battery life Bad flight time Not that good area coverage 27

Summary Current technology has been very successful Lot of experiences in many situations Proves its usability Not at its full potential yet Ideal solution would include different types of drones Different sensors at the same time (fixed wings UAV) Specific sensor (multirotor) to measure specific parameters of oilspill and waves Great software-wise control over drones 28

Thanks for your attention 29

And of coarse, drones are good for photo- and videography 30