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      Adapting open-source drone autopilots for real-time iceberg observations

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          Abstract

          Drone autopilots are naturally suited for real-time iceberg tracking as they measure position and orientation (pitch, roll, and heading) and they transmit these data to a ground station. We powered an ArduPilot Mega (APM) 2.6 with a 5V 11 Ah lithium ion battery (a smartphone power bank), placed the APM and battery in a waterproof sportsman’s box, and tossed the box and its contents by hand onto an 80 m-long iceberg from an 8 m boat. The data stream could be viewed on a laptop, which greatly enhanced safety while collecting conductivity/temperature/depth (CTD) profiles from the small boat in the iceberg’s vicinity. The 10 s position data allowed us to compute the distance of each CTD profile to the iceberg, which is necessary to determine if a given CTD profile was collected within the iceberg’s meltwater plume. The APM position data greatly reduced position uncertainty when compared to 5 min position data obtained from a Spot Trace unit. The APM functioned for over 10 h without depleting the battery. We describe the specific hardware used and the software settings necessary to use the APM as a real-time iceberg tracker. Furthermore, the methods described here apply to all Ardupilot-compatible autopilots. Given the low cost ($90) and ease of use, drone autopilots like the APM should be included as another tool for studying iceberg motion and for enhancing safety of marine operations.

          • Commercial off-the-shelf iceberg trackers are typically configured to record positions over relatively long intervals (months to years) and are not well-suited for short-term (hours to few days), high-frequency monitoring

          • Drone autopilots are cheap and provide high-frequency (>1 Hz) and real-time information about iceberg drift and orientation

          • Drone autopilots and ground control software can be easily adapted to studies of iceberg-ocean interactions and operational iceberg management

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          Most cited references38

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          Unmanned aerial systems for photogrammetry and remote sensing: A review

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            Coastal and Environmental Remote Sensing from Unmanned Aerial Vehicles: An Overview

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              PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision

                Author and article information

                Contributors
                Journal
                MethodsX
                MethodsX
                MethodsX
                Elsevier
                2215-0161
                06 September 2018
                2018
                06 September 2018
                : 5
                : 1059-1072
                Affiliations
                [a ]Arctic Research Centre, Department of Bioscience, Aarhus University, 8000 Aarhus C, Denmark
                [b ]Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL 32306, USA
                [c ]Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
                Author notes
                [* ]Corresponding author at: Arctic Research Centre, Department of Bioscience, Aarhus University, 8000 Aarhus C, Denmark. danfcarlson@ 123456bios.au.dk
                Article
                S2215-0161(18)30145-6
                10.1016/j.mex.2018.09.003
                6139390
                a241d318-de48-4930-933a-302e8bfb2506
                © 2018 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 24 April 2018
                : 3 September 2018
                Categories
                Earth and Planetary Science

                low-cost,real-time iceberg drift and orientation observations,iceberg tracking,iceberg drift and orientation,operational iceberg management,drone autopilot,iceberg-ocean interaction

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