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Sensor-Carrying Platforms

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POLAR NIGHT Marine Ecology

Part of the book series: Advances in Polar Ecology ((AVPE,volume 4))

Abstract

Information and communication technology, autonomy, and miniaturization in terms of, for example, microelectromechanical systems are enabling technologies with significant impact on the development of sensors, sensor-carrying platforms, control systems, data gathering, storage, and analysis methods. Sensor-carrying platforms are grouped in stationary devices such as landers and moorings to dynamic platforms such as marine robotics, ships, aerial systems, and remote-sensing satellites from space. Lately, the development of low-cost small satellites with customized payload sensors and accessible mission control centers has opened for a democratization of the space for remote sensing as well. The mapping and monitoring strategy may be carried out by each type of sensor-carrying platform suitable for the mission. However, we see a quantum leap by operating heterogeneous sensor-carrying platforms for the most efficient mapping and monitoring in spatial and temporal scales. We are facing a paradigm shift in terms of resolution and coverage capabilities. There have been several research efforts to improve the technology and methodology for mapping and monitoring of the oceans. Today, we see that the mapping coverage may be 100–1000 times higher than the state-of-the-art technology 6 years ago. The entailed increase in data harvesting does also create new challenges in handling of big data sets. It is an increasing need to update the oceanographic and ecosystem numerical model capabilities, taking full benefit of the ongoing shift in technology. The Arctic can truly be characterized as a remote and harsh environment for scientific operations and even more demanding during the Polar Night due to the darkness. During winter operations, extreme coldness may also be a challenge dependent on the weather conditions. Enabling technology and proper operational procedures may be the only way to reveal and understand the processes taking place there. The spatial scale is enormous, and as several research campaigns have already taught us, the variability is huge not only during the seasons but also over the years. This clearly also tells us the importance of prolonged presence. In this chapter, we will briefly present the various sensor-carrying platforms and payload sensors. We will also describe the philosophy behind integrated operations using heterogenous platforms and why and how to bridge science and technology being successful in the development of autonomous systems for efficient and safe operations. Examples and experience from Arctic missions will also be presented.

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References

  • ASL (2016) AZFP (acoustic zooplankton fish profiler) operators manual. In: ASL environmental sciences

    Google Scholar 

  • Ballard RD (2008) Archaeological oceanography. Princeton University Press, US

    Google Scholar 

  • Bassett C, Weber TC, Wilson C, De Robertis A (2016) Potential for broadband acoustics to improve stock assessment surveys of midwater fishes. J Acoust Soc Am 140(4):3242–3243

    Article  Google Scholar 

  • Bellingham JG (2014) Have robot, will travel. Meth Oceanogr 10:5–20

    Article  Google Scholar 

  • Benoit D, Simard Y, Gagné J, Geoffroy M, Fortier L (2010) From polar night to midnight sun: photoperiod, seal predation, and the diel vertical migrations of polar cod (Boreogadus saida) under landfast ice in the Arctic Ocean. Polar Biol 33(11):1505–1520

    Article  Google Scholar 

  • Berge J, Cottier F, Last KS, Varpe Ø, Leu E, Søreide J, Eiane K, Falk-Petersen S, Willis K, Nygård H, Vogedes D (2009) Diel vertical migration of Arctic zooplankton during the polar night. Biol Lett 5(1):69–72

    Article  PubMed  Google Scholar 

  • Berge J, Båtnes AS, Johnsen G, Blackwell SM, Moline MA (2012) Bioluminescence in the high Arctic during the polar night. Mar Biol 159(1):231–237

    Article  CAS  PubMed  Google Scholar 

  • Bingham B, Foley B, Singh H, Camilli R, Delaporta K, Eustice R, Mallios A, Mindell D, Roman C, Sakellariou D (2010) Robotic tools for deep water archaeology: surveying an ancient shipwreck with an autonomous underwater vehicle. J Field Robot 27(6):702–717

    Article  Google Scholar 

  • Brighenti A (1990) Parametric analysis of the configuration of autonomous underwater vehicles. IEEE J Oceanic Eng 15(3):179–188

    Article  Google Scholar 

  • Chave R, Buermans J, Lemonm DD, Taylor CJ, Lembke C, DeCollibus C, Saba GK, Reiss C (2018) Adapting multi-frequency echo-sounders for operation on autonomous vehicles. In: MTS/IEEE Oceans. Charleston, USA pp 1–6

    Google Scholar 

  • Darnis G, Hobbs L, Geoffroy M, Grenvald JC, Renaud PE, Berge J, Cottier F, Kristiansen S, Daase ME, Søreide J, Wold A (2017) From polar night to midnight sun: diel vertical migration, metabolism and biogeochemical role of zooplankton in a high Arctic fjord (Kongsfjorden, Svalbard). Limnol Oceanogr 62(4):1586–1605

    Article  CAS  Google Scholar 

  • Deines KL (1999) Backscatter estimation using broadband acoustic Doppler current profilers. In: IEEE conference on current measurement (Cat. No. 99CH36331), pp 249–253

    Chapter  Google Scholar 

  • Doneus M, Doneus N, Briese C, Pregesbauer M, Mandlburger G, Verhoeven G (2013) Airborne laser bathymetry – detecting and recording submerged archaeological sites from the air. J Archaeol Sci 40(4):2136–2151

    Article  Google Scholar 

  • Dukan F, Sørensen AJ (2014) Sea floor geometry approximation and altitude control of ROVs. Contr Eng Pract (CEP) 29:135–146

    Article  Google Scholar 

  • Farmer GT, Cook J (2013) Climate change trends. In: Climate change science: a modern synthesis, vol 1. Springer, Dordrecht pp 97–133

    Google Scholar 

  • Fernandes DA, Sørensen AJ, Pettersen KY, Donha DC (2015) Output feedback motion control system for observation class ROVs based on a high-gain state observer: theoretical and experimental results. IFAC J Control Eng Pract (CEP) 39:90–102

    Article  Google Scholar 

  • Fossum TO, Eidsvik J, Ellingsen I, Alver MO, Fragoso GM, Johnsen G, Ludvigsen M, Rajan K (2018) Information-driven robotic sampling in the Coastal Ocean. J Field Robot 35(7):1101–1121

    Article  Google Scholar 

  • Fossum TO, Fragoso GM, Davies EJ, Ullgren JE, Mendes R, Johnsen G, Ellingsen I, Eidsvik J, Ludvigsen L, Rajan K (2019) Toward adaptive robotic sampling of phytoplankton in the coastal ocean. Sci Robot 4:eaav3041

    Article  PubMed  Google Scholar 

  • Gade K (2018) Inertial navigation – theory and applications. PhD thesis. Department of Engineering Cybernetics, NTNU

    Google Scholar 

  • Garcia EG, Ragnarsson S, Steingrimsson S, Nævestad D, Haraldsson H, Fosså J, Tendal O, Eiriksson H (2006) Bottom trawling and scallop dredging in the Arctic: impacts of fishing on non-target species, vulnerable habitats, and cultural heritage. Nordic Council of Ministers, Copenhagen

    Google Scholar 

  • Geoffroy M, Cottier FR, Berge J, Inall ME (2016) AUV-based acoustic observations of the distribution and patchiness of pelagic scattering layers during midnight sun. ICES J Mar Sci 74(9):2342–2353

    Article  Google Scholar 

  • Geoffroy M, Daase M, Cusa M, Darnis G, Graeve M, Hernandez NS, Berge J, Renaud PE, Cottier F, Falk-Petersen S (2019) Mesopelagic sound scattering layers of the high Arctic: seasonal variations in biomass, species assemblages, and trophic relationships. Frontiers in Marine Science 6:364. https://doi.org/10.3389/fmars.2019.00364

  • Hacquebord L (2001) Three centuries of whaling and walrus hunting in Svalbard and its impact on the Arctic ecosystem. Environ History 7(2):169–185

    Article  Google Scholar 

  • Hacquebord L (2010) Op walvisjacht naar Spitsbergen. Een hachelijke onderneming in de Noordelijke IJszee. Walburg Pers, pp 1774–1778

    Google Scholar 

  • Hagen PE, Hegrenæs Ø, Jalving B, Midtgaard Ø, Wiig M, Hagen OK (2009) Making AUVs truly autonomous underwater vehicles. In: Inzartsev AV (ed) Underwater vehicles. InTech, pp 129–152, ISBN 978–953-7619-49-7. Source: Underwater Vehicles, Book edited by: Alexander V. Inzartsev, ISBN 978-953-7619-49-7, pp. 582, December 2008, I-Tech, Vienna, Austria

    Google Scholar 

  • Hansen RE (2011) Introduction to synthetic aperture sonar. In: Kolev PN (ed) Sonar systems. Intechopen, Rijeka, pp 3–28

    Google Scholar 

  • Haury LR, McGowan JA, Wiebe PH (1978) Patterns and processes in the time-space scales of plankton distributions. In: Spatial pattern in plankton communities. Springer, Boston, pp 277–327

    Chapter  Google Scholar 

  • Johnsen G, Volent Z, Dierssen H, Pettersen R, Van Ardelan M, Søreide F, Fearns P, Ludvigsen M, Moline MA (2013) Underwater hyperspectral imagery to create biogeochemical maps of seafloor properties. Subsea optics and imaging, Edited by John Watson and Oliver Zielinski. A volume in Woodhead Publishing Series in Electronic and Optical Materials

    Google Scholar 

  • Johnsen G, Norli M, Moline MA, Robbins I, von Quillfeldt C, Sørensen K, Cottier F, Berge J (2018) The advective origin of an under-ice spring bloom in the Arctic Ocean using multiple observational platforms. Polar Biol 41:1197–1216. https://doi.org/10.1007/s00300-018-2278-5

    Article  PubMed  PubMed Central  Google Scholar 

  • Kimball P, Bailey J, Das S, Geyer R, Harrison T, Kunz C, Manganini K, Mankoff K, Samuelson K, Sayre-McCord T, Straneo F, Traykovski P, Singh H (2014) The WHOI Jetyak: an autonomous surface vehicle for oceanographic research in shallow or dangerous waters. 2014 IEEE/OES Autonomous Underwater Vehicles (AUV)

    Google Scholar 

  • Kinsey JC, Eustice RM, Whitcomb LL (2006) A survey of underwater vehicle navigation: recent advances and new challenges. In: Manoeuvering and control of marine craft. Lisbon, Portugal, pp 1–12

    Google Scholar 

  • Kintisch E (2016) Arctic shipworm discovery alarms archaeologists. Science 351(6276):901

    Article  CAS  PubMed  Google Scholar 

  • Korneliussen RJ, Berger L, Campanlla F, Chu D, Demer D, De Robertis A, Domokos R (2018) Acoustic target classification. ICES Cooperative Research Report No. 344. doi:https://doi.org/10.17895/ices.pub.4567

  • Kortsch S, Primicerio R, Beuchel F, Renaud PE, Rodrigues J, Lonne OJ, Gulliksen B (2012) Climate-driven regime shifts in Arctic marine benthos. Proc Natl Acad Sci U S A 109(35):14052–14057. https://doi.org/10.1073/pnas.1207509109

    Article  PubMed  PubMed Central  Google Scholar 

  • Kukulya A, Plueddemann A, Austin T, Stokey R, Purcell M, Allen B, Littlefield R, Freitag L, Koski P, Gallimore E, Kemp J, Newhall K, Pietro J (2010) Under-ice operations with a REMUS-100 AUV in the Arctic. In Proceedings of the IEEE/OES AUV, pp 1–8, Monterey, CA, USA

    Google Scholar 

  • L3 Communications (2000) Multibeam sonar theory of operation. SeaBeam Instruments, USA pp 1–107

    Google Scholar 

  • Lee CM, Thomson J (2017) Marginal Ice Zone, & Arctic Sea State Teams. An autonomous approach to observing the seasonal ice zone in the western Arctic. Oceanography 30:56–68

    Article  Google Scholar 

  • Ludvigsen M, Johnsen G, Sørensen AJ, Lågstad PA, Ødegård Ø (2014) Scientific operations combining ROV and AUV in the Trondheim Fjord. Mar Technol Soc J 48:59–71

    Google Scholar 

  • Ludvigsen M, Sørensen AJ (2016) Towards integrated autonomous underwater operations for ocean mapping and monitoring. IFAC J Ann Rev Control 42:1–13

    Article  Google Scholar 

  • Ludvigsen M, Berge J, Geoffroy M, Cohen JH, De La Torre PR, Nornes SM, Singh H, Sørensen AJ, Daase M, Johnsen G (2018) Use of an autonomous surface vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance. Sci Adv 4(1):eaap9887

    Article  PubMed  PubMed Central  Google Scholar 

  • Mair JA, Jamieson J, Tena I, Evans J (2010). Autonomous vehicle qualification demonstrates potential for a game change. Offshore Technology Conference, Texas

    Google Scholar 

  • Moline MA, Blackwell SM, Von Alt C, Allen B, Austin T, Case J, Forrester N, Goldsborough R, Purcell M, Stokey R (2005) Remote environmental monitoring units: an autonomous vehicle for characterizing coastal environments. J Atmos Ocean Technol 22:1797–1808

    Article  Google Scholar 

  • Moline MA, Benoit-Bird K, O’Gorman D, Robbins IC (2015) Integration of scientific echo sounders with an adaptable autonomous vehicle to extend our understanding of animals from the surface to the bathypelagic. J Atmos Ocean Technol 32:2173–2186

    Article  Google Scholar 

  • National Research Council (2005) Autonomous vehicles in support of naval operations. Committee on Autonomous Vehicles in Support of Naval Operations, US, ISBN: 0-309-55115-3

    Google Scholar 

  • Nilssen I, Ødegård Ø, Sørensen AJ, Johnsen G, Moline MA, Berge J (2015) Integrated environmental mapping and monitoring, a methodological approach to optimise knowledge gathering and sampling strategy. Mar Pollution Bull 96:374–383. https://doi.org/10.1016/j.marpolbul.2015.04.045

    Article  CAS  Google Scholar 

  • NIST (2015) Retrieved 18th March. http://www.nist.gov/el/isd/ks/autonomy_levels.cfm

  • Norgren P (2018) Autonomous underwater vehicles in Arctic marine operations: Arctic marine research and ice monitoring. PhD thesis, Norwegian University of Science and Technology

    Google Scholar 

  • Norgren P, Skjetne R (2018) A multibeam-based SLAM algorithm for iceberg mapping using AUVs. IEEE Access 6:26318–26337

    Article  Google Scholar 

  • Nornes SM, Ludvigsen M, Ødegård Ø, Sørensen AJ (2015) Underwater photogrammetric mapping of an intact standing steel wreck with ROV. IFAC workshop on navigation, guidance, and control of underwater vehicles, April 28–30, Girona, Spain

    Google Scholar 

  • NSIDC – National Snow, Ice Data Center (2018) Retrieved 8th Mar 2019. Arctic sea ice extent arrives at its minimum. http://nsidc.org/arcticseaicenews/2018/09/arctic-sea-ice-extent-arrives-at-its-minimum/

  • Pizarro O, Singh H (2003) Towards large-area mosaicing for underwater scientific applications. IEEE J Ocean Eng 28:651–672

    Article  Google Scholar 

  • Plueddemann AJ, Kukulya AL, Stokey R, Freita L (2012) Autonomous underwater vehicle operations beneath coastal sea ice. IEEE/ASME Trans Mechatronics 17:54–64

    Article  Google Scholar 

  • Quinn R, Dean M, Lawrence M, Liscoe S, Boland D (2005) Backscatter responses and resolution considerations in archaeological side-scan sonar surveys: a control experiment. J Archaeol Sci 32:1252–1264

    Article  Google Scholar 

  • RDI (2011) Acoustic Doppler current profiler: principles of operation: a practical primer. RD Instruments, Teledyne, USA pp 1–62

    Google Scholar 

  • Ribas D, Ridao P, Tardós JD, Neira J (2008) Underwater SLAM in man-made structured environments. J Field Robot 25:898–921

    Article  Google Scholar 

  • Rudnick DL (2016) Ocean research enabled by underwater gliders. Annu Rev Mar Sci 8:519–541

    Article  Google Scholar 

  • Seto ML (2013) Marine robot autonomy. Springer, New York\Heidelberg\Dordrecht\London ISBN 978-1-4614-5658-2

    Google Scholar 

  • Singh H, Bellingham JG, Hover F, Lerner S, Moran BA, von der Heydt K, Yoerger D (2001) Docking for an Autonomous Ocean Sampling Network. IEEE J Ocean Eng 26:498–514

    Article  Google Scholar 

  • Sørensen AJ, Dukan F, Ludvigsen M, Fernandes DA, Candeloro M (2012) Chapter 6, Development of dynamic positioning and tracking system for the ROV Minerva. In: Roberts G, Sutton B (eds) Further advances in unmanned marine vehicles. IET, UK, pp 113–128

    Google Scholar 

  • Sotzing CC, Lane DM (2010) Improving the coordination efficiency of limited-communication multi–autonomus underwater vehicle operations using a multiagent architecture. Journal of Field Robotics 27:412–429

    Article  Google Scholar 

  • Testor P, Meyers G, Pattiaratchi C, Bachmayer R, Hayes DR, Pouliquen S, Villeon LP et al (2010) Gliders as a component of future observing systems. OceanObs’ 09

    Google Scholar 

  • Tivey MA, Johnson HP, Bradley A, Yoerger D (1998) Thickness of a submarine lava flow determined from near-bottom magnetic field mapping by autonomous underwater vehicle. Geophys Res Lett 25:805–808

    Article  Google Scholar 

  • Utne IB, Sørensen AJ, Schjølberg I (2017) Risk Management of Autonomous Marine Systems and Operations. OMAE2017-61645, proceedings of the 36th international conference on Ocean, Offshore & Arctic Engineering, OMAE17, June 25–30. Trondheim, Norway, p 2017

    Google Scholar 

  • Webb DC, Simonetti PJ, Jones CP (2001) SLOCUM: An underwater glider propelled by environmental energy. IEEE J Ocean Eng 26:447–452

    Article  Google Scholar 

  • Williams SB, Pizarro O, Jakuba M, Johnson CR, Barrett NS, Babcock RC, Kendrick GA, Steinberg PD, Heyward AJ, Doherty PJ, Mahon IJ, Johnson-Roberson M, Steinberg D, Friedman AL (2012) Monitoring of benthic reference sites: using an autonomous underwater vehicle. IEEE Robot Autom Mag 19:73–84

    Article  Google Scholar 

  • Williams G, Maksym T, Wilkinson J, Kunz C, Murphy C, Kimball P, Singh H (2015) Mapping ice thickness and extreme deformation of Antarctic Sea ice from an autonomous underwater vehicle. Nat Geosci 8:61–67

    Article  CAS  Google Scholar 

  • Yamafune K, Torres R, Castro F (2017) Multi-image photogrammetry to record and reconstruct underwater shipwreck sites. J Archaeol Method Theory 24:703–725

    Article  Google Scholar 

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Authors and Affiliations

  1. Centre for Autonomous Marine Operations and System (AMOS), Department of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Asgeir J. Sørensen, Martin Ludvigsen & Petter Norgren

  2. Centre for Autonomous Marine Operations and System (AMOS), NTNU University Museum, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Øyvind Ødegård

  3. Scottish Association for Marine Science, Scottish Marine Institute, Oban, Argyll, UK

    Finlo Cottier

  4. Department of Arctic and Marine Biology, Faculty for Bioscience, Fisheries and Economy, UiT the Arctic University of Norway, Tromsø, Norway

    Finlo Cottier

Authors
  1. Asgeir J. Sørensen
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  2. Martin Ludvigsen
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  3. Petter Norgren
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  4. Øyvind Ødegård
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  5. Finlo Cottier
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Correspondence to Asgeir J. Sørensen .

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Editors and Affiliations

  1. Department of Arctic and Marine Biology, Faculty for Bioscience, Fisheries and Economy, UiT the Arctic University of Norway, Tromsø, Norway The University Centre in Svalbard, Longyearbyen, Centre for Autonomous Marine Operations & Systems (AMOS), Trondhjem Biological Station, Department of Biology, Norwegian University of Science & Technology (NTNU), Trondheim, Norway

    Jørgen Berge

  2. Centre for Autonomous Marine Operations & Systems (AMOS), Trondhjem Biological Station, Department of Biology, Norwegian University of Science & Technology (NTNU), Trondheim, The University Centre in Svalbard, Longyearbyen, Norway

    Geir Johnsen

  3. School of Marine Science and Policy, University of Delaware, Lewes, DE, USA

    Jonathan H. Cohen

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Sørensen, A.J., Ludvigsen, M., Norgren, P., Ødegård, Ø., Cottier, F. (2020). Sensor-Carrying Platforms. In: Berge, J., Johnsen, G., Cohen, J. (eds) POLAR NIGHT Marine Ecology. Advances in Polar Ecology, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-030-33208-2_9

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