Improved estimation of trawling tracks using cubic Hermite spline interpolation of position registration data |
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| Authors: | Niels T Hintzen Gerjan J Piet Thomas Brunel |
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| Institution: | 1. Istituto per l’Ambiente Marino Costiero – Consiglio Nazionale delle Ricerche, Sede di Mazara del Vallo (TP), Via L. Vaccara 61, 91026 Mazara del Vallo, Italy;2. Istituto per l’Ambiente Marino Costiero – Consiglio Nazionale delle Ricerche, Sede di Capo Granitola, Via del Mare 3, 91021 Campobello di Mazara (TP), Italy;3. Russian Federal Research Institute of Fisheries & Oceanography (VNIRO), 17, V.Krasnoselskaya, Moscow 107140, Russia;1. The School of Electronic and Information Engineering, HuBei University of Science and Technology, Xianning 437100, China;2. Science Program, Texas A&M University at Qatar, P.O. Box 23874, Doha, Qatar;3. Institute of Physics, University of Belgrade, P.O. Box 68, 11001 Belgrade, Serbia;1. Department of Bioengineering, University of California San Diego, La Jolla, CA, USA;2. Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, NC, USA;3. Simula Research Laboratory, Center for Biomedical Computing, Lysaker, Norway;4. Cardiothoracic Radiology, Veterans Administration Healthcare System, San Diego, CA, USA;5. Department of Physics, University of California San Diego, La Jolla, CA, USA;6. Center for Theoretical Biological Physics, University of California San Diego, La Jolla, CA, USA;7. Department of Medicine (Cardiology), University of California San Diego, La Jolla, CA, USA;8. Division of Cardiology, Veterans Administration Healthcare System, San Diego, CA, USA;9. Cardiac Biomedical Science and Engineering Center, University of California San Diego, La Jolla, CA, USA;10. Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA;1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, via Ponzio 34/5, 20133 Milano, Italy;2. Consorzio Interuniversitario per le Scienze del Mare, Piazzale Flaminio 9, 00196 Roma, Italy;3. COISPA Tecnologia & Ricerca, Stazione Sperimentale per lo Studio delle Risorse del Mare, Via dei Trulli 18/20, 70126 Bari, Italy;4. NISEA Società Cooperativa, via Irno 11, 84135 Salerno, Italy;1. Faculty of Ocean Engineering and Ship Technology, Gdansk University of Technology, Poland;2. Faculty of Navigation, Gdynia Maritime University, Poland |
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| Abstract: | For control and enforcement purposes, all fishing vessels operating in European waters are equipped with satellite-based Vessel Monitoring by Satellite systems (VMS) recording their position at regular time intervals. VMS data are increasingly used by scientists to study spatial and temporal patterns of fishing activity and thus fishing impact (e.g. surface of sea bed trawled during a fishing trip). However, due to their low resolution (2 h basis), these data may provide a biased perception of fishing impact. We present here a method aiming at interpolating vessel trajectories from VMS data points to obtain higher-resolution data on vessel trajectories which in turn should provide improved estimates of the spatial and temporal patterns of fishing activity and hence fishing impact. This method is based on a spline interpolation technique, the cubic Hermite spline (cHs), using position, heading and speed to interpolate the trawl track of a vessel between two succeeding VMS data points. To take uncertainty of the interpolated track into account, the method also determines a confidence interval, which represents the spatial distribution of vessel presence probability between two successive VMS positions. The cHs method was compared to the straight line interpolation technique using a reference data set with intervals of 6 min which was assumed to represent the real trawl tracks. The results showed that the cHs method approximates the real trawl track markedly better than a straight line interpolation. The cHs method should therefore be preferred to the conventional straight line approach to interpolate vessel tracks in studies aiming at estimating fishing impact from VMS data. |
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