Improved estimation of trawling tracks using cubic Hermite spline interpolation of position registration data

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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.
Original languageEnglish
Pages (from-to)108-115
JournalFisheries Research
Publication statusPublished - 2010



  • monitoring-system data
  • southern north-sea
  • benthic communities
  • impact
  • disturbance
  • resolution
  • pressure
  • scale
  • indicators
  • management

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