Stock assessment and data management

Vessels Transmitted Information

Vessel Transmitted Information (VTI) is a Virtual Research Environment that allows importing, "curate" and aggregate data that contain latitude and longitude information. The VRE offers procedures to enhance the information contained in a given dataset with bathymetry and other data which result from trajectories processing. For each point along the trajectory, the VRE can estimate a fishing activity based on the speed of the vessel, and the bathymetry, where speed is based on the time and distance between two measurements. Each transmitted record can also be enriched with information on the FAO Area it belongs to, according to five types of subdivisions. The VRE also contains procedures to calculate the monthly fishing effort per area, according to the time interval involved into the dataset. Two GIS Maps can be produced, visualized and overlaid, which contain the vessel trajectories with classification, for each point, of the vessel activity (fishing, steaming, dodging, etc.) taking bathymetry into account; the monthly fishing effort with half degree resolution. Furthermore, the VRE is equipped with generic functionalities for Time Series management in a distributed infrastructure like data aggregation, union, filtering, etc.; charts reproduction; data analysis with the R language; resources sharing with other VRE users.

Details and usages of this technique are available here.

• Access to the VTI environment here.

Vessels Trajectories Interpolation

An interpolation method relying on the implementation by the authoritative Study Group on VMS (SGVMS). The method uses two interpolation approached to simulate vessels points at a certain temporal resolution. The algorithm processes up to 10000 vessels trajectory points and interpolates the trajectories according to a user's defined temporal resolution. The estimation of trawling tracks use cubic Hermite spline interpolation of position registration data.

The process is taken from the following reference work: Hintzen, N. T., Bastardie, F., Beare, D., Piet, G. J., Ulrich, C., Deporte, N., Egekvist, J., et al. 2012. VMStools: Open-source software for the processing, analysis and visualisation of fisheries logbook and VMS data. Fisheries Research, 115-116: 31-43. Hintzen, N. T., Piet, G. J., and Brunel, T. 2010. The input is a file in TACSAT format uploaded on the Statistical Manager. The output is another TACSAT file containing interpolated points.The underlying R code has been extracted from the SGVM VMSTools framework. Further details on using this tool are available here.

• Name of the algorithm on StatMan: Sgvm Interpolation

Seasonality and periodicity detection

An algorithms applying signal processing to a time series of catch statistics. The process uniformly samples the series, then extracts hidden periodicities and signal properties. The sampling period is taken as the shortest time difference between two points. Finally, by using Caterpillar-SSA the algorithm forecasts the Time Series. The output shows the detected periodicity, the forecasted signal and the spectrogram. One experiment using this technique to predict fishing activity in the Indian Ocean is available here.

• Name of the algorithm on StatMan: Time Series Analysis