Article, Early Access,
A workflow for standardizing the analysis of highly resolved vessel tracking data
Affiliations
- [1] Univ St Andrews, Sch Geog & Sustainable Dev, St Andrews KY16 9AL, Scotland [NORA names: United Kingdom; Europe, Non-EU; OECD];
- [2] Univ Politecn Cataluna, Barcelona Sch Naut Studies, Barcelona 08003, Catalunya, Spain [NORA names: Spain; Europe, EU; OECD];
- [3] Tech Univ Denmark, Natl Inst Aquat Resources, DK-2800 Lyngby, Denmark [NORA names: DTU Technical University of Denmark; University; Denmark; Europe, EU; Nordic; OECD];
- [4] Basque Res & Technol Alliance BRTA, AZTI, Sustainable Fisheries Management, Bizkaia 48395, Basque Country, Spain [NORA names: Spain; Europe, EU; OECD];
- [5] Portugues Inst Sea & Atmosphere IPMA, Div Modelling & Management Fisheries Resources, Av Dr Alfredo Magalhaes Ramalho 6, P-1495165 Lisbon, Portugal [NORA names: Portugal; Europe, EU; OECD];
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Abstract
Knowledge on the spatial and temporal distribution of the activities carried out in the marine environment is key to manage available space optimally. However, frequently, little or no information is available on the distribution of the largest users of the marine space, namely fishers. Tracking devices are being increasingly used to obtain highly resolved geospatial data of fishing activities, at intervals from seconds to minutes. However, to date no standardized method is used to process and analyse these data, making it difficult to replicate analysis. We develop a workflow to identify individual vessel trips and infer fishing activities from highly resolved geospatial data, which can be applied for large-scale fisheries, but also considers nuances encountered when working with small-scale fisheries. Recognizing the highly variable nature of activities conducted by different fleets, this workflow allows the user to choose a path that best aligns with the particularities in the fishery being analysed. A new method to identify anchoring sites for small-scale fisheries is also presented. The paper provides detailed code used in each step of the workflow both in R and Python language to widen the application of the workflow in the scientific and stakeholder communities and to encourage its improvement and refinement in the future.