New insights in interpolating fishing tracks from VMS data for different métiers

The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and quantitative evaluations of fishing effort at both spatial and temporal scale. Given that the main VMS limit is represented by the temporal r...

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Published inFisheries research Vol. 108; no. 1; pp. 184 - 194
Main Authors Russo, Tommaso, Parisi, Antonio, Cataudella, Stefano
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.02.2011
Elsevier
Subjects
Online AccessGet full text
ISSN0165-7836
1872-6763
DOI10.1016/j.fishres.2010.12.020

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Abstract The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and quantitative evaluations of fishing effort at both spatial and temporal scale. Given that the main VMS limit is represented by the temporal resolution (generally 2 h) of signals, a series of approach has been developed to interpolate vessels positions. The newest and most powerful method in this framework is based on cubic Hermite splines (cHs), which have been efficiently tested against the conventional straight line interpolation over a dataset representing fishing activity by beam trawl. However, this method has never been applied on other different gears and/or métiers. Here we propose a new approach (CRm), which is a modification of the Catmull–Rom algorithm (CR). This new method takes into account for the different aspects involved in vessel navigation, such as the combined actions of human control and drift by sea current and wind (if present). The drift component is not observed, but is estimated within the method, using the VMS data. This method has been developed in order to model the behaviour of vessels that operate using different gear types. The CRm method was compared to the cHs method, using three reference datasets (each containing VMS signals at intervals of 20 min) corresponding to three different métiers largely used in Mediterranean fisheries: bottom otter trawl for demersal species (OTB), trammel nets for demersal species (GTR), and purse seine for small pelagic fish (PS), which differ each other for the dynamic aspects connected to the use of fishing gears, and represent an archetype of the three groups actually used to classify fishing gears (namely towed, active and passive). The comparison was carried out both analyzing the error affecting interpolation of single tracks and converting the interpolated tracks into gridded data to be used for computation of ecological indicators of fishing pressure. All the results coherently evidences that the CRm algorithm performs better in interpolating trawl tracks (OTB) and that, moreover, it is able to capture the complex behaviour characterizing the trajectories of vessels performing the other two inspected métiers (GTR and PS). Finally, CRm allows a better estimation of fishing effort, as measured by ecological indicators. These findings support the idea that the conceptual formulation of CRm method is appropriate to model whatever fishing tracks presently generated by fishery vessels and could be efficiently applied in order to obtain better estimation of fishing pressure and, if sensitivity data are available, of fishing impacts.
AbstractList The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and quantitative evaluations of fishing effort at both spatial and temporal scale. Given that the main VMS limit is represented by the temporal resolution (generally 2 h) of signals, a series of approach has been developed to interpolate vessels positions. The newest and most powerful method in this framework is based on cubic Hermite splines (cHs), which have been efficiently tested against the conventional straight line interpolation over a dataset representing fishing activity by beam trawl. However, this method has never been applied on other different gears and/or métiers. Here we propose a new approach (CRm), which is a modification of the Catmull–Rom algorithm (CR). This new method takes into account for the different aspects involved in vessel navigation, such as the combined actions of human control and drift by sea current and wind (if present). The drift component is not observed, but is estimated within the method, using the VMS data. This method has been developed in order to model the behaviour of vessels that operate using different gear types. The CRm method was compared to the cHs method, using three reference datasets (each containing VMS signals at intervals of 20 min) corresponding to three different métiers largely used in Mediterranean fisheries: bottom otter trawl for demersal species (OTB), trammel nets for demersal species (GTR), and purse seine for small pelagic fish (PS), which differ each other for the dynamic aspects connected to the use of fishing gears, and represent an archetype of the three groups actually used to classify fishing gears (namely towed, active and passive). The comparison was carried out both analyzing the error affecting interpolation of single tracks and converting the interpolated tracks into gridded data to be used for computation of ecological indicators of fishing pressure. All the results coherently evidences that the CRm algorithm performs better in interpolating trawl tracks (OTB) and that, moreover, it is able to capture the complex behaviour characterizing the trajectories of vessels performing the other two inspected métiers (GTR and PS). Finally, CRm allows a better estimation of fishing effort, as measured by ecological indicators. These findings support the idea that the conceptual formulation of CRm method is appropriate to model whatever fishing tracks presently generated by fishery vessels and could be efficiently applied in order to obtain better estimation of fishing pressure and, if sensitivity data are available, of fishing impacts.
The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and quantitative evaluations of fishing effort at both spatial and temporal scale. Given that the main VMS limit is represented by the temporal resolution (generally 2h) of signals, a series of approach has been developed to interpolate vessels positions. The newest and most powerful method in this framework is based on cubic Hermite splines (cHs), which have been efficiently tested against the conventional straight line interpolation over a dataset representing fishing activity by beam trawl. However, this method has never been applied on other different gears and/or metiers. Here we propose a new approach (CRm), which is a modification of the Catmull-Rom algorithm (CR). This new method takes into account for the different aspects involved in vessel navigation, such as the combined actions of human control and drift by sea current and wind (if present). The drift component is not observed, but is estimated within the method, using the VMS data. This method has been developed in order to model the behaviour of vessels that operate using different gear types. The CRm method was compared to the cHs method, using three reference datasets (each containing VMS signals at intervals of 20min) corresponding to three different metiers largely used in Mediterranean fisheries: bottom otter trawl for demersal species (OTB), trammel nets for demersal species (GTR), and purse seine for small pelagic fish (PS), which differ each other for the dynamic aspects connected to the use of fishing gears, and represent an archetype of the three groups actually used to classify fishing gears (namely towed, active and passive). The comparison was carried out both analyzing the error affecting interpolation of single tracks and converting the interpolated tracks into gridded data to be used for computation of ecological indicators of fishing pressure. All the results coherently evidences that the CRm algorithm performs better in interpolating trawl tracks (OTB) and that, moreover, it is able to capture the complex behaviour characterizing the trajectories of vessels performing the other two inspected metiers (GTR and PS). Finally, CRm allows a better estimation of fishing effort, as measured by ecological indicators. These findings support the idea that the conceptual formulation of CRm method is appropriate to model whatever fishing tracks presently generated by fishery vessels and could be efficiently applied in order to obtain better estimation of fishing pressure and, if sensitivity data are available, of fishing impacts.
The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and quantitative evaluations of fishing effort at both spatial and temporal scale. Given that the main VMS limit is represented by the temporal resolution (generally 2h) of signals, a series of approach has been developed to interpolate vessels positions. The newest and most powerful method in this framework is based on cubic Hermite splines (cHs), which have been efficiently tested against the conventional straight line interpolation over a dataset representing fishing activity by beam trawl. However, this method has never been applied on other different gears and/or métiers. Here we propose a new approach (CRm), which is a modification of the Catmull–Rom algorithm (CR). This new method takes into account for the different aspects involved in vessel navigation, such as the combined actions of human control and drift by sea current and wind (if present). The drift component is not observed, but is estimated within the method, using the VMS data. This method has been developed in order to model the behaviour of vessels that operate using different gear types. The CRm method was compared to the cHs method, using three reference datasets (each containing VMS signals at intervals of 20min) corresponding to three different métiers largely used in Mediterranean fisheries: bottom otter trawl for demersal species (OTB), trammel nets for demersal species (GTR), and purse seine for small pelagic fish (PS), which differ each other for the dynamic aspects connected to the use of fishing gears, and represent an archetype of the three groups actually used to classify fishing gears (namely towed, active and passive). The comparison was carried out both analyzing the error affecting interpolation of single tracks and converting the interpolated tracks into gridded data to be used for computation of ecological indicators of fishing pressure. All the results coherently evidences that the CRm algorithm performs better in interpolating trawl tracks (OTB) and that, moreover, it is able to capture the complex behaviour characterizing the trajectories of vessels performing the other two inspected métiers (GTR and PS). Finally, CRm allows a better estimation of fishing effort, as measured by ecological indicators. These findings support the idea that the conceptual formulation of CRm method is appropriate to model whatever fishing tracks presently generated by fishery vessels and could be efficiently applied in order to obtain better estimation of fishing pressure and, if sensitivity data are available, of fishing impacts.
Author Russo, Tommaso
Cataudella, Stefano
Parisi, Antonio
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  givenname: Antonio
  surname: Parisi
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  givenname: Stefano
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Issue 1
Keywords Ecological indicators
Interpolation
Métiers
VMS
Fishing impact
Fishery
Ecologicalindicators
Fishing
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Snippet The Vessel Monitoring by satellite System (VMS) is a powerful tool in fishery management, since it allows for high resolution analyses of fishing activity and...
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SubjectTerms algorithms
Animal, plant and microbial ecology
Applied ecology
aquacultural and fisheries equipment
Biological and medical sciences
data collection
Ecological indicators
Exploitation and management of natural biological resources (hunting, fishing and exploited populations survey, etc.)
fisheries
fisheries management
Fishing impact
Fundamental and applied biological sciences. Psychology
gears
humans
Interpolation
monitoring
Métiers
pelagic fish
quantitative analysis
VMS
water currents
wind
Title New insights in interpolating fishing tracks from VMS data for different métiers
URI https://dx.doi.org/10.1016/j.fishres.2010.12.020
https://www.proquest.com/docview/1705439115
https://www.proquest.com/docview/860380628
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