Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering
Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the a...
Published in: | PLoS ONE |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2014
|
Subjects: | |
Online Access: | https://research-portal.st-andrews.ac.uk/en/publications/4e6f9198-df80-47c2-806c-958514377707 https://doi.org/10.1371/journal.pone.0092277 https://research-repository.st-andrews.ac.uk/bitstream/10023/4538/1/Silva_etal_2014_Assessing_performance_of_Bayesian_SSM_1.pdf |
id |
ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/4e6f9198-df80-47c2-806c-958514377707 |
---|---|
record_format |
openpolar |
spelling |
ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/4e6f9198-df80-47c2-806c-958514377707 2024-10-13T14:06:14+00:00 Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering Silva, Monica A. Jonsen, Ian Russell, Deborah Jill Fraser Prieto, Rui Thompson, David Baumgartner, Mark F. 2014-03-20 application/pdf https://research-portal.st-andrews.ac.uk/en/publications/4e6f9198-df80-47c2-806c-958514377707 https://doi.org/10.1371/journal.pone.0092277 https://research-repository.st-andrews.ac.uk/bitstream/10023/4538/1/Silva_etal_2014_Assessing_performance_of_Bayesian_SSM_1.pdf eng eng info:eu-repo/semantics/openAccess Silva , M A , Jonsen , I , Russell , D J F , Prieto , R , Thompson , D & Baumgartner , M F 2014 , ' Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering ' , PLoS One , vol. 9 , no. 3 , e92277 . https://doi.org/10.1371/journal.pone.0092277 Algorithms Satellite-tracked animals Kalman filter (KF) Least Squares (LS) algorithm Bayesian state-space models (SSMs) Harbour seal (Phoca vitulina) ARGOS satellite transmitter Fin whales (Balaenoptera physalus) Switching state-space models (SSSM) article 2014 ftunstandrewcris https://doi.org/10.1371/journal.pone.0092277 2024-10-02T23:40:44Z Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to “true” GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6±5.6 km) was nearly half that of LS estimates (11.6±8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales’ behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates. Article in Journal/Newspaper Balaenoptera physalus harbour seal Phoca vitulina University of St Andrews: Research Portal PLoS ONE 9 3 e92277 |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
topic |
Algorithms Satellite-tracked animals Kalman filter (KF) Least Squares (LS) algorithm Bayesian state-space models (SSMs) Harbour seal (Phoca vitulina) ARGOS satellite transmitter Fin whales (Balaenoptera physalus) Switching state-space models (SSSM) |
spellingShingle |
Algorithms Satellite-tracked animals Kalman filter (KF) Least Squares (LS) algorithm Bayesian state-space models (SSMs) Harbour seal (Phoca vitulina) ARGOS satellite transmitter Fin whales (Balaenoptera physalus) Switching state-space models (SSSM) Silva, Monica A. Jonsen, Ian Russell, Deborah Jill Fraser Prieto, Rui Thompson, David Baumgartner, Mark F. Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
topic_facet |
Algorithms Satellite-tracked animals Kalman filter (KF) Least Squares (LS) algorithm Bayesian state-space models (SSMs) Harbour seal (Phoca vitulina) ARGOS satellite transmitter Fin whales (Balaenoptera physalus) Switching state-space models (SSSM) |
description |
Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to “true” GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6±5.6 km) was nearly half that of LS estimates (11.6±8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales’ behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates. |
format |
Article in Journal/Newspaper |
author |
Silva, Monica A. Jonsen, Ian Russell, Deborah Jill Fraser Prieto, Rui Thompson, David Baumgartner, Mark F. |
author_facet |
Silva, Monica A. Jonsen, Ian Russell, Deborah Jill Fraser Prieto, Rui Thompson, David Baumgartner, Mark F. |
author_sort |
Silva, Monica A. |
title |
Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
title_short |
Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
title_full |
Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
title_fullStr |
Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
title_full_unstemmed |
Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering |
title_sort |
assessing performance of bayesian state-space models fit to argos satellite telemetry locations processed with kalman filtering |
publishDate |
2014 |
url |
https://research-portal.st-andrews.ac.uk/en/publications/4e6f9198-df80-47c2-806c-958514377707 https://doi.org/10.1371/journal.pone.0092277 https://research-repository.st-andrews.ac.uk/bitstream/10023/4538/1/Silva_etal_2014_Assessing_performance_of_Bayesian_SSM_1.pdf |
genre |
Balaenoptera physalus harbour seal Phoca vitulina |
genre_facet |
Balaenoptera physalus harbour seal Phoca vitulina |
op_source |
Silva , M A , Jonsen , I , Russell , D J F , Prieto , R , Thompson , D & Baumgartner , M F 2014 , ' Assessing performance of Bayesian state-space models fit to Argos Satellite telemetry locations processed with Kalman Filtering ' , PLoS One , vol. 9 , no. 3 , e92277 . https://doi.org/10.1371/journal.pone.0092277 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1371/journal.pone.0092277 |
container_title |
PLoS ONE |
container_volume |
9 |
container_issue |
3 |
container_start_page |
e92277 |
_version_ |
1812812303040512000 |