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Using GPS data to evaluate the accuracy of state-space methods for correction of Argos satellite telemetry error
Citation
Patterson, TA and McConnell, BJ and Fedak, MA and Bravington, MV and Hindell, MA, Using GPS data to evaluate the accuracy of state-space methods for correction of Argos satellite telemetry error , Ecology, 91, (1) pp. 273-285. ISSN 0012-9658 (2010) [Refereed Article]
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Copyright Statement
Copyright © 2010 Ecological Society of America
Abstract
Recent studies have applied state–space models to satellite telemetry data in
order to remove noise from raw location estimates and infer the true tracks of animals.
However, while the resulting tracks may appear plausible, it is difficult to determine the
accuracy of the estimated positions, especially for position estimates interpolated to times
between satellite locations. In this study, we use data from two gray seals (Halichoerus grypus)
carrying tags that transmitted Fastloc GPS positions via Argos satellites. This combination of
Service Argos data and highly accurate GPS data allowed examination of the accuracy of
state–space position estimates and their uncertainty derived from satellite telemetry data.
After applying a speed filter to remove aberrant satellite telemetry locations, we fit a
continuous-time Kalman filter to estimate the parameters of a random walk, used Kalman
smoothing to infer positions at the times of the GPS measurements, and then compared the
filtered telemetry estimates with the actual GPS measurements. We investigated the effect of
varying maximum speed thresholds in the speed-filtering algorithm on the root mean-square
error (RMSE ) estimates and used minimum RMSE as a criterion to guide the final choice of
speed threshold. The optimal speed thresholds differed between the two animals (1.1 m/s and
2.5 m/s) and retained 50% and 65% of the data for each seal. However, using a speed filter of
1.1 m/s resulted in very similar RMSE for both animals. For the two seals, the RMSE of the
Kalman-filtered estimates of location were 5.9 and 12.76 km, respectively, and 75% of the
modeled positions had errors less than 6.25 km and 11.7 km for each seal. Confidence interval
coverage was close to correct at typical levels (80 –95%), although it tended to be overly
generous at smaller sizes. The reliability of uncertainty estimates was also affected by the
chosen speed threshold. The combination of speed and Kalman filtering allows for effective
calculation of location and also indicates the limits of accuracy when correcting service Argos
locations and linking satellite telemetry data to spatial covariate and habitat data.
Item Details
Item Type: | Refereed Article |
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Keywords: | Argos error, Fastloc GPS, gray seal, Halichoerus grypus, Kalman filter, marine mammals, state–space model |
Research Division: | Biological Sciences |
Research Group: | Biochemistry and cell biology |
Research Field: | Systems biology |
Objective Division: | Environmental Management |
Objective Group: | Coastal and estuarine systems and management |
Objective Field: | Assessment and management of coastal and estuarine ecosystems |
UTAS Author: | Patterson, TA (Dr Toby Patterson) |
UTAS Author: | Hindell, MA (Professor Mark Hindell) |
ID Code: | 63713 |
Year Published: | 2010 |
Web of Science® Times Cited: | 76 |
Deposited By: | Zoology |
Deposited On: | 2010-05-25 |
Last Modified: | 2013-01-14 |
Downloads: | 0 |
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