A continuous-time state-space model for rapid quality control of argos locations from animal-borne tags.

ABSTRACT:

Background

State-space models are important tools for quality control and analysis of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system can aid dynamic ocean management of human activities by informing when animals enter wind farms, shipping lanes, and other intensive use zones. This capability also facilitates the use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations.

Methods

We formulate a continuous-time state-space model to filter the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of obser

SUBMITTER: Jonsen ID 

PROVIDER: S-EPMC7368688 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature