Classifying behavior from short-interval biologging data: An example with GPS tracking of birds.

ABSTRACT: Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.We apply a framework for using K-means clustering to classify bird behavior using points from short time interval GPS tracks. K-means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K-means clustering to six focal variables derived fr

SUBMITTER: Bergen S 

PROVIDER: S-EPMC8819645 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature