Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics.

ABSTRACT: Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and 'nearest neighbour distance' measurements. The latter provide useful summaries of colony spatial structure (which can indicate phenological stage) and can be used to detect movement - metrics which could be valuable for a number of different monitoring scenarios, including image capture during aerial surveys. We present two alternative pathways for producing counts: (1) via the Zooniverse citizen science project Penguin Watch and (2) via a computer vision algorithm (Pengbot), and share a comparison o

SUBMITTER: Jones FM 

PROVIDER: S-EPMC7099010 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature