Annotating very high-resolution satellite imagery: A whale case study
Hannah Charlotte Cubaynes,
Penny Joanna Clarke,
Kimberly Thea Goetz,
Tyler Aldrich,
Peter Thomas Fretwell,
Kathleen Elise Leonard,
Christin Brangwynne Khan
Affiliations
Hannah Charlotte Cubaynes
British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom; Corresponding author.
Penny Joanna Clarke
British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom; School of Engineering, The University of Edinburgh, Sanderson Building, Robert Stevenson Road, The King's Buildings, Edinburgh, EH9 3FB, United Kingdom
Kimberly Thea Goetz
Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, Seattle, Washington, United States
Tyler Aldrich
Northeast Fisheries Science Center, National Marine Fisheries Service, NOAA, Woods Hole, MA, United States
Peter Thomas Fretwell
British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom
Kathleen Elise Leonard
Protected Resources Division, Alaska Regional Office, National Marine Fisheries Service, NOAA, Anchorage, AK, United States
Christin Brangwynne Khan
Northeast Fisheries Science Center, National Marine Fisheries Service, NOAA, Woods Hole, MA, United States
The use of very high-resolution (VHR) optical satellites is gaining momentum in the field of wildlife monitoring, particularly for whales, as this technology is showing potential for monitoring the less studied regions. However, surveying large areas using VHR optical satellite imagery requires the development of automated systems to detect targets. Machine learning approaches require large training datasets of annotated images. Here we propose a standardised workflow to annotate VHR optical satellite imagery using ESRI ArcMap 10.8, and ESRI ArcGIS Pro 2.5., using cetaceans as a case study, to develop AI-ready annotations. • A step-by-step protocol to review VHR optical satellite images and annotate the features of interest. • A step-by-step protocol to create bounding boxes encompassing the features of interest. • A step-by-step guide to clip the satellite image using bounding boxes to create image chips.
