In MethodsX
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.
Cubaynes Hannah Charlotte, Clarke Penny Joanna, Goetz Kimberly Thea, Aldrich Tyler, Fretwell Peter Thomas, Leonard Kathleen Elise, Khan Christin Brangwynne
2023
AI-ready data, Cetacean, Labeling, Machine learning, Satellite image annotation to create point, bounding boxes and image datasets to train automated systems., VHR optical satellite image, Wildlife
