Monitoring marine mammals is of broad interest to governments and individuals around the globe. Very high-resolution (VHR) satellites hold the promise of reaching remote and challenging locations to fill gaps in our knowledge of marine mammal distribution. The time has come to create an operational platform that leverages the increased resolution of satellite imagery, proof-of-concept research, advances in cloud computing, and machine learning to monitor the world’s oceans. The Geospatial Artificial Intelligence for Animals (GAIA) initiative was formed to address this challenge with collaborative innovation from government agencies, academia, and the private sector. In this paper, we share lessons learned, challenges faced, and our vision for how VHR satellite imagery can enhance our understanding of cetacean distribution in the future.
Bibliographical noteFunding Information:
Downloading and handling large volumes of satellite imagery is time consuming and requires cloud storage and processing infrastructure. This adds additional complexity and cost to the development of an operational system. GAIA is being supported by a grant from Microsoft AI for Good for cloud compute resources in Azure.
This research was funded by the U.S. Naval Research Laboratory, Microsoft, the National Oceanographic Partnership Program, the National Protected Species Toolbox initiative, NOAA’s High Performance Computing and Communications IT Incubator, the Marine Mammal Commission (project MMC21-043), and the Ecosystems component of the British Antarctic Survey, funded by the Natural Environment Research council (NERC).
© 2023 by the authors.
- Geospatial Artificial Intelligence for Animals
- artificial intelligence
- collaborative innovation
- machine learning
- marine mammal
- remote sensing
- very high-resolution satellite imagery