期刊
JOURNAL OF MARINE SCIENCE AND ENGINEERING
卷 11, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/jmse11030595
关键词
very high-resolution satellite imagery; artificial intelligence; machine learning; remote sensing; marine mammal; cetacean; annotation; collaborative innovation; open-source; Geospatial Artificial Intelligence for Animals
Monitoring marine mammals through VHR satellites can fill knowledge gaps in their distribution in remote locations. The GAIA initiative aims to leverage satellite imagery, cloud computing, and machine learning to enhance our understanding of cetacean distribution. This paper presents lessons learned, challenges faced, and the vision for the future.
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.
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