Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape

New satellite remote sensing and machine learning techniques offer untapped possibilities to monitor global biodiversity with unprecedented speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and ent...

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Veröffentlicht in:	Nature communications Jg. 14; H. 1; S. 3072 - 15
Hauptverfasser:	Wu, Zijing, Zhang, Ce, Gu, Xiaowei, Duporge, Isla, Hughey, Lacey F., Stabach, Jared A., Skidmore, Andrew K., Hopcraft, J. Grant C., Lee, Stephen J., Atkinson, Peter M., McCauley, Douglas J., Lamprey, Richard, Ngene, Shadrack, Wang, Tiejun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 27.05.2023 Nature Publishing Group Nature Portfolio
Schlagworte:	639/624/1107/510 704/158/2039 Animal behavior Animals Biodiversity Deep Learning Ecosystem Ecosystems Humanities and Social Sciences Learning algorithms Machine learning Mammals multidisciplinary Populations Remote sensing Remote Sensing Technology Satellite imagery Satellites Science Science (multidisciplinary) Strategic management Ungulates
ISSN:	2041-1723, 2041-1723
Online-Zugang:	Volltext
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