Ocean eddy identification and tracking using neural networks

Katharina Franz, Ribana Roscher, Andres Milioto, Susanne Wenzel, Jürgen Kusche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

67 Scopus citations


Global climate change plays an essential role in our daily life. Mesoscale ocean eddies have a significant impact on global warming, since they affect the ocean dynamics, the energy as well as the mass transports of ocean circulation. From satellite altimetry we can derive high-resolution, global maps containing ocean signals with dominating coherent eddy structures. The aim of this study is the development and evaluation of a deep-learning based approach for the analysis of eddies. In detail, we develop an eddy identification and tracking framework with two different approaches that are mainly based on feature learning with convolutional neural networks. Furthermore, state-of-the-art image processing tools and object tracking methods are used to support the eddy tracking. In contrast to previous methods, our framework is able to learn a representation of the data in which eddies can be detected and tracked in more objective and robust way. We show the detection and tracking results on sea level anomalies (SLA) data from the area of Australia and the East Australia current, and compare our two eddy detection and tracking approaches to identify the most robust and objective method.

Original languageEnglish
Title of host publication2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781538671504
StatePublished - 31 Oct 2018
Externally publishedYes
Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)


Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018


  • Convolutional neural networks
  • Mesoscale eddies
  • Optical flow
  • Semantic segmentation


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