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01 September 2021
Big Earth Data
Special Issue Editor(s)
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences
Laboratory of Oceanography From Space, French Research Institute for Exploitation of the Sea, France
Remotely Sensed Big Data for Ocean and Polar Regions
Remote sensing data naturally have the ‘5V’ – volume, velocity, variety, veracity and value – characteristics of big data. As its use has developed, remotely sensed data has demonstrated its enormous value in the field of Earth observation. Along with the development of modern information techniques, e.g., machine learning and cloud computing, the strengths of spaceborne and airborne remote sensing as sources of big data for Earth observation have become ever more apparent.
Oceans cover 71% of the Earth’s surface. Together with the cold polar regions, the oceans play a crucial role in energy exchange and circulation at the Earth’s surface and also in climate change. In particular, against the background of global climate change, both the Arctic and Antarctic are experiencing profound changes. The interactions between the oceans, polar regions and atmosphere are more important than ever. Using remote sensing, and using remotely sensed big data in particular, we can better understand the past, present and future of the oceans and polar regions.
This special issue aims to highlight the recent progress that has been made in the application of remotely sensed big data to studies of the oceans and polar regions. We invite original research articles, review articles and data articles related to (but not limited to) the following:
• Reviews of the state of the art of remote sensing for ocean and polar observations.
• Theories, methodologies and techniques related to the derivation of key ocean and ice parameters – e.g., ocean dynamic parameters, ocean biological parameters, and sea ice and ice-sheet parameters – as derived from both satellite and airborne remote sensing data.
• Descriptions of innovative datasets relevant to the remote sensing of the oceans and polar regions.
• Synergetic use of remote sensing, in situ and numerical model data for understanding the dynamics of ocean and polar regions and also the interaction between them.
• Assimilation of data from multiple sources for numerical weather prediction and for making forecasts of ocean and ice states.
• Innovative techniques for remote sensing big data acquisition, visualization, analysis and interpretation relevant to ocean and polar observations.
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• 1 September, 2021 Paper Submission Online
• 1 November, 2021 Decision to Authors
• 1 January, 2022 Revised Paper Submission
• 1 March 2022 Publication
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