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Big Earth Data Volume 6, 2022 - Issue 2: Remotely sensed big data for the oceans and polar regions
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Data Article

A global process-oriented sea surface temperature anomaly dataset retrieved from remote sensing products

Cunjin Xuea Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China;b Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-3605-6578View further author information
ORCID Icon,
Yangfeng Xua Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China;c College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, ChinaView further author information
&
Yawen Hec College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, ChinaView further author information
Pages 179-195 | Received 08 Jun 2021, Accepted 28 Sep 2021, Published online: 14 Dec 2021

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Xinyu Zou, Xiangnan Liu, Meiling Liu, Lingwen Tian, Lihong Zhu & Qian Zhang. (2023) Spatiotemporal graph-based analysis of land cover evolution using remote sensing time series data. International Journal of Geographical Information Science 37:5, pages 1009-1040.
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Xiao-Ming Li. (2022) Remotely sensed big data for the oceans and polar regions. Big Earth Data 6:2, pages 141-143.
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Articles from other publishers (1)

Cunjin Xue, Chaoran Niu, Yangfeng Xu & Fenzhen Su. (2023) A Process-Oriented Exploration of the Evolutionary Structures of Ocean Dynamics with Time Series of a Remote Sensing Dataset. Remote Sensing 15:2, pages 348.
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