Coastal SEA Surface Salinity Retrieval Analysis from SMAP Mission using Machine Learning-Reference-Cited by-同舟云学术

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Coastal SEA Surface Salinity Retrieval Analysis from SMAP Mission using Machine Learning

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Lv YanFang¹,Zhang YiFan¹,Liu JingYi²,Zhang LanJie¹

Affiliation:

1. Ministry of Information Industry, Beijing Information Science and Technology University,Key Laboratory of Information and Communication Systems,Beijing,China,100101

2. National Space Science Center, Chinese Academy of Sciences,Key Laboratory of Microwave Remote Sensing,Beijing,China,100190

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282625.pdf?arnumber=10282625

Reference8 articles.

1. The Effect of Salinity on Density in the Leeuwin Current System[J];Huang;Journal of Geophysical Research Oceans,1996

2. The Soil Moisture Active Passive (SMAP) Mission

3. Empirical Characterization of the SMOS Brightness Temperature Bias and Uncertainty for Improving Sea Surface Salinity Retrieval

4. Global Analysis of Coastal Gradients of Sea Surface Salinity

5. A Novel Wind Speed Estimation Based on the Integration of an Artificial Neural Network and a Particle Filter Using BeiDou GEO Reflectometry

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