A Fast Polarized BRDF Model Developed for Spaceborne Scatterometer with Neural Network-Reference-Cited by-同舟云学术

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A Fast Polarized BRDF Model Developed for Spaceborne Scatterometer with Neural Network

Published:2024-07-07 Issue: Volume: Page:10580-10582
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Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Wen Jinghan¹,Xu Jing²,Weng Fuzhong³,He Lingli²,Jia Tong¹,Zhang Lei¹

Affiliation:

1. Chinese Academy of Meteorological Sciences,Qingdao Joint Institute of Marine Meteorology,Qingdao,China,266000

2. China Meteorological Administration,Chinese Academy of Meteorological Sciences,Beijing,China,100081

3. China Meteorological Administration,Earth System Modeling and Prediction Centre,Beijing,China,100081

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640728.pdf?arnumber=10640728

Reference8 articles.

1. Synergic inversion technique for active and passive microwave remote sensing of the ocean

2. Development of a modified two-scale electromagnetic model simulating both active and passive microwave measurements: Comparison to data remotely sensed over the ocean

3. PARMIO: A Reference Quality Model for Ocean Surface Emissivity and Backscatter from the Microwave to the Infrared

4. Improved Microwave Ocean Emissivity and Reflectivity Models Derived from Two-Scale Roughness Theory

5. Polarized Bidirectional Reflectance Distribution Function (pBRDF) Derived from Two-scale Roughness Theory and Its Applications for Active Remote Sensing;He;IEEE Transactions on Geoscience and Remote Sensing,2024

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