GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet-Reference-Cited by-同舟云学术

GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet

Published:2022-02 Issue: Volume:269 Page:112801
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Asgarimehr Milad^ORCID,Arnold Caroline^ORCID,Weigel Tobias^ORCID,Ruf Chris^ORCID,Wickert Jens

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference37 articles.

1. TDS-1 GNSS reflectometry: development and validation of forward scattering winds;Asgarimehr;IEEE J. Select. Top. Appl. Earth Observ. Rem. Sens.,2018

2. Can GNSS reflectometry detect precipitation over oceans?;Asgarimehr;Geophys. Res. Lett.,2018

3. A GNSS-R geophysical model function: machine learning for wind speed retrievals;Asgarimehr;IEEE Geosci. Rem. Sens. Lett.,2020

4. Remote sensing of precipitation using reflected GNSS signals: response analysis of polarimetric observations;Asgarimehr;IEEE Trans. Geosci. Rem. Sens.,2021

5. Characterization of rain impact on L-band GNSS-R ocean surface measurements;Balasubramaniam;Remote Sens. Environ.,2020

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