Multi-Frequency SAR Retrieval of Sea Surface Wind Field

This study is to present the lesson learned during the activities related to the Italian Space Agency (ASI) funded APPLICAVEMARS project which aims at estimating sea surface wind field from L-, C- and X-band Synthetic Aperture Radar (SAR) imagery. The paper focuses on the X-band results and it descr...

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Bibliographic Details
Published inIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium pp. 1581 - 1584
Main Authors Nunziata, F., Migliaccio, M., Verlanti, A., Buono, A., Ferrentino, E., Alparone, M., Zecchetto, S., Zanchetta, A., Portabella, M., Grieco, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.07.2023
Subjects
Estimation
Geoscience and remote sensing
Neural networks
Ocean
Radar polarimetry
SAR
Sea surface
Sensitivity
Wind field
Wind speed
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Summary:This study is to present the lesson learned during the activities related to the Italian Space Agency (ASI) funded APPLICAVEMARS project which aims at estimating sea surface wind field from L-, C- and X-band Synthetic Aperture Radar (SAR) imagery. The paper focuses on the X-band results and it describes a new approach to estimate ancillary wind direction info from the SAR image itself using neural networks.
ISSN:2153-7003
DOI:10.1109/IGARSS52108.2023.10282177