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Multi-Sensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery

Ebel, Patrick and Meraner, Andrea and Schmitt, Michael and Zhu, Xiao Xiang (2021) Multi-Sensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery. IEEE Transactions on Geoscience and Remote Sensing. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.3024744. ISSN 0196-2892. (In Press)

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Official URL: https://ieeexplore.ieee.org/document/9211498


Item URL in elib:https://elib.dlr.de/138015/
Document Type:Article
Title:Multi-Sensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ebel, PatrickTUMUNSPECIFIED
Meraner, AndreaSignal Processing in Earth Observation Group, Technical University of MunichUNSPECIFIED
Schmitt, MichaelTUMUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:2021
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1109/TGRS.2020.3024744
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:In Press
Keywords:Cloud removal, data fusion, deep learning, generative adversarial network (GAN), optical imagery, synthetic aperture radar (SAR)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Liu, Rong
Deposited On:26 Nov 2020 11:31
Last Modified:14 Jan 2021 13:29

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