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Machine Learning Methods for Ozone Total Column Retrieval from Sentinel-5 Precursor Data: Application to Synthetic and Real Measurements

Jain, Himani (2019) Machine Learning Methods for Ozone Total Column Retrieval from Sentinel-5 Precursor Data: Application to Synthetic and Real Measurements. Master's, TU Berlin.

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Item URL in elib:https://elib.dlr.de/133727/
Document Type:Thesis (Master's)
Title:Machine Learning Methods for Ozone Total Column Retrieval from Sentinel-5 Precursor Data: Application to Synthetic and Real Measurements
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Jain, Himanihimani.jain (at) lr.deUNSPECIFIED
Date:2019
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:86
Status:Published
Keywords:machine learning, remote sensing
Institution:TU Berlin
Department:Electrical Engineering and Computer Science
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Atmosphären- und Klimaforschung, R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Efremenko, Dr Dmitry
Deposited On:21 Jan 2020 13:01
Last Modified:22 Jan 2020 09:52

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