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Sentinel-1 and TanDEM-X InSAR Coherence for monitoring forests using Deep Learning

Rizzoli, Paola and Diniz Dal Molin Junior, Ricardo Simao and Carcereri, Daniel and Bueso Bello, Jose Luis (2023) Sentinel-1 and TanDEM-X InSAR Coherence for monitoring forests using Deep Learning. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2023-07-16 - 2023-07-21, Pasadena, USA.

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Item URL in elib:https://elib.dlr.de/194829/
Document Type:Conference or Workshop Item (Speech)
Title:Sentinel-1 and TanDEM-X InSAR Coherence for monitoring forests using Deep Learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Diniz Dal Molin Junior, Ricardo SimaoUNSPECIFIEDhttps://orcid.org/0000-0003-4103-7910UNSPECIFIED
Carcereri, DanielUNSPECIFIEDhttps://orcid.org/0000-0002-3956-1409UNSPECIFIED
Bueso Bello, Jose LuisUNSPECIFIEDhttps://orcid.org/0000-0003-3464-2186UNSPECIFIED
Date:2023
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:TanDEM-X, Sentinel-1, coherence, vegetation, deep learning
Event Title:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Event Location:Pasadena, USA
Event Type:international Conference
Event Dates:2023-07-16 - 2023-07-21
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 - AI4SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute
Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Rizzoli, Paola
Deposited On:02 May 2023 10:39
Last Modified:22 Sep 2023 11:46

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