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A CNN-based approach for forest parameter regression by fusion of Sentinel-2 and TanDEM-X data

Carcereri, Daniel and Rizzoli, Paola and Ienco, Dino and Bueso Bello, Jose Luis and Gonzalez, Carolina and Bruzzone, Lorenzo (2022) A CNN-based approach for forest parameter regression by fusion of Sentinel-2 and TanDEM-X data. In: ESA Living Planet Symposium 2022. ESA Living Planet Symposium, 2022-05-23 - 2022-05-27, Bonn, Germany.

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Item URL in elib:https://elib.dlr.de/186248/
Document Type:Conference or Workshop Item (Speech)
Title:A CNN-based approach for forest parameter regression by fusion of Sentinel-2 and TanDEM-X data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Carcereri, DanielDaniel.Carcereri (at) dlr.dehttps://orcid.org/0000-0002-3956-1409
Rizzoli, PaolaPaola.Rizzoli (at) dlr.dehttps://orcid.org/0000-0001-9118-2732
Ienco, Dinodino.ienco (at) inrae.frhttps://orcid.org/0000-0002-8736-3132
Bueso Bello, Jose LuisJose-Luis.Bueso-Bello (at) dlr.dehttps://orcid.org/0000-0003-3464-2186
Gonzalez, Carolinacarolina.gonzalez (at) dlr.dehttps://orcid.org/0000-0002-9340-1887
Bruzzone, Lorenzolorenzo.bruzzone (at) unitn.ithttps://orcid.org/0000-0002-6036-459X
Date:2022
Journal or Publication Title:ESA Living Planet Symposium 2022
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-2, Above Ground Biomass
Event Title:ESA Living Planet Symposium
Event Location:Bonn, Germany
Event Type:international Conference
Event Dates:2022-05-23 - 2022-05-27
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: Carcereri, Daniel
Deposited On:02 May 2022 14:56
Last Modified:13 Jan 2023 17:40

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