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Deep Learning for Land Cover Classification from Sentinel-1 InSAR Short-Time-Series in the Amazon Forest

Diniz Dal Molin Junior, Ricardo Simao and Rizzoli, Paola (2022) Deep Learning for Land Cover Classification from Sentinel-1 InSAR Short-Time-Series in the Amazon Forest. ESA Living Planet Symposium, 2022-05-23 - 2022-05-27, Bonn, Germany.

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Item URL in elib:https://elib.dlr.de/186249/
Document Type:Conference or Workshop Item (Speech)
Title:Deep Learning for Land Cover Classification from Sentinel-1 InSAR Short-Time-Series in the Amazon Forest
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Diniz Dal Molin Junior, Ricardo Simaoricardo.dinizdalmolinjunior (at) dlr.deUNSPECIFIED
Rizzoli, PaolaPaola.Rizzoli (at) dlr.dehttps://orcid.org/0000-0001-9118-2732
Date:2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Accepted
Keywords:convolutional neural networks; Synthetic Aperture Radar; Sentinel-1; forest mapping; deforestation monitoring; deep learning;
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: Diniz Dal Molin Junior, Ricardo Simao
Deposited On:02 May 2022 14:57
Last Modified:02 May 2022 14:57

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