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Assessing Sentinel-1 InSAR Short-Time-Series for Systematic Rainforest Mapping with Deep Learning

Diniz Dal Molin Junior, Ricardo Simao and Rizzoli, Paola (2022) Assessing Sentinel-1 InSAR Short-Time-Series for Systematic Rainforest Mapping with Deep Learning. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR. European Conference on Synthetic Aperture Radar (EUSAR), 2022-07-25 - 2022-07-27, Leipzig, Germany. ISBN 978-3-8007-5823-4. ISSN 2197-4403.

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Item URL in elib:https://elib.dlr.de/191513/
Document Type:Conference or Workshop Item (Speech)
Title:Assessing Sentinel-1 InSAR Short-Time-Series for Systematic Rainforest Mapping with Deep Learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Diniz Dal Molin Junior, Ricardo SimaoUNSPECIFIEDhttps://orcid.org/0000-0003-4103-7910UNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:2022
Journal or Publication Title:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
ISSN:2197-4403
ISBN:978-3-8007-5823-4
Status:Published
Keywords:Forest mapping; Deep Learning; Synthetic Aperture Radar (SAR); Sentinel-1
Event Title:European Conference on Synthetic Aperture Radar (EUSAR)
Event Location:Leipzig, Germany
Event Type:international Conference
Event Start Date:25 July 2022
Event End Date:27 July 2022
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:05 Dec 2022 09:28
Last Modified:24 Apr 2024 20:52

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