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. 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/191586/

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:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Diniz Dal Molin Junior, Ricardo Simao	UNSPECIFIED	https://orcid.org/0000-0003-4103-7910	UNSPECIFIED
Rizzoli, Paola	UNSPECIFIED	https://orcid.org/0000-0001-9118-2732	UNSPECIFIED

Date:

2022

Journal or Publication Title:

ESA Living Planet Symposium 2022

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

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:

05 Dec 2022 10:09

Last Modified:

13 Jan 2023 17:40

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