Amazon Rainforest Monitoring with TanDEM-X and Deep Learning Strategies

Bueso Bello, Jose Luis and Carcereri, Daniel and Rizzoli, Paola (2022) Amazon Rainforest Monitoring with TanDEM-X and Deep Learning Strategies. 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/186252/

Document Type:

Conference or Workshop Item (Poster)

Title:

Amazon Rainforest Monitoring with TanDEM-X and Deep Learning Strategies

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD
Bueso Bello, Jose Luis	UNSPECIFIED	https://orcid.org/0000-0003-3464-2186
Carcereri, Daniel	UNSPECIFIED	https://orcid.org/0000-0002-3956-1409
Rizzoli, Paola	UNSPECIFIED	https://orcid.org/0000-0001-9118-2732

Date:

May 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:

Synthetic Aperture Radar, TanDEM-X, rainforest, tropical forest, forest mapping, deforestation monitoring, deep learning, convolutional neural network

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 - Support TerraSAR-X/TanDEM-X operations

Location:

Oberpfaffenhofen

Institutes and Institutions:

Microwaves and Radar Institute
Microwaves and Radar Institute > Spaceborne SAR Systems

Deposited By:

Bueso Bello, Jose Luis

Deposited On:

02 May 2022 14:59

Last Modified:

13 Jan 2023 17:35

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