Geospatial extrapolation of time-series data with deep learning

Schollerer, Lea and Geiß, Christian and Zhu, Yue and Maier, Jana (2023) Geospatial extrapolation of time-series data with deep learning. 4. EO-Symposium „Neue Perspektiven der Erdbeobachtung“, 2023-06-26 - 2023-06-28, Bonn, Deutschland.

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Official URL: https://www.dialogplattform-erdbeobachtung.de/downloads/poster2023/Poster_EO_Symposium_final.pdf

Item URL in elib:

https://elib.dlr.de/202467/

Document Type:

Conference or Workshop Item (Poster)

Title:

Geospatial extrapolation of time-series data with deep learning

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Schollerer, Lea	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Geiß, Christian	UNSPECIFIED	https://orcid.org/0000-0002-7961-8553	UNSPECIFIED
Zhu, Yue	ETH Zürich	UNSPECIFIED	UNSPECIFIED
Maier, Jana	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

Date:

June 2023

Refereed publication:

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

future prediction, time series data, LSTM model, exposure analysis, population distribution, PARATUS

Event Title:

4. EO-Symposium „Neue Perspektiven der Erdbeobachtung“

Event Location:

Bonn, Deutschland

Event Type:

international Conference

Event Start Date:

26 June 2023

Event End Date:

28 June 2023

Organizer:

Deutsche Raumfahrtagentur im DLR

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 - Remote Sensing and Geo Research

Location:

Oberpfaffenhofen

Institutes and Institutions:

German Remote Sensing Data Center > Geo Risks and Civil Security

Deposited By:

Schollerer, Lea

Deposited On:

04 Mar 2024 10:22

Last Modified:

24 Apr 2024 21:02

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