Data science for understanding physics – modelling ship wake detectability using machine learning

Tings, Björn and Kortum, Karl (2024) Data science for understanding physics – modelling ship wake detectability using machine learning. DLR International Conference on Geoinformation Data, Processing and Application (GeoDPA 2024), 2024-04-23 - 2024-04-25, Oldenburg, Germany.

PDF
1MB

Official URL: https://geodpa2024.welcome-manager.de/front/index.php

Item URL in elib:

https://elib.dlr.de/203328/

Document Type:

Conference or Workshop Item (Poster)

Title:

Data science for understanding physics – modelling ship wake detectability using machine learning

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Tings, Björn	UNSPECIFIED	https://orcid.org/0000-0002-1945-6433	UNSPECIFIED
Kortum, Karl	UNSPECIFIED	https://orcid.org/0000-0002-8418-6484	UNSPECIFIED

Date:

24 April 2024

Refereed publication:

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

SAR, sea surface roughness, sea state, Oceanography

Event Title:

DLR International Conference on Geoinformation Data, Processing and Application (GeoDPA 2024)

Event Location:

Oldenburg, Germany

Event Type:

international Conference

Event Start Date:

23 April 2024

Event End Date:

25 April 2024

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 - SAR methods

Location:

Bremen , Oberpfaffenhofen

Institutes and Institutions:

Remote Sensing Technology Institute > SAR Signal Processing

Deposited By:

Kaps, Ruth

Deposited On:

26 Apr 2024 12:03

Last Modified:

21 Feb 2025 12:12

Repository Staff Only: item control page