DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Knowledge extraction from Copernicus satellite data

Dumitru, Corneliu Octavian and Schwarz, Gottfried and Datcu, Mihai (2020) Knowledge extraction from Copernicus satellite data. IOP Conference Series : Materials Science and Engineering, pp. 1-2. Institute of Physics (IOP) Publishing. ISSN 1757-8981

Full text not available from this repository.

Official URL: https://isde2019.iopconferenceseries.rivervalleytechnologies.com/


We describe two alternative approaches of how to extract knowledge from high- and medium-resolution Synthetic Aperture Radar (SAR) images of the European Sentinel-1 satellites. To this end, we selected two basic types of images, namely images depicting arctic shipping routes with icebergs, and - in contrast - coastal areas with various types of land use and human-made facilities. In both cases, the extracted knowledge is delivered as (semantic) categories (i.e., local content labels) of adjacent image patches from big SAR images. Then, machine learning strategies helped us design and validate two automated knowledge extraction systems that can be extended for the understanding of multispectral satellite images.

Item URL in elib:https://elib.dlr.de/131718/
Document Type:Article
Title:Knowledge extraction from Copernicus satellite data
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Dumitru, Corneliu OctavianCorneliu.Dumitru (at) dlr.deUNSPECIFIED
Schwarz, GottfriedGottfried.Schwarz (at) dlr.deUNSPECIFIED
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Journal or Publication Title:IOP Conference Series : Materials Science and Engineering
Refereed publication:No
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:No
Page Range:pp. 1-2
Publisher:Institute of Physics (IOP) Publishing
Keywords:SAR, semantics, Sentinel-2, land cover, polar areas
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Dumitru, Corneliu Octavian
Deposited On:04 Dec 2019 10:21
Last Modified:05 Dec 2019 12:55

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.