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The Digital Earth Observation Librarian: A Data Mining Approach for Large Satellite Images Archives

Datcu, Mihai and Grivei, Alexandru Cosmin and Espinoza Molina, Daniela and Dumitru, Corneliu Octavian and Reck, Christoph and Manilici, Vlad and Schwarz, Gottfried (2020) The Digital Earth Observation Librarian: A Data Mining Approach for Large Satellite Images Archives. Big Earth Data, 4 (3), pp. 265-294. Taylor & Francis. doi: 10.1080/20964471.2020.1738196. ISSN 2096-4471.

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Official URL: https://doi.org/10.1080/20964471.2020.1738196


Throughout the years, various Earth Observation (EO) satellites have generated huge amounts of data. The extraction of latent information in the data repositories is not a trivial task. New methodologies and tools, being capable of handling the size, complexity and variety of data, are required. Data scientists require support for the data manipulation, labeling and information extraction processes. This paper presents our Earth Observation Image Librarian (EOLib), a modular software framework which offers innovative image data mining capabilities for TerraSAR-X and EO image data, in general. The main goal of EOLib is to reduce the time needed to bring information to end-users from Payload Ground Segments (PGS). EOLib is composed of several modules which offer functionalities such as data ingestion, feature extraction from SAR (Synthetic Aperture Radar) data, meta-data extraction, semantic definition of the image content through machine learning and data mining methods, advanced querying of the image archives based on content, meta-data and semantic categories, as well as 3-D visualization of the processed images. EOLib is operated by DLR’s (German Aerospace Center’s) Multi-Mission Payload Ground Segment of its Remote Sensing Data Center at Oberpfaffenhofen, Germany.

Item URL in elib:https://elib.dlr.de/134309/
Document Type:Article
Title:The Digital Earth Observation Librarian: A Data Mining Approach for Large Satellite Images Archives
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Grivei, Alexandru CosminUniversity Politehnica of Bucharest, RomaniaUNSPECIFIED
Espinoza Molina, DanielaDaniela.EspinozaMolina (at) dlr.deUNSPECIFIED
Dumitru, Corneliu OctavianCorneliu.Dumitru (at) dlr.deUNSPECIFIED
Reck, ChristophChristoph.Reck (at) dlr.dehttps://orcid.org/0000-0002-4300-4920
Manilici, VladVlad.Manilici (at) dlr.deUNSPECIFIED
Schwarz, GottfriedGottfried.Schwarz (at) dlr.deUNSPECIFIED
Date:16 April 2020
Journal or Publication Title:Big Earth Data
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.1080/20964471.2020.1738196
Page Range:pp. 265-294
Publisher:Taylor & Francis
Keywords:Earth observation, TerraSAR-X, Data Mining System
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 - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
German Remote Sensing Data Center > Information Technology
Institute of Communication and Navigation > Institute Project Management and - Administration
Deposited By: Dumitru, Corneliu Octavian
Deposited On:05 Mar 2020 13:44
Last Modified:11 Jun 2021 04:13

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