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Multilayer Architecture for Heterogeneous Geospatial Data Analytics: Querying and Understanding EO Archives

Alonso, Kevin and Espinoza-Molina, Daniela and Datcu, Mihai (2017) Multilayer Architecture for Heterogeneous Geospatial Data Analytics: Querying and Understanding EO Archives. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (3), pp. 791-801. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2017.2649040 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/document/7843650/

Abstract

The constantly growing process of the Earth Observation (EO) data and their heterogeneity require new systems and tools for effectively querying and understanding the available data archives. In this paper, we present a tool for heterogeneous geospatial data analytics. The system implements different web technologies in a multilayer server–client architecture, allowing the user to visually analyze satellite images, maps, and in-situ information. Specifically, the information managed is composed of EO multispectral and synthetic aperture radar products along with the multitemporal in-situ LUCAS surveys. The integration of these data provides a very useful information during the EO scene interpretation process. The system also offers interactive tools for the detection of optimal datasets for EO multitemporal image change detection, providing at the same time ground-truth points for both human and machine analyses. Furthermore, we show by means of visual analytic representations a way to analyze and understand the content and distribution of the EO databases.

Item URL in elib:https://elib.dlr.de/111298/
Document Type:Article
Title:Multilayer Architecture for Heterogeneous Geospatial Data Analytics: Querying and Understanding EO Archives
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Alonso, Kevinkevin.alosonogonzales (at) dlr.deUNSPECIFIED
Espinoza-Molina, Danieladaniela.espinozamolina (at) dlr.deUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:March 2017
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:10
DOI :10.1109/JSTARS.2017.2649040
Page Range:pp. 791-801
Editors:
EditorsEmail
Qian, (Jenny) Dudu@ece.msstate.edu
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:synthetic aperture radar (SAR), Big data, data integration, geographic information systems (GIS), LUCAS
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 > Photogrammetry and Image Analysis
Deposited By:INVALID USER
Deposited On:08 Mar 2017 12:58
Last Modified:31 Jul 2019 20:08

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