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GI_Forum 2021, Volume 9, Issue 112th International Symposium on Digital Earth
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2021, Volume 9, Issue 1, pp. 76-84, 2021/06/29
12th International Symposium on Digital Earth
Database systems capable of efficiently storing geospatial data are widespread. However, recent developments in earth observation systems, remote sensing, mobile mapping, and crowd sourcing lead to large amounts of geospatial mass data that can hardly be handled efficiently with the existing solutions. Especially large geospatial raster data require novel concepts for well-organized data storage. A concept for storage of large geospatially and temporally referenced image data using the NoSQL graph database system Neo4j as a research subject of the project “RiverView®” is introduced. New strategies and access structures have been developed to ensure the persistence and performant access to image data in Neo4j. These strategies are compared with the up-and download performance of the widespread Rasdaman array database system.
Keywords: geospatial raster database, graph database, big geo data, image database, Neo4j