Year: 2021
Type: article
Abstract: 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.
Source: GI_Forum
Authors: Nicole Hein, Jörg Blankenbach
Institution: RWTH Aachen University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $539
OpenAlex ID: W3173390116