Data Cube on Demand (DCoD): Generating an earth observation Data Cube anywhere in the world

•Facilitate the generation and provision of a Data Cube instance based on simple user requirements.•Users have to specify an area of interest; sensors; temporal frame; and provide an email address.•DCoD approach can reduce the burden of software installation, configuration and data ingestion.•Provid...

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Veröffentlicht in:International journal of applied earth observation and geoinformation 2020-05, Vol.87, p.102035, Article 102035
Hauptverfasser: Giuliani, Gregory, Chatenoux, Bruno, Piller, Thomas, Moser, Frédéric, Lacroix, Pierre
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Sprache:eng
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Zusammenfassung:•Facilitate the generation and provision of a Data Cube instance based on simple user requirements.•Users have to specify an area of interest; sensors; temporal frame; and provide an email address.•DCoD approach can reduce the burden of software installation, configuration and data ingestion.•Provides more flexibility and scalability as well as a strengthened sense of ownership. To tackle Big Data challenges such as Volume, Variety, and Velocity, the Earth Observations Data Cube (EODC) concept has emerged as a solution for lowering barriers and offering new possibilities to harness the information power of satellite EO data. However, installing, configuring, and managing an EODC instance is still difficult requiring specific knowledge and capabilities. Consequently, facilitating and automating the generation and provision of EODC given specific user’s requirements can be beneficial. In response to this issue, this paper presents the Data Cube on Demand (DCoD) approach, a proof-of-concept that aims at facilitating the generation and use of an EODC instance virtually anywhere in the World. Users are only required to specify an area of interest; select the types of sensors between Landsat 5-7-8 and Sentinel-2; choose a desired temporal frame; and provide their email address to receive notifications. Then automatically an empty ODC instance is instantiated and desired data are ingested. The proposed approach has been successfully tested in two sites in Bolivia and DRC in the field of environmental monitoring. It has lowered many complexity barriers of such a new technology; greatly facilitated the generation and use of the Data Cube technology; enhanced data sovereignty; and ultimately can help reaching large adoption and acceptance.
ISSN:1569-8432
1872-826X
DOI:10.1016/j.jag.2019.102035