International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Volume XLII-3/W11
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W11, 15–16, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W11-15-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W11, 15–16, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W11-15-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Feb 2020

14 Feb 2020

REALTIME PLANETARY-SCALE DATACUBE FUSION

P. Baumann P. Baumann
  • Jacobs University, Bremen, Germany

Keywords: datacube, fusion, distributed processing, query planning, rasdaman

Abstract. The datacube model has rapidly gained acceptance as a cornerstone for analysis-ready data, and also the corresponding service model which is more powerful, but easier to use than existing API-based interfaces. Mature and widely adopted datacube standards show the way how datacube functionality can be presented to clients, be they human or m2m connections. Specifically, the OGC Coverage Implementation Schema (CIS) data model and the Web Coverage Service (WCS) service model suite define a framework adopted by the main opensource as well as proprietary tools, including MapServer, GeoServer, GDAL, QGIS, ArcGIS, and python/OWSlib.

In this contribution we present federation methods implemented in the rasdaman datacube engine which is accepted technology leader, standards driver, and reference implementation for datacubes.

In summary, rasdaman allows federated processing of declarative queries whereby complete location transparency is given: any federation member can receive the query, and the federation will dynamically orchestrate each query individually for optimized processing.