Six Lighthouse Applications are being established in EarthServer, each of which poses distinct challenges on Earth Data Analytics: Cryospheric Science Airborne Science, Atmospheric Science, Geology, Oceanography, and Planetary Science. Altogether, they cover all Earth Science domains; the Planetary Science use case has been added to challenge concepts and standards in non-standard environments. Technology relies on the innovative Big Data Analytics technology developed in EarthServer. Installations are being done at the partner sites, prepared for sustained operation beyond the project. Alongside with the service as such, software, best practices, and trainings are being developed as elements of the project's outreach activities.
EarthLook demonstrates how OGC standards can help achieving fast, flexible, and open coverage services. Based on the rasdaman Big Array Analytics Server, access, processing, and filtering on 1-D through 4-D coverage data can be explored interactively. All service interfaces implement OGC standards.
|The Cryospheric Data Service is developed by EOX and will, in the final stage, support the snow and land ice community by providing an online data archive and processing facility for relevant products. Currently, the service holds a selection of Snow Cover Products created by CryoLand, a Collaborative EU-FP7 Project (2011-2015).|
The Atmospheric Data Service is developed by MEEO with the aim of supportign the Climate and Atmosphere communities in loading, visualizing and analyising 3D and 4D datasets at European and global scale. COMETA has developed the repository of MERIS data.Related Applications
| Geology Data Service |
|The Ocean Data Service is developed by PML and is intended to provide a portal to EO data for the Ocean Science community. Currently the service demonstrates the use of WCPS queries in querying sample ocean colour datasets.|
The Planetary Data Service offers orbital spacecraft data over Mars. PlanetServer aims at providing access and analysis capabilities to Mars Remote Sensing data. Ingested datasets include panchromatic, hyperspectral and topography data, at multiple spatial scales.