With the unprecedented increase of orbital sensor, in situ measurement, and simulation data there is a rich, yet not leveraged potential for obtaining insights from dissecting datasets and rejoining them with other datasets. Obviously, goal is to allow users to "ask any question, any time, on any size", thereby enabling them to "build their own product on the go".One of the most influential initiatives in EO is EarthServer which has demonstrated new directions for flexible, scalable EO services based on innovative NoSQL
The lack of open-source tools for hyperspectral data visualization and analysis creates a demand for new tools. In this paper we present the new PlanetServer, a set of tools comprising a web Geographic Information System (GIS) and a recently developed Python Application Programming Interface (API) capable of visualizing and analyzing a wide variety of hyperspectral data from different planetary bodies. Current WebGIS open-source tools are evaluated in order to give an overview and contextualize how PlanetServer can help in this matters. The web client is thoroughly described as well as the datasets available in PlanetServer. Also, the Python API is described and exposed the reason of its development. Two different examples of mineral characterization of different hydrosilicates such as chlorites, prehnites and kaolinites in the Nili Fossae area on Mars are presented. As the obtained results show positive outcome in hyperspectral analysis and visualization compared to previous literature, we suggest using the PlanetServer approach for such investigations.
Virtual Observatory tools are specifically designed for astronomical data, but they can be adapted to work with geospatial data by providing existing Geographical Information System tools with Simple Application Messaging Protocol interface. Open source QGIS package was chosen as a platform for this. The Simple Application Messaging Protocol interface was made with Python plug‐ins. Geospatial data were exposed to Virtual European Solar and Planetary Access via a dedicated German Astronomical Virtual Observatory Data Center Helper Suite server and several tables exposing existing Open Geospatial Consortium—compliant planetary services were published to Virtual European Solar and Planetary Access providing a variety of geospatial data types: vector data and spectral cube rasters, as well as Open Geospatial Consortium Web Map Service of planetary maps.
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