The ADAM platform

Operational Earth Observation (EO) satellite missions are entering their 5^th lifetime decade, and the need to access historical data has strongly increased, particularly for long-term science and environmental monitoring applications. This trend that drives users to request long time-series of data will increase even more in the future, in particular regarding the interest on global change assessment and monitoring to support policy makers decisions on atmosphere, ocean, cryosphere, carbon and other biogeochemical cycles safeguard.

The Copernicus initiative (https://www.copernicus.eu) is playing a unique and unprecedented role form the point of view of amount, relevance and quality of provided environmental data. In the frame of the European Commission funded activities, the Data and Information Access Service (DIAS) are operated by five different consortia to acquire, process, archive and distribute data from Copernicus and Third-Party Missions.

With this enormous availability of past, present, and future geospatial environmental data, there is the need to make users able to identify the datasets that best fit with their needs and obtain these data in fastest and easiest-to-use possible way. The Advanced geospatial DAta Management - ADAM platform (https://adamplatform.eu/) provides discovery, access, processing and visualization services for data in the distributed cloud environment, significantly reducing the burden of data usability.

ADAM allows the exploitation of the content of EO data archives extended from a few years to decades and therefore makes their continuously increasing scientific value fully accessible. The advances in satellite sensor characteristics (spatial resolution, temporal frequency, spectral sensors) as well as in all related technical aspects (data and metadata format, storage, infrastructures) underline the strong need to preserve the EO space data without time constraints and to keep them accessible and exploitable, as they constitute a humankind asset. This is a typical big data challenge that ADAM can face.  

This paper describes the ADAM platform and various application domains supported with its data science analytics and visualization capabilities.