openEO Platform – showcasing a federated, accessible platform for reproducible large-scale Earth Observation analysis 

<p>openEO Platform holds a large amount of free and open as well as commercial Earth Observation (EO) data which can be accessed and analysed with openEO, an open API that enables cloud computing and EO data access in a unified and reproducible way. Additionally, client libraries are available in R, Python and Javascript. A JupterLab environment and the Web Editor, a graphical interface, allow a direct and interactive development of processing workflows. The platform is developed with a strong user focus and various use cases have been implemented to illustrate the platform capabilities. Currently, three federated backends support the analysis of EO data from pixel to continental scale. &#160;</p> <p>The use cases implemented during the platform&#8217;s main development phase include a dynamic landcover mapping, an on-demand analysis-ready-data creation for Sentinel-1 GRD, Sentinel-2 MSI and Landsat data, time series-based forest dynamics analysis with prediction functionalities, feature engineering for crop type mapping and large-scale fractional canopy mapping. Additionally, three new use cases are being developed by platform users. These include large scale vessel detection based on Sentinel-1 and Sentinel-2 data, surface water indicators using the ESA World Water toolbox for a user-defined area of interest and monitoring of air quality parameters using Sentinel-5P data.&#160;</p> <p>The future evolution of openEO Platform in terms of data availability and processing capabilities closely linked to community requirements, facilitated by feature requests from users who design their workflows for environmental monitoring and reproducible research purposes. This presentation provides an overview of the completed use cases, the newly added functionalities such as user code sharing, and user interface updates based on the new use cases and user requests. openEO Platform exemplifies how the processing and analysing large amounts of EO data to meaningful information products is becoming easier and largely compliant with FAIR data principles supporting the EO community at large.&#160;</p>