Even though recent developments have simplified access to Copernicus Earth observation data, one of the biggest challenges in EO is converting satellite data into reliable information. The new solution SIAM-as-a-Service (SIAMaaS) serves as a building block for image interpretation tasks worldwide by fully automating semantic enrichment (spectral categorisation) of Sentinel-2 images in near-real time. The solution is based on Satellite Image Automated Mapper (SIAM™), which is software with a proven, knowledge-based decision tree. The service grants on-demand access to semantic enrichment, thereby covering the first step in effective and fully automated analysis of big EO data. Unlike other approaches, it works without training samples, is reproducible and not limited to selected geographic areas (application domains), and comes at an affordable price. SIAMaaS meets the global demand for converting EO data into viable information using reproducible, repeatable, transferable, and automated methods – all in near-real time.

Univ. Salzburg, Department of Geoinformatics – Z_GIS
Martin Sudmanns, Hannah Augustin, Dirk Tiede and Andrea Baraldi