Rasdaman as a platform for serving space-time raster data

Satellite imagery is an important source of raster data, with multiple applications in science and economy. Historical imagery together with growing archives of active satellite missions present big amounts of data. Sentinel-2 mission launched in 2015. is the last in row of satellite missions aimed at collecting global high resolution images with high time frequency. Data from this mission is freely available for scientific and commercial uses. Handling and analysing that data efficiently presents a challenge due to the size of the data - according to Sentinel-2 annual report for 2017, 10TB of data is generated daily, with size of overall data collected from this mission since launch exceeding 40PB. Raster databases offer a solution for fast, efficient and reliable handling of big aounts of raster data. This paper describes the results of testing rasdaman raster database, using a timeseries of Sentinel-2 images over test area.