Breaking the big data barrier by enhancing on-board sensor flexibility

Abstract

Modern sensors, such as hyperspectral cameras, deliver massive amounts of data. On board of satellites, the high volume is paired with low bandwidth and part-time availability, during overpasses. This leads to well-known availability problems and bottlenecks in today's remote sensing. We address this challenge by enhancing the on-board system with flexible filtering and processing capabilities based on the Array Analytics engine, rasdaman. Users then can exact request, which can lead to substantially decreased data traffic. Our project has been accepted for a CubeSat mission for which rasdaman now has been prepared. We present the project setup and core extensions done to rasdaman to this end.