The project, part of the ESA Discovery Campaign on Remote Sensing of Plastic Marine Litter, developed a method to estimate floating macroplastic accumulation and transport rates in rivers using remote sensing. It combined the detection of floating water hyacinths using Sentinel-2 and Sentinel-1 with in-situ estimates of macroplastic densities carried by this invasive aquatic weed. Water hyacinths typically form large patches of several meters of width and length, and can thus be detected from space.

Payload data transmitters in Earth Observation (EO) missions are moving from X-band to K-band (i.e. 25.5 to 27 GHz), where the downlink data rates can be increased due to the four times higher availability of bandwidth than in X-band. In addition, an interest is certainly growing in the field of small-size satellites and cube-sats. Therefore, there is a need to reduce the size/mass of the K-Band transmitter while increasing the DC-to-RF efficiency in order to relax the constraints of the thermal management systems at platform level.

The main objective of this study was to evaluate the merits of a dual-camera setup to acquire high-resolution images of identified events of iinterest, on board, through AI methods. A mission analysis of the approach for a single-satellite, dual camera setup as well as for a two-satellite (leading-trailing), single camera setup was performed. The dual-camera AI approach was demonstrated on commercially available high-performance embedded computers (Xilinx Kria SoM / Google Edge TPU SoM) through a state-of-the-art active fire detection use case.

While AI technologies have shown promise in various applications in the space industry, their adoption within spacecraft flight software has yet to happen in a significant manner. This is due to a number of factors, including the relatively low computing power available onboard traditional spacecraft, the long development process required in the industry and the lack of opportunities for in-orbit demonstrations. In ESA's OPS-SAT satellite, Airbus teams identified a unique opportunity to quickly test promising algorithms in orbit as the industry seeks to resolve the issues listed above.

Early space missions consisted of bespoke components communicating with facilities on Earth. Today this model has been updated with off-the-shelf components and reusable launch systems that lower mission cost into low-Earth orbit. Extending this model to develop a sustainable off-Earth economy requires bringing the concept of reconfigurable computing agents to deep space.

Persistent Responsive Real-Time Earth Observation small satellite constellation mission (PERTEO) was a study dedicated to providing a global democratic service to support disaster management. Earth observation and satellite-based communications play a key role in supporting disaster management targeting responsiveness and the persistence of the service. In the terminology of on-demand Copernicus services, responsiveness is determined by the lead-time and latency. The persistence is determined by the availability and by the revisit time of the service.

Radioisotope generators provide electrical power for spacecraft by converting the energy released by the decay of radioisotope fuel into electricity. Non-thermal converters (voltaic devices) make use of the photoelectric effect much in the same way a solar cell does. They are much easier to miniaturise for future chip-sized deep space probes, however performance quickly degrades due to radiation damage.

The use of optical (laser) feeder-links for next generation telecommunication satellites is receiving strong interest from commercial telecommunication providers because it will soon not be possible to support the projected growth in bandwidth using radio frequency bands (e.g. Ka-band). Moving to higher radio frequencies such as the Q/V or W-bands does not dramatically improve available bandwidth, while it increases atmospheric attenuation to a level comparable with the laser communication bands. Cloud coverage can be mitigated by site diversity, namely by using multiple (e.g.