The DTN-EO study was initiated in order to research the performance of DTN in future missions, particularly Earth observation and constellation-type missions. In the original proposal, ESA stipulated three scenarios which were to be tested: Earth observation, constellation, and exploration missions. These scenarios built upon each other, starting with an Earth observation-centric mission such as the Sentinel missions, before moving to a large constellation. Ultimately, the DTN network from the first two scenarios was expanded to represent a deep-space exploration mission.

The main scope of this activity was to foster the exchange of expertise between the European Lidar Network (EARLINET) and Latin America Lidar Network (LALINET), and demonstrate the capability of joint research, setting the groundwork for GALION (The Global Atmosphere Watch Aerosol Lidar Observation Network) and future calibration/validation of ESA’s atmospheric satellite missions such as Aeolus and EarthCARE.

The basic goal of this project was to analyse how the usage of non-conventional data (i.e. 'data of opportunity') in conjunction with conventional data could help improve the estimation of parameters for weather and space weather. Conventional data it is considered to be data coming from well-known sources such as permanent GNSS receivers (e.g. receivers from IGS or EUREF networks) while non-conventional data is considered to be GNSS data from research vessels or mass-market GNSS receivers (such as smartphones or other single-frequency GNSS chipsets).

The development of High Altitude Pseudo-Satellites (HAPS) has reached an outstanding level of maturity, with several flight demonstrations that augur soon to have operational capabilities. ESA, aware of the synergies among satellite and HAPS services, set up the HAPPIEST study to analyse the impact of the erruption of aerostatic HAPS into the telecommunications market, currently covered by space and terrestrial networks. Furthermore, some complementary payloads can serve interesting applications such as Earth observation and navigation services.

The main objectives of this project were to develop the tools and structure to enable routine EarthCARE radar and lidar observations of clouds to be assimilated in the ECMWF Numerical Weather Prediction model and to prepare for the real-time monitoring of the observations to detect instrument degradation or errors. This required adjustments of assimilation tools, such as the observation operators, observation error definition, quality control, data screening and bias correction.

This activity presents a Synthetic Aperture Radar (SAR) simulator designed to assess the performance of bi-static SAR missions. It is a modular software able to simulate realistic SAR data (including injection of the system non-idealities), to estimate the SAR performance at radiometric and interferometric level. In order to ensure accurate measures of the bi-static performance, it simulates raw data exploiting a time-domain approach, without assumptions on the acquisition geometry. This feature makes the simulator a useful tool for the design of new SAR missions concepts.

The difficult and costly access to reliable and quality Earth Observation (EO) satellite data has historically often limited the development of operational and sustainable services in multiple application domains (among which Disaster Risk Management) and, as a consequence, it has impaired the benefit that the society could have been receiving back as a return of huge multi annual investments in the space sector.

Shannon-Nyquist theorem rules the signal sampling stating that the signal must be sampled at a rate of at least twice the maximum frequency present in the signal to be fully reconstructed. Compressive Sensing (CS) theory affirms that a sparse signal can be efficiently reconstructed by the acquisition of a number of samples far below the minimal one dictated by Nyquist theorem, thus providing a new approach to data acquisition. CS technique is based on the concept of sparsity. The information rate of a continuous 'sparse' signal may be much smaller than suggested by its bandwidth.

The Process Exploration through Measurement of infrared and millimetre-wave Emitted Radiation (PREMIER) instrument was proposed to ESA within the framework of the 7th Earth Explorer Call. The instrument was designed to quantify dynamic, radiative, and chemical processes in the upper troposphere and lower stratosphere (UTLS) that control the global atmospheric composition.

Space-based radio echo sounding of the continental ice sheets can potentially provide full coverage with uniform sampling and data quality as well as detection of change in environmentally sensitive areas. This research addresses the feasibility of sounding the Antarctic ice sheets with a space-based P-band radar. The assessment makes use of an electromagnetic model of the ice sheets where most of the model parameters are estimated from data that have been acquired in Antarctica with an airborne P-band ice sounding radar.