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Sentinel-4 is an imaging UVN (UV-VIS-NIR) spectrometer, developed by Airbus Defence and Space as prime contractor under ESA contract in the frame of the joint EU/ESA COPERNICUS program. The mission objective is the operational monitoring of trace gas concentrations for atmospheric chemistry and climate applications. This paper gives an overview of the Sentinel-4 system architecture, its design & development status.

Sentinel-4 is an imaging UVN (UV-VIS-NIR) spectrometer, developed by Airbus DS under ESA contract in the frame of the joint EU/ESA COPERNICUS program. The mission objective is the operational monitoring of trace gas concentrations for atmospheric chemistry and climate applications – hence the motto of Sentinel-4 “Knowing what we breathe”.

Copernicus is a European Union (EU) led initiative designed to establish a European capacity for the provision and use of operational monitoring information for environment and security applications. Within the Copernicus program, ESA is responsible for the development of the Space Component and Ground Segment..

The applications of remote sensing in hydrology are diverse and offer significant benefits for water monitoring. Up to now, operational river monitoring and sediment management in Germany mainly rely on in-situ measurements and on results obtained from numerical modelling. Remote sensing by satellites has a great potential to supplement existing data with two-dimensional information on near-surface turbidity distributions at greater spatial scales than in-situ measurements can offer. Within the project WasMon-CT (WaterMonitoring-Chlorophyll/Turbidity), the Federal Institute of Hydrology (BfG) aims at the implementation of an operational monitoring of turbidity distributions based on satellite images (esp. Sentinel-2, Landsat7 and 8). Initially, selected federal inland and estuarine waterways will be addressed: Rhine, Elbe, Ems, Weser. WasMon-CT is funded within the German Copernicus activities. Within the project, a database of atmospherically corrected, geo-referenced turbidity data will be assembled. The collected corresponding meta-data will include aspects of satellite data as well as hydrological data, e.g. cloud cover and river run-off. Based on this catalogue of spatially linked meta-data, the satellite data will be selected by e.g. cloud cover or run-off. The permanently updated database will include past as well as recent satellite images. It is designed with a long-term perspective to optimize the existing in-situ measurement network, which will serve partly for calibration and partly as validation data set. The aim is to extend, but not to substitute, the existing frequent point measurements with spatially extensive, satellite-derived data from the near surface part of the water column. Here, turbidity is used as proxy for corresponding suspended sediment concentrations. For this, the relationship between turbidity and suspended sediment concentrations will be investigated. Products as e.g. longitudinal profiles or virtual measurement stations will be developed from an application toolbox to specifically match requirements of operational monitoring tasks and to allow for a better integration into the existing monitoring system. The toolbox demonstrates the benefits of remote sensing by applying the established processing chain to diverse hydrological questions, such as for the investigation of tidal-affected sediment loads or mixing processes at river confluences. This new application will be of great value to assess, evaluate and monitor the status or the change of large-scale sediment processes at the system level. Accordingly, the satellite-derived turbidity data will strongly enhance federal consulting activities and thus ensure a modern river monitoring of Germany’s federal water ways.

The Department of Energy and the Sandia National Laboratories Wind Power Technology Department have initiated a number of wind turbine blade sensing technology projects with a major goal of understanding the issues and challenges of incorporating new sensing technologies in wind turbine blades. The projects have been highly collaborative with teams from several commercial companies, universities, other national labs, government agencies and wind industry partners. Each team provided technology that was targeted for a particular application that included structural dynamics, operational monitoring, non-destructive evaluation and structural health monitoring. The sensing channels were monitored, in some or all cases, during blade fabrication, field testing of the blade on an operating wind turbine, and lab testing where the life of the blade was accelerated to blade failure. Implementing sensing systems in wind turbine blades is an engineering challenge and solutions often require the collaboration with a diverse set of expertise. This report discusses some of the key issues, challenges and lessons-learned while implementing sensing technologies in wind turbine blades. Some of the briefly discussed topics include cost and reliability, coordinate systems and references, blade geometry, blade composites, material compatibility, sensor ingress and egress, time synchronization, wind turbine operation environments, and blade failure mechanisms and locations.

Most of China's rice production is located in the southern provinces of the country where frequent cloudy conditions hinder the successful acquisition of optical imagery. Small field sizes and complex planting patterns pose additional challenges to crop mapping using remote sensing approaches. High resolution radar data are most suitable for operational monitoring of crops in this region of China. In this study, the suitability of high-resolution TerraSAR-X StripMap data (6 m resolution) for identification of rice was investigated for a site in Xuwen, Guangdong Province, China. An integrated decision tree and object-oriented classification approach was used. The results showed that higher rice identification accuracies can be obtained using multi-temporal TerraSAR-X data at the tillering, jointing and flowering periods. Both the VV and VH polarizations provided accurate rice identification.

The most commonly used fire detection methods based on AVHRR (Advanced Very High Resolution Radiometer aboard NOAA satellites) observations have been applied, in this work, to the Italian Peninsula, in order to assess their effectiveness and robustness in an operational scheme for fire monitoring in different areas. The analysis developed so far shows that unsuccessful results obtained from existing detection methods mainly depend on the use of generalized, fixed threshold values, in the fire-detection tests. A new fire-detection technique, based on the most general RAT (Robust AVHRR Technique) approach, is proposed in this work. It seems able to join good performances, typically associated with techniques based on locally tuned thresholds, with high operational exportability, achieved by an automated implementation scheme completely based on AVHRR data hands. Improvements achievable by using this new approach over the Italian Peninsula, have been evaluated (for several forest- fire events and different observational conditions) by comparison with the historical records of the Italian Forestry Service.