This paper describes how high-precision DEMs are obtained over the Wadden Sea using the AeS-1 airborne interferometric radar. The Wadden Sea is an intertidal zone along the coast which has height variations less than 5 m over 30 km and is free of vegetation. The resulting DEM has a grid spacing of 2.5 m and an absolute height accuracy of 5 cm rms, as verified by theodolite measurements. The paper describes the radar system, the processing techniques, the test area, the results, and the verification procedure.£ accepted for publication in

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ABSTRACT:Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

Interferometric processing of a time series of acquisitions from synthetic aperture radar (SAR) satellites makes it possible to detect and measure ground motion phenomena, typically caused by landslides, subsidence, earthquakes or volcanic activity, with millimeter-scale precision. This enables, for example, monitoring of the stability of slopes, mining areas, buildings and infrastructures. This work presents the European Ground Motion Service (EGMS), funded by the European Commission as an essential element of the Copernicus Land Monitoring Service (CLMS). The EGMS constitutes the first application of the interferometric SAR (InSAR) technology to high-resolution monitoring of ground deformations over an entire continent, based on fullresolution processing of all Sentinel-1 (S1) satellite acquisitions over most of Europe (Copernicus Participating States). Upscaling from existing national precursor services to pan-European scale is challenging. The EGMS will employ the most advanced persistent scatterer (PS) and distributed scatterer (DS) InSAR processing techniques in combination with a high-quality Global Navigation Satellite System (GNSS) model to calibrate the ground motion products. To foster as wide usage as possible, the EGMS will also provide tools for visualization, exploration, analysis and download of the ground deformation products, as well as elements to promote best practice applications and user uptake.

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Constraint-based random simulation is state-of-the-art in verification of multi-million gate industrial designs. This method is based on stimulus generation by constraint solving. The resulting stimuli will particularly cover corner case test scenarios which are usually hard to identify manually by the verification engineer. Consequently, constraintbased random simulation will catch corner case bugs that would remain undetected otherwise. Therefore, the quality of design verification is increased significantly. However, in the process of constraint specification for a specific test scenario, the verification engineer is faced with the problem of over-constraining, i.e. the overall constraint specified for a test scenario has no solution. In this case the root cause of the contradiction has to be identified and resolved. Given the complexity of constraints used to describe test scenarios, this can be a very time-consuming process.In this paper we propose a fully automated contradiction analysis method. Our method determines all "non relevant" constraints and computes all reasons that lead to the over-constraining. Thus, we pinpoint the verification engineer to exactly the sets of constraints that have to be considered to resolve the over-constraining. Experiments have been conducted in a real-life SystemC-based verification environment at AMD Dresden Design Center. They demonstrate a significant reduction of the constraint contradiction debug time.