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Germany has a long history in seismic instrumentation. The installation of the first station sites was initiated in those regions with seismic activity. Later on, with an increasing need for seismic hazard assessment, seismological state services were established over the course of several decades, using heterogeneous technology. In parallel, scientific research and international cooperation projects triggered the establishment of institutional and nationwide networks and arrays also focusing on topics other than monitoring local or regional areas, such as recording global seismicity or verification of the compliance with the Comprehensive Nuclear-Test-Ban Treaty. At each of the observatories and data centers, an extensive analysis of the recordings is performed providing high-level data products, for example, earthquake catalogs, as a base for supporting state or federal authorities, to inform the public on topics related to seismology, and for information transfer to international institutions. These data products are usually also accessible at websites of the responsible organizations. The establishment of the European Integrated Data Archive (EIDA) led to a consolidation of existing waveform data exchange mechanisms and their definition as standards in Europe, along with a harmonization of the applied data quality assurance procedures. In Germany, the German Regional Seismic Network as national backbone network and the state networks of Saxony, Saxony-Anhalt, Thuringia, and Bavaria spearheaded the national contributions to EIDA. The benefits of EIDA are attracting additional state and university networks, which are about to join the EIDA community now.

<p>Large-scale subsidence and uplift pose a significant risk to buildings and infrastructure. While subsidence due to groundwater removal or construction activities can easily be constrained on a local scale, regional changes caused by climate change are more difficult to detect. These phenomena are investigated within the „Umwelt 4.0, Cluster I - Use of digital terrain models and Copernicus data" project, which is carried out by the Hessian Agency for Nature Conservation, Environment and Geology in cooperation with the TU Darmstadt and funded by the Hessian Minister for Digital Strategy and Development. Within the framework of this project, we are creating a systematic workflow to detect ground motion over a period of several years. We focus on the state of Hessen, Germany, where several regions are known for landslide activity, e.g., Hoher Meissner, or for widespread subsidence, e.g., in the industrial areas surrounding Frankfurt a.M.. In this way, occurring ground movements and even mass movements could be detected at an early stage and, if necessary, measures can be initiated. Based on these results, future decisions on regulations or even information for the general public on risk areas can be created.</p> <p>We utilize two major datasets based on remote sensing. High-resolution digital elevation and surface models (DGM 1 and DSM 1) from airborne LiDAR surveys by the Hessian Administration for Land Management and Geoinformation. For the most parts of Hessen, it was possible to calculate differences in elevation between the years 2014, 2019 and 2021. The second dataset are persistent scatterer interferometry points (PSIs) from the BodenBewegungsdienst Deutschland with a temporal resolution of 6 days since 2015. Both datasets are integrated and linked with other data sources, such as geological maps, known subsidence-sensitive layers, hydrogeological and climatic data. For the InSAR data a toolbox has been developed that automatically detects regions with strong movement (Ground Motion Analyzer). A major challenge for integrating both datasets is the large difference in spatial coverage and temporal resolution. Advantages of LiDAR data are the high spatial resolution and the possibility to detect even small-scale movements (<5 x 5 m) below vegetation cover, for example the re-tracing of forest roads or the creation of logging trails. A disadvantage is the low temporal resolution of several years between flights in comparison with the 6 days of the PSI data. From the latter, even seasonal variations can be detected and measured. However, the spatial distribution of the points is highly heterogeneous, so in cities the point density is very high, whereas in rural areas hardly any measurements exist. Other problems are the strong fluctuations both within a time series of a single PSI point and between neighbouring points.</p> <p>With our contribution we want to highlight a typical use case of both data sets and their implementation into regulatory decision-making processes. Furthermore, we want to show a possible integrative method combining remote sensing data with ground based geoinformation and future use of advanced classification schemes to automatically detect affected regions in big datasets.</p>

In den Anwendungsbereichen der Automatisierungstechnik kommen immer häufiger Technologien aus dem Informationstechnik (IT)-Umfeld zum Einsatz. Der Grund sind neue und sich ändernde Anforderungen, die an die Automation und speziell die SPS gestellt werden. Daher verschwimmt die Grenze zwischen IT und OT (Operational Technology) zunehmend. Vielen Anwendern bereitet außerdem der Mangel an Softwareentwicklern Probleme.