Abstract. The European COPERNICUS program provides an unprecedented breakthrough in the broad use and application of satellite remote sensing data. Maintained on a sustainable basis, the COPERNICUS system is operated on a free-and-open data policy. Its guaranteed availability in the long term attracts a broader community to remote sensing applications. In general, the increasing amount of satellite remote sensing data opens the door to the diverse and advanced analysis of this data for earth system science.However, the preparation of the data for dedicated processing is still inefficient as it requires time-consuming operator interaction based on advanced technical skills. Thus, the involved scientists have to spend significant parts of the available project budget rather on data preparation than on science. In addition, the analysis of the rich content of the remote sensing data requires new concepts for better extraction of promising structures and signals as an effective basis for further analysis.In this paper we propose approaches to improve the preparation of satellite remote sensing data by a geo-database. Thus the time needed and the errors possibly introduced by human interaction are minimized. In addition, it is recommended to improve data quality and the analysis of the data by incorporating Artificial Intelligence methods. A use case for data preparation and analysis is presented for earth surface deformation analysis in the Upper Rhine Valley, Germany, based on Persistent Scatterer Interferometric Synthetic Aperture Radar data. Finally, we give an outlook on our future research.

<p><strong>Abstract.</strong> The use of intelligent technologies within 3D geospatial data analysis and management will decidedly open the door towards efficiency, cost transparency, and on-time schedules in planning processes. Furthermore, the mission of smart cities as a future option of urban development can lead to an environment that provides high-quality life along stable structures. However, neither geospatial information systems nor building information modelling systems seem to be well prepared for this new development. After a review of current approaches and a discussion of their limitations we present our approach on the way to an intelligent platform for the management and analysis of big 3D geospatial data focusing on infrastructure projects such as metro or railway tracks planning. three challenges are presented focusing on the management of big geospatial data with existing geo-database management systems, the integration of heterogeneous data, and the 3D visualization for database query formulation and query results. The approach for the development of a platform for big geospatial data analysis is discussed. Finally, we give an outlook on our future research supporting intelligent 3D city applications in the United Arab Emirates.</p>