In Austria, more than a half of all electricity is produced with the help of hydropower plants. To reduce their ecological impact, dams are being equipped with fish passages that support connectivity of habitats of riverine fish species, contributing to hydropower sustainability. The efficiency of fish passages is being constantly monitored and improved. Since the likelihood of fish passages to be discovered by fish depends, inter alia, on flow conditions near their entrances, these conditions have to be monitored as well. In this study, we employ large-scale particle image velocimetry (LSPIV) in seeded flow conditions to analyse images of the area near a fish passage entrance, captured with the help of a ready-to-fly consumer drone. We apply LSPIV to short image sequences and test different LSPIV interrogation area sizes and correlation methods. The study demonstrates that LSPIV based on ensemble correlation yields velocities that are in good agreement with the reference values regarding both magnitude and flow direction. Therefore, this non-intrusive methodology has a potential to be used for flow monitoring near fish passages on a regular basis, enabling timely reaction to undesired changes in flow conditions when possible.

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For a task like 3D building reconstruction, there are three main data sources carrying information which is required for a highly automated data acquisition. These data sources are aerial images, Digital Surface Models ( DSM) , which can either be derived by stereo matching from aerial images or be directly measured by scanning laser systems, and -at least for highly developed countries -existing (2D) GIS information on the ground plan or usage of buildings. The way these different data sources should be utilized by a process of 3D building reconstruction depends on the distinctive characteristics ofthe different, partly complementary type of information they contain. Image data contains much information, but just this complexity causes enormous problems for the automatic interpretation of this data type. The GIS as a secondary data source provides information on the 2D shape, i.e. the ground plan of a building, which is very reliable, although information on the third dimension is missing and therefore has to be provided by other data sources. As the information of a DSM is restricted to surface geometry, the interpretation of this kind of data is easier compared to the interpretation of image data. Nevertheless, due to insufficient spatial resolution or quality of the DSM, optimal results can only be achieved by the combination of all data sources. Within this paper two approaches aiming on the combination of aerial images, digital surface models and existing ground plans for the reconstruction of three-dimensional building reconstructions will be demonstrated.