Unmanned aircraft systems (UAS) have rapidly become more common in various applications. At the same time, the need for a safe UAS operation is of great importance to minimize and avoid risks that could arise with the deployment of this technology. With these requirements, UAS regulators in the European Union (EU) are making large efforts to enable a reliable legal framework of conditions for UAS operation to keep up with new capabilities of this technology and to minimize the risk of property damage and, most importantly, human injury. A recent outcome of the mentioned efforts is that new EU drone regulations are into force since 1 January 2021. In this paper we aim to provide a sound overview of recent EU drone regulations and the main changes to the rules since the first wave of regulations adopted in 2017. We highlight how such new rules help or hinder the use of UAS technology and its economic potential in scientific and commercial sectors by providing an exploratory investigation of UAS legal frames in Europe. An example of the impact of legislation on the operation of one particular UAS in Germany is provided, which has been in use since 2013 for atmospheric research.

Abstract. The proper function of rail-based transport networks relies on the accurate positioning of the tracks. Regular control and maintenance intervals are in place to guarantee safe and reliable operation. This also holds for the crane rails of the storage cranes in the container terminal in the Hamburg harbour. Especially in the terminal “Altenwerder” the geomorphological conditions of the soil lead to a permanent subsidence of the tracks and thus ask for intensive surveying and maintenance activities. The allowed tolerances are in the range of 10mm in the XY-plane on a stretch of 300m. In the daily practice, the measurements are done using traditional tachymetric survey, in combination with a rail car carrying a reflector. This method is reliable but comes with the disadvantage that the operation of cranes needs to be interrupted. In this paper we present an alternative, automatic approach which employs state-of-the-art UAV-based photogrammetry to measure the actual location of the rail. The mid-format camera system combined with a 150mm tele-lens results in a GSD of 0.9mm at 35m flying height. Challenges addressed concern the proper setup and installation of the ground control network, the flight planning and bundle adjustment. Furthermore, an automated rail delineation in the derived surface model was developed. First experiments show that an automatic workflow is possible, including the delineation task. Remaining obstacles concern, for instance, the compliance with the requirements regarding absolute positional accuracy, since the inner block geometry is theoretically much more accurate than the realised control point network.

Abstract. Container crane inspection is a very important task to maintain their uninterrupted operation. Nevertheless, this is a costly and time-consuming activity if performed manually. Recently, image-based detection of surface damages or changes using drones has gained increasing interest in industry; especially when objects of interest have a complex structure like container cranes. One main aim of this paper is a single-epoch image analysis which will also serve later for multi-epoch processing. It provides reliable information about current defects that may lead to big damages if not inspected by experts. Naïve Bayes classifier is employed to classify the images in different classes of which critical defects and especially rust is important. The preliminary results show that the precision on the target class reached about 99%. However, 87% percent recall in this class is not enough and it should be improved for this application.Having a large dataset requires an efficient data management system to provide users and decision makers with the information needed. In addition, in order to foster full automation, the aforementioned image analysis component should have a direct connection to the database and thus is able to query image and semantic information. We therefore introduce the second aim of our research, that is a concept for database design. Here, not only the raw data and the final results are integrated but also the intermediate results. At the same time, the database concept is connected to an integrated client interface that allows retrieving data of interest in a virtual globe.

<p><strong>Abstract.</strong> Disasters such as floods, large fires, landslides, avalanches, or forest fires are often inevitable and cannot be fully prevented, but their impact can be minimized with sound disaster management strategies aided by the latest technological advancements. A key factor affecting these strategies is the time, because any delay can result in dramatic consequences and potentially human losses. Therefore, a quick geo-situation report of the disaster is highly demanded, but still not an easy task because – in most cases – a priori known spatial information like map data or geodatabases, are outdated, and anyway won’t provide an overview on the current situation. This paper provides an exploratory investigation to be smart in providing correct and timely geodata that can help in emergency cases; especially in support decision making in emergency and risk management. In particular, issues related to geodatabase design and visualization of a variety of geodata available play a key role when it comes to efficient data deployment and usability. To this end, a significant part of this research will be devoted to develop a concept for a geodatabase design and dataset management that helps assessing a disaster risk through a potential provision of data needed. Based on this consideration, the proposed concept is to create multi-disciplinary integrated geodatabases as well as an easy-to-use graphical user interface to access the obtained data. To address this concept, hard- and software solutions are being developed through the joint research project ANKommEn and its extension ANKommEn2. In those projects two automated unmanned systems, that is an aerial UAV (Unmanned Aerial Vehicle) and a ground based UGV (Unmanned Ground Vehicle), are being developed to provide up-to-date information of rescue scenarios. Within this paper, highlights about the two project parts will be briefly presented, and then the current state of the art in geospatial database management, followed by focusing on Postgres-based database management connected with QGIS, and finally current results like a Web Map Service will be discussed.</p>

<p><strong>Abstract.</strong> Disasters such as floods, large fires, landslides, avalanches, or forest fires are often inevitable and cannot be fully prevented, but their impact can be minimized with sound disaster management strategies aided by the latest technological advancements. A key factor affecting these strategies is the time, where any delay can result in dramatic consequences and potentially human losses. Therefore, a quick situation report of the disaster is highly demanded, but still not an easy task because - in most cases - a priori known spatial information like map data or geo-databases, are outdated. In addition, visual and geometric information on the current situation is needed to help rescue teams and first responders. From this point of view, we came up to the main idea of the joint research project ANKommEn and its extension ANKommEn 2 (german acronym for Automated Navigation and Communication for Exploration). The project idea embodies an exploratory investigation to be smart in providing correct and timely geodata that can help in emergency cases; especially in support decision making in emergency risk management. For this purpose, automated unmanned systems, both ground (UGV) and airborne (UAV), are being developed to provide up-to-date information of rescue scenarios.</p>