The integration of Terrestrial Laser Scanning (TLS) and Structure from Motion and MultiView Stereo techniques allows to obtain comprehensive models of complex objects by using each technique in contexts presenting the optimal operating conditions, as widely reported in bibliographic references. A different situation occurs for emergency surveys. In this case, time and security act as constraining factors, requiring the use of these techniques also in the most unfavourable conditions. In the case of photogrammetry, these include areas where the object surfaces are not perpendicular to the camera axis, and in the case of TLS, they include areas where laser beams are almost tangent to the surveyed object surfaces. These situations are anyway necessary for safely carrying out these surveys in the minimum possible time and cost. Although this kind of survey results locally in lower precision levels than those obtainable by these techniques in ideal conditions, it entails the possibility of obtaining complete models, e.g. including vertical external walls in inaccessible buildings, with controlled precision.

In this article first ideas are presented to extend the classical concept of geodetic network adjustment by introducing a new method for uncertainty assessment as two-step analysis.In the first step the raw data and possible influencing factors are analyzed using uncertainty modeling according to GUM (Guidelines to the Expression of Uncertainty in Measurements). This approach is well established in metrology, but rarely adapted within Geodesy.The second step consists of Monte-Carlo-Simulations (MC-simulations) for the complete processing chain from raw input data and pre-processing to adjustment computations and quality assessment. To perform these simulations, possible realizations of raw data and the influencing factors are generated, using probability distributions for all variables and the established concept of pseudo-random number generators. Final result is a point cloud which represents the uncertainty of the estimated coordinates; a confidence region can be assigned to these point clouds, as well.This concept may replace the common concept of variance propagation and the quality assessment of adjustment parameters by using their covariance matrix. It allows a new way for uncertainty assessment in accordance with the GUM concept for uncertainty modelling and propagation.As practical example the local tie network in “Metsähovi Fundamental Station”, Finland is used, where classical geodetic observations are combined with GNSS data.

In this paper stochastic properties are discussed for the final results of the application of an innovative approach for uncertainty assessment for network computations, which can be characterized as two-step approach: As the first step, raw measuring data and all possible influencing factors were analyzed, applying uncertainty modeling in accordance with GUM (Guide to the Expression of Uncertainty in Measurement). As the second step, Monte Carlo (MC) simulations were set up for the complete processing chain, i.e., for simulating all input data and performing adjustment computations. The input datasets were generated by pseudo random numbers and pre-set probability distribution functions were considered for all these variables. The main extensions here are related to an analysis of the stochastic properties of the final results, which are point clouds for station coordinates. According to Cramer’s central limit theorem and Hagen’s elementary error theory, there are some justifications for why these coordinate variations follow a normal distribution. The applied statistical tests on the normal distribution confirmed this assumption. This result allows us to derive confidence ellipsoids out of these point clouds and to continue with our quality assessment and more detailed analysis of the results, similar to the procedures well-known in classical network theory. This approach and the check on normal distribution is applied to the local tie network of Metsähovi, Finland, where terrestrial geodetic observations are combined with Global Navigation Satellite System (GNSS) data.

Since decades the discrepancy exists that geodesists monitor changes of the earth surface resp. large engineering structures with most-modern equipment, but the results are computed and presented in a suboptimal manner: In many cases, the displacements are computed in relation to reference (datum) stations, which are not stable over a long time. Aside, the variations of an object are presented as coordinates for representative points with time stamps or with displacements rates (absolute values or velocities). Finally, nowadays often we have continuous measuring sensors and data, but there is no complete concept to treat variations continuously within the coordinate approach. In this paper at first the problems are outlined and open questions are formulated. Then some ideas are presented, how to analyse and describe coordinates in a continuous manner, taking into account the classical concepts and thinking of the surveying profession. The new ideas start with the definition of a stable reference frame over time, followed by the introduction of time dependent coordinates. A specific objective is to deliver day-by-day precise reference coordinate values for different groups, working on monitoring with their own sensors and computational concepts in the same area. These concepts are applied to an extended monitoring network of the mining authority Ruhrkohle AG (RAG), responsible for the eternal obligations that the German hard coal mining industry has left behind. This RUHR-network is located in the federal state North-Rhine-Westphalia within German, where after 300 years of coal mining larger and irregular ground movements can be expected.

<p><strong>Abstract.</strong> The project ‘Determinations on the absolute sea-level rise on the German North Sea and Baltic Sea coasts’, funded by the Federal Ministry of Education and Research (BMBF) , has the overall goal to estimate the absolute sea level change in those coastal areas. A major issue associated with detecting absolute sea level changes is the relative character of tidal records. To calibrate the tidal records, a spatial vertical land movement model for northern Germany has been set up. To this end we combined a network from German Height Reference Systems (Deutsches Haupthöhennetz, DHHN 95 and DHHN 2016), reprocessed data from 180 permanent GNSS stations and results from Persistent Scatterer (PS) Interferometry.</p><p>PS processing covers an approximately 50&amp;thinsp;km wide strip along the 1200&amp;thinsp;km long German coast. We processed two tracks from Sentinel-1A and -1B from October 2014 to September 2018 and generated a combined spatial solution for the estimation of vertical land movement. In general, vertical velocities from PS Interferometry range between &amp;plusmn;2&amp;thinsp;mm/a and show a homogeneous distribution for coastal areas. Therefore we consider them as stable. We observe subsidence in the area around Groningen and Emden through hydrocarbon extraction. In Wilhelmshaven and Etzel subsidence associated with cavern storage is visible.</p><p>Processed GNSS data and PSI results overlap in time from 2014 to 2016. The integration of the spatial multi-temporal PS results with point-wise GNSS time series data are required, as they form the main input data for the further development of our vertical displacement model of northern Germany.</p>