# Quality Assessment of DSMs Produced from UAV Flights Georeferenced with On-Board RTK Positioning
### Paper Motivations and Objectives  
Following a previous study by [PERSON] et al. [39], the objective of this paper is to investigate a further step of the photogrammetric workflow in UAV blocks oriented by AAT, i.e., the repeatability and the accuracy of DSM generation. In most cases, the main survey product of an UAV flight is the DSM. A DSM quality analysis cannot be restricted, as for block orientation, to a few checkpoints made by ideal-contrast targets manually collimated in multiple images. For a better spatial understanding of AAT error propagation on the DSM, a larger and well distributed point set is necessary.  
As shown by [PERSON] et al. [36], a valuable indication of the AAT error propagation spatial characteristics from image and camera station observations to tie point ground coordinates can be performed with Monte Carlo analysis, given the precision of both kind of observations. This is indeed the most appropriate technique for such an investigation. However, there are also reasons to collect experimental evidence from real data, as the complete and accurate modelling of the stochastic properties of GNSS observations is not so simple. It is well known to all geodesists that precision estimates of GNSS surveys output by data processing are optimistic; moreover, as projection center coordinates are output from a Kalman filter, they can hardly be considered truly independent observations in the BBA. On the other hand, only the diagonal entries of the variance-covariance matrix of the projection center coordinates are supplied by GNSS data processing, if any. As shown by [PERSON] et al. [39], the precision assigned to camera station coordinates in the Helmert transformation or in the BBA by three widely used software packages affects the elevation accuracy of checkpoints in different ways.  
Tie points from SfM could be the natural candidates for studying the error spatial distribution, since besides block orientation errors, DSM points also inherit dense matching errors and DSM interpolation errors. Moreover, as noticed by [PERSON] et al. (2019), dense image matching does not contribute to the determination of camera exterior and interior parameters, so there is no advantage in using DSM points. However, for an empirical investigation on the repeatability of DSM generation with real blocks, as opposed to simulated ones, the tie points extracted at every repetition of the survey are different. Therefore, it is necessary to move further in the photogrammetric workflow and study the error propagation at the DSM level.  
An analysis of the discrepancies among DSMs obtained by repeated surveys of the same, unchanged area helps to gauge the limits of a surveying technique in change detection. GNSS-Assisted Aerial Triangulation would be of great interest in monitoring changes in difficult areas. In periodic surveys with this technique, the stability of the reference system would depend on the GNSS kinematic survey of the camera network, rather than on GCPs positioned in stable areas (or surveyed at each campaign execution, if no suitable stable area can be found). Therefore, the experiment presented here was conceived through trying, as far as possible, to highlight the DSM elevation changes due to the different GNSS constellations that are experienced in the various flights. Hence, the same processing parameters were applied to all of the flights in the DSM generation workflow.  
The paper is structured as follows: Section 2 describes the experiment organisation: test site, reference network, survey flights processing parameters, block control configurations, and DSM generation. Section 3 illustrates the main experiment results (with additional material provided in the Appendix). Section 4 discusses the results, and finally, Section 5 draws the conclusions.