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The optimization of measurements in a geodetic network (second-order design) has been investigated in the past; however, the practical usability of the outcomes of most of such studies is doubtful. Hence, we have proposed a new automated optimization algorithm, taking into account the practical aspects of total station measurements. The algorithm consists of four parallel partial algorithms, of which one is subsequently automatically selected—the one meeting the geodetic network accuracy requirements with the lowest number of necessary measurements. We tested the algorithm (and individual partial algorithms) on four geodetic networks designed to resemble real-world networks with 50–500 modifications to each of those networks in individual tests. The results indicate that (i) the results achieved by the combined algorithm are close to the optimal results and (ii) none of the four partial algorithms universally performs the best, implying that the combination of the four partial algorithms is necessary for achieving the best possible results of geodetic network optimization.

The presented paper focuses on testing the performance of a SLAM scanner Zeb Horizon by GeoSLAM for the creation of a digital model of a bridge construction. A cloud acquired using a static scanner Leica ScanStation P40 served as a reference. Clouds from both scanners were registered into the same coordinate system using a Trimble S9 HP total station. SLAM scanner acquisition was performed independently in two passes. The data acquired using the SLAM scanner suffered from relatively high noise. Denoising using the MLS (Moving Least Squares) method was performed to reduce noise. An overall comparison of the point clouds was performed on both the original and MLS-smoothed data. In addition, the ICP (Iterative Closest Point) algorithm was also used to evaluate local accuracy. The RMSDs of MLS-denoised data were approximately 0.02 m for both GeoSLAM passes. Subsequently, a more detailed analysis was performed, calculating RMSDs for several profiles of the construction. This analysis revealed that the deviations of SLAM data from the reference data did not exceed 0.03 m in any direction (longitudinal, transverse, elevation) which is, considering the length of the bridge of 133 m, a very good result. These results demonstrate a high applicability of the tested scanner for many applications, such as the creation of digital twins.

ABSTRACTIn this paper, we evaluated the results in terms of accuracy and coverage of the LiDAR-UAV system DJI Zenmuse L1 and Digital Aerial Photogrammetric system (DAP – UAV) DJI Zenmuse P1 in a forested area under leaf-off conditions on three sites with varying terrain ruggedness/tree type combinations. Detailed reference clouds were obtained using terrestrial scanning by Leica P40. Our results show that branches pose no problem to the accuracy of LiDAR-UAV and DAP-UAV derived terrain clouds. Elevation accuracies for photogrammetric data were even better than for LiDAR data – as low as 0.015 m on all sites. However, the LiDAR system provided better coverage, with almost full coverage at all sites, while the DAP-UAV coverage declined with the increasing density of branches (being worst in the young forest). In the very dense young forest (Site 1), the coverage by photogrammetrically extracted terrain cloud using high calculation quality and no filtering achieved 80.7% coverage, while LiDAR-UAV reached almost 100% coverage. The importance of the use of multiple (or last) returns when using LiDAR-UAV systems was demonstrated by the fact that on the site with the densest vegetation, only 11% of the ground points were represented by first returns.

The classification of point clouds is an important research topic due to the increasing speed, accuracy, and detail of their acquisition. Classification using only color is basically absent in the literature; the few available papers provide only algorithms with limited usefulness (transformation of three-dimensional color information to a one-dimensional one, such as intensity or vegetation indices). Here, we proposed two methods for classifying point clouds in RGB space (without using spatial information) and evaluated the classification success since it allows a computationally undemanding classification potentially applicable to a wide range of scenes. The first is based on Gaussian mixture modeling, modified to exploit specific properties of the RGB space (a finite number of integer combinations, with these combinations repeated in the same class) to automatically determine the number of spatial normal distributions needed to describe a class (mGMM). The other method is based on a deep neural network (DNN), for which different configurations (number of hidden layers and number of neurons in the layers) and different numbers of training subsets were tested. Real measured data from three sites with different numbers of classified classes and different “complexity” of classification in terms of color distinctiveness were used for testing. Classification success rates averaged 99.0% (accuracy) and 96.2% (balanced accuracy) for the mGMM method and averaged 97.3% and 96.7% (balanced accuracy) for the DNN method in terms of the best parameter combinations identified.

This paper presents the results of over a year-long experiment dealing with a temperature measurement to calculate the theoretical effect of the atmosphere on the measured zenith angle in engineering surveying. The measurements were performed to determine the accurate and specific temperatures (temperature gradients), which can be recorded in different seasons in the low level of the atmosphere (up to 2 m above the ground, where most Engineering Surveying measurements take place) for the geographical area of Central Europe - specifically the Czech Republic. A numerical model was then applied to the resulting determined temperature gradients to calculate the path of the beam passing through an inhomogeneous atmosphere. From these values, the apparent vertical shifts caused by refraction in a given environment and time were finally determined.

Filtering out vegetation from a point cloud based on color is only rarely used, largely due to the lack of knowledge of the suitability of input information (color, vegetation indices) and the thresholding methods. We have evaluated multiple vegetation indices (ExG, ExR, ExB, ExGr, GRVI, MGRVI, RGBVI, IKAW, VARI, CIVE, GLI, and VEG) and combined them with 10 methods of threshold determination based on training set selection (including machine learning methods) and the renowned Otsu’s method. All these combinations were applied to four clouds representing vegetated rocky terrain, and the results were compared. The ExG and GLI indices were generally the most suitable for this purpose, with the best F-scores of 97.7 and 95.4, respectively, and the best-balanced accuracies for the same combination of the method/vegetation index of 98.9 and 98.3%, respectively. Surprisingly, these best results were achieved using the simplest method of threshold determination, considering only a single class (vegetation) with a normal distribution. This algorithm outperformed all other methods, including those based on a support vector machine and a deep neural network. Thanks to its simplicity and ease of use (only several patches representing vegetation must be manually selected as a training set), this method can be recommended for vegetation removal from rocky and anthropogenic surfaces.

There are numerous talus cones that have formed by long-term geological processes and sudden hydrological events in the Small Cold Valley (High Tatras National Park in Slovakia). Frequent hiking trails lead here; therefore, their safeness needs to be monitored due to recent rock avalanches and landslides. A complex methodology for monitoring changes in talus cones was developed to determine the extent, pace, nature, and origin of the morphological changes in the land in this complex high-mountain terrain. Non-contact UAS photogrammetry with SfM-MVS processing was applied as a quick, reliable, and environment-friendly data acquisition method. For proper georeferencing, a network of GCPs and stabilized surveying points were established by terrestrial geodetic surveying. Together with an evaluation of the methodology, the results comparing the actual state of a talus cone in 2018 and 2022 (after the significant hydrological event) are presented. Comparing and analyzing spatial models represented by point clouds, with an accuracy of centimeter level, was obtained. The detected morphological changes reached values in meters. A differential model expresses the distribution of the morphological changes. In conclusion, geodetic and geological knowledge is synthesized to evaluate the phenomena occurring in this territory.

Currently, the creation of digital copies (digital twins) of various objects by remote sensing methods producing point clouds is becoming commonplace. This might be particularly important for the digital preservation of historical objects. Such clouds are typically primarily acquired as unordered sets of points with regular dense spacing, making the clouds huge in size, which causes such clouds to be difficult to process, store and share. The clouds are, therefore, usually diluted before use, typically through uniform dilution with a set spacing; such dilution can, however, lead to the loss of detail in the resulting cloud (washed-out edges and fine features). In this paper, we present an easy-to-use and computationally inexpensive progressive dilution method preserving detail in highly rugged/curved areas while significantly reducing the number of points in flat areas. This is done on the basis of a newly proposed characteristic T, which is based on the local scattering of the cloud (i.e., on the ruggedness of the local relief). The performance of this algorithm is demonstrated on datasets depicting parts of historic buildings of different characters. The results are evaluated on the basis of (a) root mean square deviation (RMSD) between the original and diluted clouds, (b) of visual evaluation of the differences and (c) of reduction in the point cloud size, demonstrating an excellent performance of the algorithm with a minimum loss of detail while significantly reducing the point clouds (approx. by 47–66% compared to the corresponding uniform dilution for individual datasets)

With the ever-increasing popularity of unmanned aerial vehicles and other platforms providing dense point clouds, filters for the identification of ground points in such dense clouds are needed. Many filters have been proposed and are widely used, usually based on the determination of an original surface approximation and subsequent identification of points within a predefined distance from such surface. We presented a new filter, the multidirectional shift rasterization (MDSR) algorithm, which is based on a different principle, i.e., on the identification of just the lowest points in individual grid cells, shifting the grid along both the planar axis and subsequent tilting of the entire grid. The principle was presented in detail and both visually and numerically compared with other commonly used ground filters (PMF, SMRF, CSF, and ATIN) on three sites with different ruggedness and vegetation density. Visually, the MDSR filter showed the smoothest and thinnest ground profiles, with the ATIN the only filter comparably performing. The same was confirmed when comparing the ground filtered by other filters with the MDSR-based surface. The goodness of fit with the original cloud is demonstrated by the root mean square deviations (RMSDs) of the points from the original cloud found below the MDSR-generated surface (ranging, depending on the site, between 0.6 and 2.5 cm). In conclusion, this paper introduced a newly developed MDSR filter that outstandingly performed at all sites, identifying the ground points with great accuracy while filtering out the maximum of vegetation and above-ground points and outperforming the aforementioned widely used filters. The filter dilutes the cloud somewhat; in such dense point clouds, however, this can be perceived as a benefit rather than as a disadvantage.

This paper presents an interesting application of the riverbed model shape and deformations monitoring using laser scanning technology and accurate local micro-network. The most interesting fact about this application is very high accuracy demand on deformation determination (maximum permissible error is only 2 mm) within quite large object (the size of the riverbed model is about 100 meters). Up to now, mechanical calipers in the selected profiles were used to detect the changes. This manual approach is very laborious and time-consuming and the gathered data resolution and accuracy is often not sufficient. The suggested solution contains two main parts. The first part deals with construction of highly accurate local micro-network for laser scanning needs (maximum required standard deviation in any coordinate is lower than 0.4 mm) and the second part deals with actual laser scanning and data processing. Design, measurement and processing of the experiment was conducted for the needs of the research project “Improvement of navigation conditions on the Elbe between Ústí nad Labem - state border CR / FRG - Navigation Step Děčín”. The main goal of this project is design and realization of the river regulation to improve the navigation conditions. The key benefit of using river model is the possibility to easily simulate various catastrophic scenarios (various degrees of the floods) and their impacts on riverbed changes.

Lately, affordable unmanned aerial vehicle (UAV)-lidar systems have started to appear on the market, highlighting the need for methods facilitating proper verification of their accuracy. However, the dense point cloud produced by such systems makes the identification of individual points that could be used as reference points difficult. In this paper, we propose such a method utilizing accurately georeferenced targets covered with high-reflectivity foil, which can be easily extracted from the cloud; their centers can be determined and used for the calculation of the systematic shift of the lidar point cloud. Subsequently, the lidar point cloud is cleaned of such systematic shift and compared with a dense SfM point cloud, thus yielding the residual accuracy. We successfully applied this method to the evaluation of an affordable DJI ZENMUSE L1 scanner mounted on the UAV DJI Matrice 300 and found that the accuracies of this system (3.5 cm in all directions after removal of the global georeferencing error) are better than manufacturer-declared values (10/5 cm horizontal/vertical). However, evaluation of the color information revealed a relatively high (approx. 0.2 m) systematic shift.

Point clouds derived using structure from motion (SfM) algorithms from unmanned aerial vehicles (UAVs) are increasingly used in civil engineering practice. This includes areas such as (vegetated) rock outcrops or faces above linear constructions (e.g., railways) where accurate terrain identification, i.e., ground filtering, is highly difficult but, at the same time, important for safety management. In this paper, we evaluated the performance of standard geometrical ground filtering algorithms (a progressive morphological filter (PMF), a simple morphological filter (SMRF) or a cloth simulation filter (CSF)) and a structural filter, CANUPO (CAractérisation de NUages de POints), for ground identification in a point cloud derived by SfM from UAV imagery in such an area (a railway ledge and the adjacent rock face). The performance was evaluated both in the original position and after levelling the point cloud (its transformation into the horizontal plane). The poor results of geometrical filters (total errors of approximately 6–60% with PMF performing the worst) and a mediocre result of CANUPO (approximately 4%) led us to combine these complementary approaches, yielding total errors of 1.2% (CANUPO+SMRF) and 0.9% (CANUPO+CSF). This new technique could represent an excellent solution for ground filtering of high-density point clouds of such steep vegetated areas that can be well-used, for example, in civil engineering practice.

This paper is focused on a comparison measurement processing of absolute gravimeters in 2013. The comparison deals with a number of various types of absolute gravimeters and includes also an absolute gravimeter from Geodetic observatory Pecný. Comparative measurements are performed to detect systematic errors of gravimeters. A result of processing is most likely value of a gravity and a systematic error of individual devices. Measured values are input to a adjustment with condition a sum of systematic errors is zero. A part of this process is also verification following output: (i) value of a posteriori standard deviation, (ii) size of corrections and (iii) statistical significance of systematic errors. The results of adjustment are 15 gravity values on the reference places and 25 systematic errors of measuring instruments. Result shows that the presence of systematic errors in measurements is not statistically provable because the systematic errors are similarly sized as their standard deviation.

The study presented in this paper analyses the results of measurements and data processing for documentation and quantification of material in heaps in large areas, where UAVs may no longer be effective due to a large range. Two test heaps were selected from a whole area, where the aim was to confirm the suitability of using the method of digital aerial photogrammetry by manned (crewed) aerial vehicle. For comparison, a commonly used GNSS RTK method was also used. Terrestrial laser scanning was chosen as the control reference method. TLS measurement is a trusted method with high accuracy. The methods were compared with each other through the quality of the mesh, analysis of the cross-sections, and comparison of the volumes of heaps. As a result, the determination of heap volumes and documentation using digital aerial photogrammetry can be confirmed as an appropriate, efficient, fast, and accurate method. The difference in the detected volume was less than 0.1%, the mean difference of the meshes was less than 0.01 m, and the standard deviation was less than 0.05 m.

Georeferencing using ground control points (GCPs) is the most common strategy in photogrammetry modeling using unmanned aerial vehicle (UAV)-acquired imagery. With the increased availability of UAVs with onboard global navigation satellite system–real-time kinematic (GNSS RTK), georeferencing without GCPs is becoming a promising alternative. However, systematic elevation error remains a problem with this technique. We aimed to analyze the reasons for this systematic error and propose strategies for its elimination. Multiple flights differing in the flight altitude and image acquisition axis were performed at two real-world sites. A flight height of 100 m with a vertical (nadiral) image acquisition axis was considered primary, supplemented with flight altitudes of 75 m and 125 m with a vertical image acquisition axis and two flights at 100 m with oblique image acquisition axes (30° and 15°). Each of these flights was performed twice to produce a full double grid. Models were reconstructed from individual flights and their combinations. The elevation error from individual flights or even combinations yielded systematic elevation errors of up to several decimeters. This error was linearly dependent on the deviation of the focal length from the reference value. A combination of two flights at the same altitude (with nadiral and oblique image acquisition) was capable of reducing the systematic elevation error to less than 0.03 m. This study is the first to demonstrate the linear dependence between the systematic elevation error of the models based only on the onboard GNSS RTK data and the deviation in the determined internal orientation parameters (focal length). In addition, we have shown that a combination of two flights with different image acquisition axes can eliminate this systematic error even in real-world conditions and that georeferencing without GCPs is, therefore, a feasible alternative to the use of GCPs.

Measurand MEMS ShapeAccelArray sensors are in many ways unique and new equipment, which allows to determine the relative displacements and deformations in other ways than before. The instruments are described, tested and compared with existing instrumentation in a small number of articles, but with exception of one it was not tested from engineering surveying point of view, where the exact precision and accuracy knowledge is a basis for the further use. The result of the experiments is the accuracy of measuring changes by the sensor itself, the pros and cons of its use and some features of its design, which is good to know before using it.There were designed and performed practical tests to determine the relative and absolute measurement accuracy of the sensor deformations measurement in all three possible types of use, namely the vertical installation, the horizontal installation and the measurement of convergence.The results show high accuracy of the sensor tested, which is under certain conditions even considerably higher than that given by Measurand

widespread used method. In this paper, an analysis of the accuracy and its changes over time of the measured values in continuous geodetic monitoring is presented. For the analysis, a set of data measured in the period of time between January 2006 to July 2010 was used. The main method of the analysis is a linear-harmonic function approximation.

The current trend in the use of remote sensing technologies is their use as a tool for monitoring hard-to-reach areas, objects or phenomena in the alpine environment. Remote sensing technology is also effectively used to monitor geohazards and the development of human-made changes in the country. Research presented in this study demonstrates the results for the usability of the publicly available national digital elevation model DEM 5.0 obtained by utilizing the airborne laser scanning (ALS) survey to monitor the development of erosion, morphological changes of talus cones, or the dynamics of movement of rock blocks between stages of measurement in the alpine environment of the High Tatras mountains. The reference methods for this study are the terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetric approach using unmanned aerial systems (UASs). By comparing the created DEMs, the ALS point cloud’s accuracy on mostly rocky areas of different sizes was verified. The results show that the standard deviation of the ALS point cloud ranges from 19 to 46 mm depending on the area’s size and characteristics. The maximum difference ranges from 100 to 741 mm. The value of systematic displacement of data obtained by different technologies ranges from 1 to 29 mm. This research confirms the suitability of the ALS method with its advantages and limits for the detection of movement of rock blocks or change of position of any natural or anthropogenic objects with a size from approximately 1 m2.

This research focused on determining a rotary kiln’s geometric parameters in a non-traditional geodetic way—by deriving them from a survey realized by a terrestrial laser scanner (TLS). The point cloud obtained by TLS measurement was processed to derive the longitudinal axis of the RK. Subsequently, the carrier tires’ geometric parameters and shell of the RK during the shutdown were derived. Manual point cloud selection (segmentation) is the base method for removing unnecessary points. This method is slow but precise and controllable. The proposed analytical solution is based on calculating the distance from each point to the RK’s nominal axis (local radius). Iteration using a histogram function was repeatedly applied to detect points with the same or similar radiuses. The most numerous intervals of points were selected and stored in separate files. In the comparison, we present the conformity of analytically and manually obtained files and derived geometric values of the RK-radiuses’ spatial parameters and coordinates of the carrier tires’ centers. The horizontal (X and Y directions) and vertical (Z-direction) of root–mean–square deviation (RMSD) values are up to 2 mm. RMSD of the fitting of cylinders is also up to 2 mm. The center of the carrier tires defines the longitudinal axis of the RK. Analytical segmentation of the points was repeated on the remaining point cloud for the selection of the points on the outer shell of the RK. Deformation analysis of the shell of the RK was performed using a cylinder with a nominal radius. Manually and analytically processed point clouds were investigated and mutually compared. The calculated RMSD value is up to 2 mm. Parallel cuts situated perpendicularly to the axis of the RK were created. Analysis of ovality (flattening) of the shell was performed. Additionally, we also present the effect of gradually decreasing density (number) of points on the carrier tires for their center derivation.

Using a GNSS RTK (Global Navigation Satellite System Real Time Kinematic) -equipped unmanned aerial vehicle (UAV) could greatly simplify the construction of highly accurate digital models through SfM (Structure from Motion) photogrammetry, possibly even avoiding the need for ground control points (GCPs). As previous studies on this topic were mostly performed using fixed-wing UAVs, this study aimed to investigate the results achievable by a quadrocopter (DJI Phantom 4 RTK). Three image acquisition flights were performed for two sites of a different character (urban and rural) along with three calculation variants for each flight: georeferencing using ground-surveyed GCPs only, onboard GNSS RTK only, and a combination thereof. The combined and GNSS RTK methods provided the best results (at the expected level of accuracy of 1–2 GSD (Ground Sample Distance)) for both the vertical and horizontal components. The horizontal positioning was also accurate when georeferencing directly based on the onboard GNSS RTK; the vertical component, however, can be (especially where the terrain is difficult for SfM evaluation) burdened with relatively high systematic errors. This problem was caused by the incorrect identification of the interior orientation parameters calculated, as is customary for non-metric cameras, together with bundle adjustment. This problem could be resolved by using a small number of GCPs (at least one) or quality camera pre-calibration.

In modern industrial geodesy, high demands are placed on the final accuracy, with expectations currently falling below 1 mm. The measurement methodology and surveying instruments used have to be adjusted to meet these stringent requirements, especially the total stations as the most often used instruments. A standard deviation of the measured distance is the accuracy parameter, commonly between 1 and 2 mm. This parameter is often discussed in conjunction with the determination of the real accuracy of measurements at very short distances (5–50 m) because it is generally known that this accuracy cannot be increased by simply repeating the measurement because a considerable part of the error is systematic. This article describes the detailed testing of electronic distance meters to determine the absolute size of their systematic errors, their stability over time, their repeatability and the real accuracy of their distance measurement. Twenty instruments (total stations) have been tested, and more than 60,000 distances in total were measured to determine the accuracy and precision parameters of the distance meters. Based on the experiments’ results, calibration procedures were designed, including a special correction function for each instrument, whose usage reduces the standard deviation of the measurement of distance by at least 50%.

It is necessary to be careful of geometric accuracy of the roadways when constructing them.Correct thickness of the individual construction layers together with roughness of thepavement belongs among important influences ensuring lifetime of the roadways andvehicles and for comfortable and safe car ride. It is necessary beside other things to havea reliable check measurement method at disposal so as to ensure the required accuracy ofthe individual construction layers will be achieved. The check measurement method mustbe able to measure a checked construction component with the required accuracy and withsufficiently high density describing not only global deviations, but also local deviations.The highest requirements on accuracy are placed on the final construction layer of theroadway. Layer thickness and pavement roughness are being evaluated here. The 3Dterrestrial scanning method is currently offered for geometric checking of its realization.The article deals with testing of procedure of the pavement roughness measurement withthe 3D terrestrial scanning system and with its verification by a total station measurement.Emphasis is put on verification of accuracy of absolute heights of points in the 3D modelof the pavement and on size of random errors in the elevation component. Results of thetesting clarified using the 3D terrestrial scanning systems and their accuracy for check ofthe roadway surface.

Regarding the terrestrial laser scanning accuracy, one of the main problems is the noisein measured distance which is necessary for the spatial coordinates ́ determination. In thispaper the technique of using the wavelet transformation for the reduction of the noise inthe laser scanning data is described. This method of filtration is made in “post processing”and due to this fact any changes in the measuring procedure in the field shouldn ́t be done.The creation of the regular matrix is needed to apply image processing. This matrix thenmakes the range image. In the paper real and simulated efficiency tests of wavelettransformation, the final summary and advantages or disadvantages of this method areintroduced.

In the area of Prague Castle there is already about 10 years of periodical measurement ofthe height changes in the buildings and structures being performed. The measurementmethod is precise levelling predominantly. Until now, these measurements have beenevaluated only locally with respect to each building and its stability without an overall viewof the situation of possible movements of individual parts of the surface Prague Castle.Whereas there are height shift of some points between epochs undoubtedly, a new andcomplete adjustment of each measured epoch and mutual assessment of changes betweenepochs using robust analysis was conducted. This comparison shows the relative movementof certain parts against another. The results are consistent with current knowledge of thegeology in the area of the Prague Castle.

The paper deals with geodetic measurements of mutual longitudinal displacements ofconstruction of the railway bridge and rails on the bridge in Klášterec nad Oh í.Construction of the bridge is made of steel with a concrete deck, which carries the stonesuperstructure and rails. The bridge is about 100 meters long and expected deformationsare in millimetres. The method of geodetic network with the expected standard deviationsof coordinates about 0.2 mm was chosen. The deformation of the structure was determinedto be 4 mm, the deformation of the rails was determined to be 1 mm, both as a result ofepoch comparison.

The paper deals with the construction and determination of coordinates of the absoluteEDMs baseline in a laboratory with 16 pillars with forced centring. Leica Absolute TrackerAT401 (standard deviation of distance measurement: 5 μ m, standard deviation of anglemeasurement: 0.15 mgon), which is designed for very accurate industrial measurements,was used for our purpose. Lengths between the baseline points were determined with astandard deviation of 0.02 mm. The baseline is used for determining systematic and randomerrors of distance meters and for accuracy of distance meters at short distances commonin engineering surveying for purposes of mechanical engineering.

The prediction of landslides and other events associated with slope movement is a very serious issue in many national parks around the world. This article deals with the territory of the Malá Studená Dolina (Little Cold Valley, High Tatras National Park—Slovakia), where there are extensive talus cones, through which seasonally heavy hiking trails lead. In the last few years particularly, there have been frequent falls and landslides in the mountainous environment, which also caused several fatal injuries in 2018. For the above reasons, efforts are being made to develop a methodology for monitoring the changes of the talus cones in this specific alpine area, to determine the size, speed, and character of the morphological changes of the soil. Non-contact methods of mass data collection (laser scanning with Leica P40 and aerial photogrammetry with unmanned aerial system (UAS) DJI Phantom 4 Pro) have been used. The results of these measurements were compared and the overall suitability of both methods for measurement in such terrain evaluated. The standard deviation of the difference of surface determination (represented by the point cloud) is about 0.03 m. As such accuracy is sufficient for the purpose of monitoring talus cones and the use of UAS is easier and associated with lower risk of damage of expensive equipment, we conclude that this method is more suitable for mapping and for repeated monitoring of such terrain. The properties of the outputs of the individual measurement methods, the degree of measurement difficulty and specific measurement conditions in the mountainous terrain, as well as the economy of the individual methods, are discussed in detail.

The article addresses the solution of the external orientation of the camera by means of a generic algorithm which replaces complicated calculation models using the matrix inverse. The computation requires the knowledge of four control points in the spatial coordinate system and the image coordinate system. The computation procedure fits very well computer-based solutions thanks to it being very simple.

The article assesses the precision development of distance measurement using prismless distance meters, both in relation to the changing length of the measured distance and the changing incidence angle of the distance meter’s beam. The article presents the design and performance of an original experiment, the characteristics of instruments used, statistical evaluation of experimental data and formulation of conclusions on the precision rate of distance measurement using prismless instruments.

Long-span concrete prestressed bridges are sensitive for long-term deflections growing. Bridge over the river Labe near Mělníkis a typical example of this structural type. 15 years after bridge opening, midspan deflection still increases. Detail surveyingof the superstructure was made to identify possible structure failure.