New measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called OptD-multi and it gives several acceptable solutions. The paper presents methods of selecting one best solution based on the assumptions of two selected numerical optimization methods: the weighted sum method and the "-constraint method. The research was carried out on two measurement datasets from Airborne Laser Scanning (ALS) and Mobile Laser Scanning (MLS). The analysis have shown that it is possible to use numerical optimization methods (often used in construction) to obtain the LiDAR data. Both methods gave different results, they are determined by initially adopted assumptions and – in relation to early made findings, these results can be used instead of the original dataset for various studies.

Over the last two decades, geodetic surveying has seen significant advancements with terrestrial and unmanned aerial vehicle (UAV) laser scanning, alongside automatic observations being increasingly utilised throughout the construction process.
In the context of dam structures, periodic geodetic displacement measurements are a compulsory component of control measurements and safety assessments. In Poland, however, control measurements have largely remained rooted in traditional techniques such as classic linear and angular measurements and precise levelling. These methods are typically carried out within distinct control networks, i.e. without dual-function observation points and targets. Furthermore, network points (pillars, targets) have often not been renewed since their installation several decades ago, and glass discs, used for crown measurements in the baseline method, frequently face damage.
Changes in property ownership and modifications in environmental regulations are compounded by these issues, which often impede the proper upkeep of the sight line.
The article proposes the adaptation and reconstruction of control networks to incorporate automatic observation techniques, including linear and angular measurements. This approach includes activities aimed at reconstructing and supplementing damaged network structures, modernising the geodetic process of determining structure displacements, and enhancing the accuracy, credibility, and reliability of geodetic displacement measurement results.
The article presents the findings of an inventory assessment conducted on the existing control network infrastructure, focusing on the analysis of displacements for structures with diverse constructions and functions – a concrete dam (class I) and a water damming weir with a water intake. Furthermore, it presents practical conclusions regarding the efficient organisation of geodetic control measurements.

Using a lower-cost laser scanner for generating accuracy in 3D point-cloud has been a concern because of economic issues; therefore, this study aims to create a 3D point cloud of a target object using a low-cost 2D laser scanner, Hokuyo UTM 30LX. The experiment was carried out in November 2019 with 16 single scans from 8 different viewpoints to capture the surface information of a structure object with many intricate details. The device was attached to a rail, and it could move with stable velocity thanks to an adjustable speed motor. The corresponding 16 point-clouds were generated by using the R language. Then, they were combined one by one to make a completed 3D point cloud in the united coordinate system. The resulted point cloud consisted of 1.4 million points with high accuracy (RMSE = 1:5 cm) is suitable for visualizing and assessing the target object thanks to high dense point-cloud data. Both small details and characters on the object surface can be recognized directly from the point cloud. This result confirms the ability of generated the accuracy point cloud from the low-cost 2D laser scanner Hokuyo UTM 30LX for 3D visualizing or indirectly evaluating the current situation of the target object.

Monitoring the technical condition of hydrotechnical facilities is crucial for ensuring their safe usage. This process typically involves tracking environmental variables (e.g., concrete damming levels, temperatures, piezometer readings) as well as geometric and physical variables (deformation, cracking, filtration, pore pressure, etc.), whose long-term trends provide valuable information for facility managers. Research on the methods of analyzing geodetic monitoring data (manual and automatic) and sensor data is vital for assessing the technical condition and safety of facilities, particularly when utilizing new measurement technologies. Emerging technologies for obtaining data on the changes in the surface of objects employ laser scanning techniques (such as LiDAR, Light Detection, and Ranging) from various heights: terrestrial, unmanned aerial vehicles (UAVs, drones), and satellites using sensors that record geospatial and multispectral data. This article introduces an algorithm to determine geometric change trends using terrestrial laser scanning data for both concrete and earth surfaces. In the consecutive steps of the algorithm, normal vectors were utilized to analyze changes, calculate local surface deflection angles, and determine object alterations. These normal vectors were derived by fitting local planes to the point cloud using the least squares method. In most applications, surface strain and deformation analyses based on laser scanning point clouds primarily involve direct comparisons using the Cloud to Cloud (C2C) method, resulting in complex, difficult-to-interpret deformation maps. In contrast, preliminary trend analysis using local normal vectors allows for rapid threat detection. This approach significantly reduces calculations, with detailed point cloud interpretation commencing only after detecting a change on the object indicated by normal vectors in the form of an increasing deflection trend. Referred to as the cluster algorithm by the authors of this paper, this method can be applied to monitor both concrete and earth objects, with examples of analyses for different object types presented in the article.

Significant subsoil deformation and additional loads from the new denitrification unit caused a major problem with the load-bearing capacity of the coal power plant. It was necessary to perform an advanced assessment of the technical condition of the structure. Laser scanning (LiDAR) were used to obtain detailed data upon structure. Based on the analysis of the point cloud, the location of the column axes was determined, which allowed to determine the global and local displacements of the structure. Spatial models of the structure were created. Non-linear analyses of the structure were carried out using two types of models: 1) global beam-shell 3D models of the boiler room used to calculate the magnitude of internal forces and deformations of the structure; 2) local beam-shell detailed models of selected structural elements. Based on the results of the calculations, necessary reinforcement of the structure was designed and successfully implemented. Advanced analysis of the structure using laser scanning, subsoil monitoring and complex numerical models made it possible to perform only local reinforcements of the entire complex structure.

Archaeology of north-eastern Poland has been poorly recognized owing to vast forest areas and numerous lakes. This particularly refers to the Warmian–Masurian Voivodship, where forest covers over 30% of its area. Prospection of forested areas has become possible in Poland just over 10 years ago with the Airborne Laser Scanning (ALS) and Light Detection and Ranging (LiDAR). These techniques allow obtaining 3-D documentation of recognized and also unknown archaeological sites in the forested areas. Thanks to ALS/LiDAR prospection a significant number of archaeological structures have been identified also in the Warmia and Masuria regions. Among them oval-shaped hillforts, surrounded by perfectly spaced concentric moats and ramparts, located mainly on islands and in wetland areas, have raised particular attention. Based on field prospection and results of preliminary excavations, these objects have been considered as Iron Age hillforts. One of the best preserved objects of this type is on the Radomno Lake island, located several kilometres to the south of Iława town. Integrated geoarchaeological prospection of this hillfort emphasized benefits of using LiDAR in combination with results of geophysical prospection and shallow drillings. Applied methodology enabled to document the hillfort shape, and to study its geological structure and stratigraphy. The results clearly indicate that integration of LiDAR data with geophysical prospecting is indispensable in future archaeological surveys. It is a perfect tool for remote sensing of archaeological objects in forest areas, so far not available for traditional archaeology.