The contribution presents a novel approach to the detection and tracking of lanes based on lidar data. Therefore, we use the distance and reflectivity data coming from a one-dimensional sensor. After having detected the lane through a temporal fusion algorithm, we register the lidar data in a world-fixed coordinate system. To this end, we also incorporate the data coming from an inertial measurement unit and a differential global positioning system. After that stage, an original image of the road can be inferred. Based on this data view, we are able to track the lane either with a Kalman filter or by using a polynomial approximation for the underlying lane model.

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.

The TerraSAR-X add-on for Digital Elevation Measurement ( TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.

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.

The prediction of PM2.5 is important for environmental forecasting and air pollution control. In this study, four machine learning methods, ground-based LiDAR data and meteorological data were used to predict the ground-level PM2.5 concentrations in Beijing. Among the four methods, the random forest (RF) method was the most effective in predicting ground-level PM2.5 concentrations. Compared with BP neural network, support vector machine (SVM), and various linear fitting methods, the accuracy of the RF method was superior by 10%. The method can describe the spatial and temporal variation in PM2.5 concentrations under different meteorological conditions, with low root mean square error (RMSE) and mean square deviation (MD), and the consistency index (IA) reached 99.69%. Under different weather conditions, the hourly variation in PM2.5 concentrations has a good descriptive ability. In this paper, we analyzed the weights of input variables in the RF method, constructed a pollution case to correspond to the relationship between input variables and PM2.5, and analyzed the sources of pollutants via HYSPLIT backward trajectory. This method can study the interaction between PM2.5 and air pollution variables, and provide new ideas for preventing and forecasting air pollution.

Terrestrial laser scanning (TLS) is one of the instruments for remote detection of damage of structures (cavities, cracks) which is successfully used to assess technical conditions of building objects. Most of the point clouds analysis from TLS relies only on spatial information (3D–XYZ). This study presents an approach based on using the intensity value as an additional element of information in diagnosing technical conditions of architectural structures. The research has been carried out in laboratory and field conditions. Its results show that the coefficient of laser beam reflectance in TLS can be used as a supplementary source of information to improve detection of defects in constructional objects.

A complete system of a Laser Radar is described in this paper. One explains the principles of the laser and all additional devices used in this system in order to obtain a compact and eye-safe system. The principle and realization of algorithms for controlling the cruise and speed of the vehicle are described. By applying modal control, and choosing the optimal mode for reducing the speed, one derives the system equation and determines its coefficients. Finally, the paper presents simulations of the laser scanning system, the modal control system and the behavior of the system affected by different errors and disturbances. The effects of instrumental errors are defined and simulation is performed illustrating how such a control system is influenced by internal and external disturbances.

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.

Based on the analysis of the LIDAR terrain Digital Elevation Model (DEM), traces of opencast and underground mining of iron ore mining were located and classified. They occur in the zone of ore-bearing deposits outcropping on the north-eastern and north-western bounds of the Holy Cross Mountains. The DEM of an area covered by thirty-six (36) standard sheets of the Detailed Geological Map of Poland on a scale of 1:50,000 was thoroughly explored with remote sensing standards. Four types of ore recovery shafts with accompanying waste heaps were classified. The acquired data on the extent of former mining areas, covered with varying shafts and barren rock heaps could make a basis for distinguishing, according to historical data and in cooperation with archaeologists, the historical development stages of today’s steel industry. According to general knowledge, the iron industry in Europe instigate dates from the Roman times, in the Ist century BC to the IVth century AD, throughout the earlier and the late medieval times, up to the most recent the 1970ties. The usefulness of the LIDAR method has already been amazingly confirmed in archaeological researches worldwide. Many discoveries of ling forgotten, even large entities resulting from human activities in Asia and Central America especially were discovered owed to the LIDAR DEM. Also, traces of human settlements from various historical periods were discovered that way in Poland. The applicability of DEM based on LIDAR data is, in geological studies of surficial geodynamic processes and in geological mapping in Poland, rather contested.

A variety of optoelectronic devices (rangefinders, velocity meters, terrestrial scanners, lidars, free space optics communication systems and others) based on semiconductor laser technology feature low−quality and highly asymmetric beams. It results from optical characteristics of the applied high−peak−power pulsed laser sources, which in most cases are composed of several laser chips, each containing one or a few active lasers. Such sources cannot be considered as coherent, so the resultant beam is formed by the superposition of many optically uncorrelated sub-sources. Far−field distribution of laser spots in such devices corresponds to the shape of laser emitting area, which instead of desired symmetry shows layout composed of one or several discrete lines or rectangles. In some applications, especially if small targets are concerned, it may be crucial to provide more symmetrical and uniform laser beam cross−section. In the paper, the novel strategy of such correction, combining coherent and incoherent approaches, is presented. All aspects of technological implementations are discussed covering general theoretical treatment of the problem, diffractive optical element (DOE) design in the form of computer generated hologram (CGH), its fabrication and testing in case of selected laser module beam correction.

Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW), Delaunay Triangulation (TIN), and supervised Artificial Neural Networks (ANN), for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

In this brief article five bronze fibulae, being exposed in the museum of Şanlıurfa and belonging to the Iron Age, will be presented. At least two of these five were found at Lidar Höyük.