Reports on Geodesy and Geoinformatics Feed

Unmanned aerial vehicle data acquisition methodology and assessment of photogrammetric products for telecommunication mast inventory

Wed, 28 Oct 2026 00:00:00 GMT

UAV (unmanned aerial vehicle) data are widely utilized for the inspection of telecommunication masts, but the quality and accuracy of photogrammetric products largely depend on the method of data acquisition and flight parameters. This study proposes a methodology for flight trajectory planning and acquiring UAV imagery for inventorying telecommunications masts. A crucial component of the methodology is an application that facilitates flight mission planning and enables operators to collect reliable and repeatable data fast. An accuracy analysis was performed for both dense image matching (DIM) point clouds and 3D mesh models to evaluate quality of products with terrestrial laser scanning (TLS) point clouds used as the reference. A similar evaluation was performed with unmanned laser scanning (ULS) data. The experiments demonstrated that the mean distance between the DIM point cloud and the TLS data was not higher than 2 cm and standard deviation was 1.8 cm or less for all surveyed towers while for 3D mesh models these values were less than 1.2 cm and 2.6 cm respectively. A comparative analysis with ULS data also confirmed that both the DIM point cloud and the mesh model meet the accuracy criteria adopted in the research project.

Analysis of the potential of low-cost GNSS receivers in the establishment of geodetic control networks using a static technique

Wed, 28 Oct 2026 00:00:00 GMT

Recent developments in Global Navigation Satellite System (GNSS) technology have significantly improved the performance and quality of inexpensive measuring equipment, namely low-cost GNSS. These devices enable positioning with an accuracy comparable to that of geodetic-grade GNSS receivers. The main objective of this study was to verify whether such receivers are sufficient for establishing geodetic control networks using static measurement techniques, which require high accuracy in both horizontal and vertical directions. Field tests were carried out using several low-cost GNSS receivers and antennas, operated simultaneously with geodetic-grade instruments. The collected observations were processed using commercial software and compared with a benchmark campaign. The analyses considered the lengths of measurement sessions, information about antenna reference point offsets used, and the challenges in calculating baselines with low-cost GNSS receivers. Special attention was paid to minimizing the time required for measurement activities, while maintaining the required accuracy parameters. The results show that low-cost GNSS receivers fulfill the requirements of the relevant national guidelines – i.e., achieving vertical positioning accuracy of not exceeding 0.01 m, as well as horizontal positioning errors of well below 0.07 m. The conducted analyses further confirmed the stability and repeatability of the obtained results for sessions lasting 20 minutes or longer. The conducted work and obtained results confirm that low-cost GNSS receivers’ affordability combined with their high precision makes them a valuable alternative to geodetic instruments in many practical applications.

Legal procedures ensuring the proper performance of tasks in the field of geodesy and cartography

Mon, 21 Sep 2026 00:00:00 GMT

The article focuses on broadly understood legal procedures specified in the provisions of the Act of 17 May 1989 Geodetic and Cartographic Law, aimed at ensuring the correctness of tasks performed in the field of geodesy and cartography. The content of legal norms that define these procedures is examined. The discussion covers whether the current legal regulations contained in the above-mentioned Act, concerning supervision, control, and disciplinary responsibility, are sufficient for the efficient operation of the state and legal entities in the area in question. The main objective of the research was to systematise the issues discussed and to develop directions for change, considering the findings of previous analyses in this area. The interpretation of the relevant legal provisions constitutes a starting point for further research aimed at identifying optimal supervisory, inspection, and other verification mechanisms. The outcome of this research will be the development of a target model of procedures ensuring the proper performance of tasks in the field of geodesy and cartography.

Application of mobile mapping technology in automating inventory and legal compliance checks for advertising signs and devices

Mon, 21 Sep 2026 00:00:00 GMT

The increasing number of advertisements in public spaces, combined with ineffective control mechanisms, leads to growing visual pollution in urban areas. The aim of this study was to develop and evaluate a semi-automated workflow for the inventory and legal compliance assessment of advertising signs and devices using mobile mapping data and geographic information system (GIS) tools. The analysis of legal regulations reveals that their complexity significantly hampers the processes of recording, monitoring, and conducting administrative proceedings. To address these challenges, a methodology based on data collected using a mobile mapping system was developed. This system includes Light Detection and Ranging (LiDAR) scanners, a 360-degree camera, and a Global Navigation Satellite Systems (GNSS)/ Inertial Measurement Unit (IMU) positioning unit, enabling rapid and accurate spatial data collection. The proposed solution covers the entire process – from field data acquisition, through processing, legal and spatial analysis, to support for administrative procedures. Research results confirm the high effectiveness of the proposed approach, demonstrating a clear advantage of mobile laser scanning (MLS) technology over traditional inventory methods in terms of accuracy and operational efficiency. Dedicated software tools were also developed, extending the functionality of the open-source QGIS software. The Street3D application enables comprehensive recording, verification, and analysis of advertising devices in compliance with current regulations. This methodology can significantly support municipal authorities in shaping an orderly, functional, and aesthetically pleasing public space.

Evaluating machine learning algorithms: The role of sample size and quality

Tue, 28 Jul 2026 00:00:00 GMT

This study evaluates the performance of selected machine learning methods, Maximum Likelihood (MLC), Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machine (SVM), and Artificial Neural Networks (ANN), for land use/land cover (LULC) classification using Sentinel-2 satellite imagery. Each algorithm was tested across multiple classification scenarios that systematically varied both training sample size and training sample quality. To emulate realistic imperfections in reference data, controlled levels of label noise were introduced into the training set, and the resulting changes in classification performance were analysed. In addition, each model’s susceptibility to overfitting was assessed by comparing performance on training data and independent test data. To reduce the influence of a single random draw of training and testing pixels, all sampling-based experiments were repeated 10 times using different random seed values, and the reported results were summarized using repeated-run statistics. This design enabled a comparable assessment of how classification accuracy, stability, and generalization depend on dataset size and quality. The results indicate that SVM was the most consistent and reliable method across the tested scenarios, achieving high classification accuracy over a wide range of training sample sizes and maintaining strong robustness under noisy labels. Compared with the other methods, SVM showed lower sensitivity to degraded training data and a smaller tendency to overfit, which makes it a strong baseline choice when reference data are limited or imperfect.

Quantitative assessment of 2D-3D thematic convergence in UAV-based terrain inventory

Thu, 02 Jul 2026 00:00:00 GMT

While geometric accuracy, expressed as Root Mean Square Error (RMSE), serves as the primary benchmark in Unmanned Aerial Vehicle (UAV) photogrammetry, thematic consistency between planar (2D) and volumetric (3D) deliverables remains insufficiently quantified. This study investigates the "accuracy paradox" questioning the assumption that high georeferencing precision inherently ensures thematic reliability. Research was conducted over a 22.6-hectare rural site in southern Poland. Using a UAV photogrammetric model (3 cm Ground Sampling Distance (GSD), 0.136 m RMSE), independent manual land-use delineations were performed on a high-resolution orthomosaic and a dense point cloud. To evaluate discrepancies, the Convergence Index (CI) was introduced, quantifying relative area differences between representations. Results indicate a total thematic discrepancy of 2.4% (0.5419 ha). However, errors were non-uniformly distributed: infrastructural classes showed near-perfect agreement (CI < 1%), whereas forested areas exhibited CI values exceeding 6%. 2D projections tended to overestimate forested areas, creating a false horizontal expansion of tree canopies. Furthermore, a strong negative correlation (Pearson r = –0.95, p < 0.001) was found between image overlap redundancy and thematic divergence. The study concludes that object morphology and 3D reconstruction completeness exert a more significant impact on inventory reliability than nominal georeferencing accuracy. For high-precision cadastral and environmental surveying, integrating 3D point clouds may be necessary, particularly in vegetation-dominated environments, to mitigate systematic distortions inherent in 2D orthomosaic projections.

A practical approach to coupling GNSS and precise geometric leveling

Mon, 18 May 2026 00:00:00 GMT

This study aims to couple satellite data with precise geometric models. The performance assessment of the method is based on the dataset collected at a part of the vertical base geodetic control network in the Podkarpackie province in Poland. We used baselines determined in two 12-hour-long static Global Navigation Satellite System (GNSS) measurement sessions and reference coordinates of vertical base points of the geodetic control network. Baselines obtained from satellite measurements were used for the fusion, considering the height anomalies taken from the corresponding official geoid model PL-geoid2021. Proprietary solutions played a key role in satellite measurements by ensuring the correct performance of long-term measurements without requiring the manual measurement of the height of GNSS antennas relative to the marks of the measured geodetic control points. Two patented solutions were used for the first time in this study. The results confirmed the correctness and high applicability of the presented approach.

Construction of 3D models of the Cracow Fortress Powder Magazine and determination of their accuracy using photogrammetric and terrestrial scanning methods

Wed, 06 May 2026 00:00:00 GMT

This study presents a comparative analysis of two three-dimensional reconstruction models of Powder Magazine no. 2 of the 19h-century Cracow Fortress, developed using terrestrial laser scanning (TLS) and close-range digital photogrammetry to assess the suitability of both methods for the documentation and reconstruction of heritage structures, as well as to evaluate their geometric accuracy and visual quality. The investigated structure was scanned from four positions using a Leica ScanStation P40 and photographed using a Canon EOS 400D camera. Based on the acquired point clouds, two 3D models were generated: a TLS-based model in Autodesk Revit and a photogrammetric model in Trimble SketchUp, both at Level of Detail (LOD) 200. Accuracy assessment was conducted in CloudCompare using the Cloud-to-Cloud (C2C) method, supplemented by visual and historical comparisons. The results show high geometric consistency between the datasets (with deviations below 0.2 m) and confirm the effectiveness and complementarity of both techniques in the documentation of cultural heritage. The developed models provide valuable material for scientific research, conservation planning, education, and digital heritage presentation.

Single-image indoor localization using cross-domain learning from BIM models

Wed, 06 May 2026 00:00:00 GMT

Accurate indoor camera localization is crucial for applications in augmented reality, robotics, and autonomous navigation. While single-image deep learning models for 6-DOF pose regression have shown competitive results on established benchmarks, their development still requires extensive data annotation and hyperparameter tuning. In this work, we investigate the combination of advanced network architectures, transfer learning, and synthetic data to improve single-image indoor pose regression. Our approach employs a ResNet50 backbone pre-trained on the Places365 dataset and further trained and evaluated on established benchmarks. To enhance the training data, synthetic images are generated from 3D BIM models using Unreal Engine, with alignment procedures ensuring accurate correspondence between synthetic and real environments. Real RGB images are preprocessed to resemble synthetic data, enabling effective cross-domain evaluation. Experiments demonstrate that both architectural design and pretraining significantly influence model performance. On the UniMelb dataset (real-to-real scenario), the model achieves 0.21 m and 0.80° errors, surpassing baseline accuracy. We also present cross-validation and synthetic-to-synthetic experiments, providing insights into factors affecting performance and interactions between architecture, pretraining, and dataset characteristics.

Evaluation of open-source libraries and commercial software utilised for dense point cloud generation: a case study of cultural heritage objects

Tue, 21 Apr 2026 00:00:00 GMT

The development of image-based approaches for 3D dense reconstruction has found wide application in the architectural documentation of cultural objects and sites. For this reason, it is crucial to understand the potential and limitations of Multi-View Stereo (MVS) algorithms used in 3D shape reconstruction. This article aims to evaluate the quality and accuracy of dense point generation for cultural heritage objects using open-source (MicMac, OpenMVS, RealityScan), commercial algorithms (Agisoft Metashape and Pix4D), and an Unmanned Aerial Vehicle (UAV) in parallel and skew configurations at two historic wooden structures. To achieve this, a workflow for data evaluation was proposed, incorporating eigenvalues and quality factors, such as planarity, roughness, normal vector variance, and cloud-to-TLS (Terrestrial Laser Scanning) cloud deviation analysis. The results demonstrate that the image-acquisition geometry strongly influences reconstruction accuracy. Parallel configurations consistently produced higher completeness, narrower deviation distributions, and improved geometric fidelity compared to skew configurations. Among commercial solutions, Agisoft Metashape and Pix4D achieved the best overall performance. Open-source algorithms yielded variable results: OpenMVS-SGM achieved competitive accuracy under optimal conditions, while the OpenMVS-Patch-Based Approach offered a balance between density and roughness.

Analysis of the impact of TLS point cloud feature sets on the detection of building displacements using machine learning algorithms

Tue, 21 Apr 2026 00:00:00 GMT

The study addresses the problem of detecting displacements of building walls using terrestrial laser scanning (TLS) data and machine learning methods. Traditional displacement measurement techniques are often time-consuming. They are also limited in capturing the full geometry of monitored objects. In response, this research proposes a methodology based on the analysis of geometric and radiometric features extracted from point clouds. Controlled experiments were conducted with a geodetic rosette equipped with distance-measuring prisms, which were displaced in the XY plane by 4 mm, 9 mm, and 13 mm. Data were recorded with a Leica RTC360 scanner from three stations, yielding nine point clouds. Selected features describing differences between corresponding points in the reference and displaced series were used as input for neural network models. Both binary classification (displacement/non-displacement) and multi-class classification (0, 4, 9, 13 mm displacement) were performed. The results demonstrated high classification accuracy: 99.1% for binary models and 96.0% for multi-class models. Feature ranking revealed that geometric attributes, such as displacement vector length, curvature, and normal vectors, were the most relevant for model training, while color features had minor importance. The study confirmed that scanner position and incidence angle of the laser beam strongly affect classification quality. The developed procedure proved effective in detecting displacements that occur in directions parallel to the plane of building walls. The conclusions drawn from the research constitute a valuable contribution to the theory of monitoring building structures using TLS.

Editorial Note: In Memoriam: Witold Prószyński (1942-2025)

Wed, 31 Dec 2025 00:00:00 GMT

The influence of sunlight on the measurement of slender steel pole inclination – A case study

Wed, 31 Dec 2025 00:00:00 GMT

Many factors cause the deformation of slender structures, such as the weather conditions that significantly affect their geometry. Surveys of such structures are critical for deformation monitoring and, therefore, general safety. Modern surveying methods like electronic tacheometry (ET), Global Navigation Satellite Systems (GNSS), laser scanning (LiDAR, terrestrial (TLS) and mobile (MLS)), and Unmanned Aerial Vehicles (UAVs) provide means for accurate and effective monitoring. Integrating surveying technologies paves the way for an exhaustive approach to slender structure monitoring and provides accurate data to detect deformation and intervene early. Electricity transmission poles exemplify such structures. The poles need to be monitored regularly to ensure operating stability and safety. The article reports a survey of tubular steel pole deflection angles at various times of the year and under various weather conditions. The surveys were accompanied by temperature measurements and a solar irradiance analysis. The maximum horizontal deflection of the pole top was found to be approximately 27 cm over a single sunny day, highlighting the dynamic nature of solar influence. The analyses yielded conclusions regarding measurements of slender steel structures. Specifically, the study confirmed that solar irradiance can cause short-term deflections of the pole top by up to 27 cm in a single day, and uncertainty increases proportionally with structural dynamics. Consequently, recording precise time and weather conditions during surveys is essential to improve rapid, time-constrained measurement accuracy and the operational safety assessment of slender steel structures. This should improve the measurement accuracy and operational safety of slender steel structures.

3D Building documentation using portable LiDAR systems – functionality analysis

Wed, 31 Dec 2025 00:00:00 GMT

Contemporary building documentation increasingly relies on laser scanning technologies that provide rapid and precise spatial data acquisition. Portable LiDAR systems such as the Leica BLK360, as well as mobile devices like the iPad, offer modern tools for efficient documentation of interior spaces, including office rooms. With dedicated applications (e.g., Leica Cyclone Field 360, Leica Cyclone 3DR, MagicPlan, BIMx, AutoCAD Mobile), users can record measurements, create sketches, and generate 3D models and photographic documentation within a single digital environment. The purpose of this study is to assess the dimensional accuracy in the documentation of an office space using portable LiDAR systems. The experiments showed that, for most analysed dimensions, the results agreed within several centimetres, which is sufficient for architectural inventory work. However, the issue of rounded corners was identified, which may significantly influence measurement results depending on the distance-measurement method applied. Reliable accuracy analysis required proper mutual alignment (common georeferencing) of the scans acquired with the selected instruments. To achieve this, point cloud classification was performed to identify surfaces suitable for cloud-to-cloud alignment. A predefined AI-based classification model dedicated to indoor environments was used. The findings confirm that portable LiDAR systems significantly reduce the time required to complete inventory tasks and enable more comprehensive visualisation of interior spaces. This technology serves as an effective tool supporting the design, modernisation, and management of office environments in a digital workflow, although its accuracy-related limitations must be considered.

GNSS sites at Hornsund reveal increase of land uplift rate due to recent acceleration of deglaciation at Svalbard

Wed, 17 Dec 2025 00:00:00 GMT

This paper discusses recent and up-to-date uplift rates at Polish Polar Station at Hornsund (SW Svalbard). Twenty years of continuous Global Navigation Satellite Systems (GNSS) measurements was used to infer contemporary vertical crust deformation due to viscous and elastic response to variable loads. Using environmental models good agreement of observed land uplift with numerical predictions was found. Most of the vertical change stem from Glacial Isostatic Adjustment (GIA), Little Ice Age (LIA) and Present Day IceMelting (PDIM). Significant increase of uplift was observed in the last few years from 9.0mmyr−1 up to 11.5mmyr−1. This can be attributed to increase of ice mass loss at Svalbard archipelago of additional 10 Gt yr−1. In case of GNSS site at Hornsund 80% of PDIM comes from melting of glaciers at south Spitsbergen.

Application of the Simulated Annealing algorithm and robust weight functions for identification of constant reference points in 3D deformation analysis

Wed, 17 Dec 2025 00:00:00 GMT

Identification of the reference base in deformation analysis is a key element in obtaining the correct deformations of the monitored object. As it cannot be assumed that all the reference points are stable, a stability check must be conducted as the initial stage of the deformation analysis. Most known methods used for the identification of stable reference points cover leveling or horizontal networks. This study presents an approach using a coordinate transformation for the comparison of coordinates corresponding to two measurement epochs in 3D deformation analysis. The proposed algorithm is aimed at selecting such coordinate transformation parameters that correspond to the acceptable transformation residuals for the points of the reference base. Three robust adjustment weight functions (Kadaj, Huber, and Danish) were selected as a basis for formulating the objective function. The six 3D transformation parameters create a 6D search space. The optimization algorithm (simulated annealing) was applied for the search through the search space for desirable transformation parameters. The simulated example 3D two-epoch network was used for testing the performance of particular objective functions. The necessary parameters of the objective functions and optimization procedure were selected empirically. The test results confirmed the correctness of the adopted solution and the ability of all objective functions to detect the groups of fitting points. The objective function based on the Danish weight function appeared to be most promising due to the wide possibilities of shaping its features, which enable tailoring the objective function to the specific need.

Effects of observation loss in geodetic determination of horizontal displacements

Mon, 01 Dec 2025 00:00:00 GMT

Regular monitoring of dams is fundamental to ensuring their safety, stability, and smooth operation. However, during the measurement phase, a number of obstacles are encountered that are often difficult to predict at the planning stage of the observation campaign. In such situations, the surveyor must decide whether to continue all planned observations, which may involve a significant extension of working time. An alternative is to reduce the number of observations deliberately, provided the required accuracy and reliability of the data are ensured. This paper examines the impact of missing observations on the position errors of control network points. Using an angular-linear network as an example, a simulation was carried out by excluding observation stations selected at random from subsequent adjustments and by checking its effect on the final result.Additionally, the possibility of removing from the adjustment those observations that were considered problematic for measurement due to various types of obstacles was verified. The results of the conducted studies show that the cautious station elimination prevents network weakening. The necessary removal of problematic observations can be implemented already at the measurement stage. These findings highlight the significant trend of decreasing accuracy in determining the positions of network points. After eliminating 15% of the observations, the control network maintained high accuracy, with the resulting RMSE changing by no more than 10%.

Laser scanning data processed using Msplit estimation and sliding window algorithm

Mon, 10 Nov 2025 00:00:00 GMT

Laser scanning systems are modern measurement techniques generating large datasets. Observations, usually collected as a point cloud, present the general results that can be visualized using specialized software. While the final effect might be impressive from a visualization point of view, it is inconvenient formodeling or extracting detailed information about, for example, terrain, buildings, engineering structures, and deformations. Therefore, data from laser scanning systems require post-processing using several methods reflecting different purposes or data processing stages: data segmentation, modeling, and filtration. Msplit estimation is one of the methods that has proved its effectiveness in laser scanning data processing and determination of terrain profiles, deformation, or building shapes. Processing the complete datasets tends to only yield often inadequate results when high-class computers are used, and it is time-consuming. Therefore, datasets tend to remain segmented. This paper explores a range of several types of segmentation methods that can be used in Msplit estimation. It presents profile determination when data cut out from the original point cloud are divided into intervals of the same length, or the sliding window algorithm is applied. In comparison, the given examples show that the latter approach can providemore reliable results. The application of the sliding window algorithm entails having to make assumptions concerning estimation parameters. The paper offers valuable guidance about both the width of the window and the slide size.

Synergy of BIM, GIS, and open-access geospatial data in 3D modelling for property management

Tue, 04 Nov 2025 00:00:00 GMT

Three-dimensional modelling of buildings requires reliable data sources and sophisticated tools capable of delivering exhaustive models that can facilitate property management. The authors devised a methodology for 3D building modelling using only open-access geospatial databases like Light detection and ranging (LiDAR) scanning, map and photogrammetry resources, and the relevant publicly available land and topography databases. The models integrate building geometry and detailed object information, which makes them versatile tools for property valuation, management, and structural health monitoring. The study brings together Building Information Modeling (BIM) and Geographic Information Systems (GIS) tools that can integrate spatial data and build precise models with details of critical parts of buildings, such as roofs, walls, window and door openings, balconies, terraces, hard infrastructure, and other structural and fit-out components. The methodology’s performance and versatility were verified on single-family residential buildings in Kraków (Poland). The results have confirmed that the constructive collaboration of open-access geospatial data, GIS, and BIM yields high-grade 3D models for structural health monitoring, action planning, and building life cycle management. This approach leads to effective property (resources) management and streamlines planning and taking actions over the life cycle.

Cadaster and land register harmonization in Poland and Ukraine

Tue, 04 Nov 2025 00:00:00 GMT

This study presents an analysis of the functioning of real estate data registration systems in Poland and Ukraine, with a particular focus on the registration of property rights. It examines the historical development of these systems, their current structures, and the existing mechanisms for data exchange between them. The analysis also identifies key challenges related to interoperability and data consistency.The investigation revealed that in Poland, the real estate cadastre and the land register operate as separate systems under the authority of different institutions, despite recording overlapping information. To address issues of data integration, the Integrated Real Estate Information System was introduced to enable the exchange and verification of data between these registers and other public databases. In Ukraine, three independent systems manage real estate data: the State Land Cadastre, the State Register of Real Rights, and the archival records maintained by the Bureau of Technical Inventory (BTI). This fragmentation undermines the completeness and reliability of real estate information, complicating administrative procedures.The findings of this study highlight the urgent need to develop comprehensive legal frameworks and implement advanced technical solutions in both countries to reconcile discrepancies across real estate registers. The research also points to the substantial potential of integrated information systems to deliver accurate, consistent, and up-to-date property data. Empowering such systems with appropriate legal authority and functional capabilities would significantly improve the reliability, transparency, and efficiency of real estate information management.