A practical workflow for road slopes monitoring using handled mobile mapping systems

Performance of mobile terrestrial LiDAR systems for data collection at high speeds on highways

Automated dock-based UAV systems for geohazard monitoring in mountainous terrain

Abstract. This study presents the first systematic field evaluation of dock-based UAV (Uncrewed Aerial Vehicle) systems for geohazard monitoring in mountainous terrain. We assess their potential to provide reliable, high-frequency, and automated monitoring of surface changes across three different hazard scenarios: (1) a fast-moving glacier icefall (Supphellebreen, Norway), (2) an unstable rock slope (Skjøld, Norway), and (3) a post-failure landscape resulting from a catastrophic rock-ice avalanche (Blatten, Switzerland). Effective hazard management requires timely detection of displacement patterns and terrain change. To address these issues, we introduce an automated workflow integrating multitemporal UAV dock data acquisition with an end-to-end processing pipeline for displacement field generation and change detection. The results show that this workflow has the potential to provide data at centimetre-level accuracy before, during, and after hazard events, supporting both precautionary risk assessments and timely decision-making in critical phases of potential hazard evolution. Wider adoption will depend on supportive regulatory frameworks, reliable power and communication infrastructure, and sufficient expertise to ensure effective operation, maintenance, data interpretation and risk management. Overall, dock-based UAV systems represent a significant technological advancement in efficient geohazard monitoring, facilitating rapid response in critical situations, thereby contributing to increased resilience of communities living in vulnerable mountain environments.

Hydromorphological Monitoring and Navigation Assessment on Alluvial River Sections Using Sentinel-2 and Water Gauge Data

Abstract. Monitoring dynamic alluvial rivers is essential for safe inland navigation, yet traditional bathymetric surveys are costly and infrequent. This paper presents an automated method for detecting migrating sandbars by integrating Sentinel-2 satellite imagery with daily water gauge data. Implemented in Google Earth Engine (GEE), the algorithm matches specific water levels with cloud-optimized images to map emerging shoals. Water and sediment were separated using the Sentinel Water Mask (SWM) index, while a 30-meter internal channel buffer mitigated shoreline mixed-pixel errors. The method’s accuracy was validated using 3-meter resolution PlanetScope imagery. Results demonstrated high geometric agreement (mean Intersection over Union = 0.71) and a strong area correlation (R² = 0.97). Notably, the 10-meter Sentinel-2 resolution caused a systematic 26% overestimation of sandbar size. However, for navigation, this overestimation provides a beneficial safety margin that prevents the underestimation of submerged obstacles. By correlating specific gauge levels with sandbar emergence, the extracted 2D contours provide a vital spatial baseline that enables the future estimation of available water columns over specific bottlenecks. Ultimately, this cost-effective procedure allows for the continuous generation of spatial databases, forming a practical foundation for dynamic relative depth mapping within River Information Services (RIS).

Railway parameter extraction with high-precision UAV-photogrammetry: a feasibility study

Abstract. This paper presents a feasibility study on the extraction of railway parameters from high-precision UAV photogrammetry. A two-stage methodology is adopted: first, point-cloud accuracy and rail-surface coverage are optimized through controlled laboratory and field acquisitions; second, the resulting point clouds are evaluated against the local precision requirements for railway parameter extraction. Laboratory tests show that the SfM workflow is intrinsically capable of sub-millimeter agreement under controlled conditions. In the field, standard nadir and higher-altitude flights proved insufficient to reconstruct the narrow rail-side geometry required for accurate gauge estimation. The best results were obtained by combining a 15 m nadir flight with additional side-looking images at 2.5 m and 5 m, yielding local fitted-surface RMS values down to 0.25 mm and about 0.37 mm on the rail running surface. Although the best lightweight UAV configuration still showed a 2.2 mm gauge discrepancy relative to TLS, the laboratory validation and the strong performance of optimized acquisitions indicate that tolerance-compliant railway parameter extraction may be achievable with higher-end UAV platforms and improved rail-side visibility. Overall, the results confirm the strong potential of UAV photogrammetry for near-industrial railway documentation.

Automated and Comprehensive Quality Assessment of Nationwide Aerial LiDAR Data: Insights from the LiDAR-ITA Project

Abstract. National LiDAR programs are increasingly adopted worldwide to support land management, infrastructure planning, and environmental monitoring. Italy launched its most extensive airborne LiDAR operation in July 2025 as part of the Integrated Monitoring System (SIM) project, funded by the National Recovery and Resilience Plan (PNRR). This effort represents the most extensive airborne LiDAR campaign ever conducted in the country, covering over 302,000 km2, including coastal zones and major islands. The acquisition plan is designed to ensure a minimum point density of 10 points/m2 and produce high-resolution DTMs and DSMs at a 0.25 m grid spacing. Given the unprecedented spatial and data volume, a robust, standardised, and fully automated quality assurance framework is essential. This paper presents the methodology used to evaluate geometric consistency and spatial accuracy across the national dataset. Congruence between overlapping flight strips is assessed by automatically extracting 100 × 100 m patches at regular intervals and computing point-to-point distances and cross-section profiles to detect horizontal and vertical discrepancies. Plano-altimetric accuracy is further evaluated through comparisons with terrestrial laser scanning (TLS) data collected in dedicated control areas, where robust plane fitting enables rigorous three-dimensional error estimation. Results from two control areas acquired with different sensors demonstrate the robustness and scalability of the proposed automated framework. The presented approach provides a reliable foundation for delivering high-precision national LiDAR products and offers a framework applicable to future large-scale geospatial acquisition programs.

Vertical Accuracy Assessment of the MOASURE 2 for DTM Generation in Urban Environments

Digital terrain models (DTMs) are essential elevation datasets that represent the morphology of the Earth’s surface and play a critical role in applications, such as urban planning, civil engineering, infrastructure design, and environmental assessment. However, the excessive cost remains the major challenge in obtaining accurate terrain models. Recent advancements in low-cost inertial navigation and motion-sensing technologies offer significant potential to enhance the cost-effectiveness of surveying projects. This study investigates the vertical accuracy and operational usability of a handheld inertial measurement unit (IMU) device (Moasure 2) for DTM generation in urban environments through the comparison with traditional total station and digital levels procedures. It also assesses the device compliance with The American Society for Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards. For this purpose, a comprehensive field survey was conducted in a small urban area characterized by varied terrain morphology. The vertical accuracy of the Moasure 2 was acceptable for many urban mapping applications based on a rigorous analysis of checkpoint data and error patterns, which were quantitatively assessed relative to reference surfaces. Profile-based validation showed that the elevation differences between similar terrain types were mainly within ±25 cm, with minimal bias and symmetric error distributions. The findings indicate that Moasure 2 can be a viable alternative tool for fast DTM generation in low-cost urban projects. It offers significant advantages in terms of portability, ease of use, and reduced fieldwork time compared to conventional methodologies. Furthermore, this study addresses the critical gap in the validation of the new IMU-based surveying technology and provides evidence for choosing appropriate equipment for urban terrain modeling.