Jul 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· Vol XLIX-B1-2026, pp. 347-351· 0 citations· 1 references
Abstract
Abstract. UAS photogrammetry has become an efficient solution for acquiring high-resolution geospatial data for urban mapping, environmental monitoring, and 3D modelling. However, mission planning still involves a trade-off between data quality and operational efficiency, particularly regarding flight altitude, which directly affects ground sample distance (GSD), point cloud density, and positional accuracy. This study evaluates the influence of flight altitude through a controlled comparison of two urban photogrammetric surveys: a low-altitude flight at 61.2 m (GSD = 1.56 cm/pix, 420 images) and a higher-altitude flight at 121 m (GSD = 3.11 cm/pix, 116 images). Both surveys used RGB cameras with equivalent image resolution mounted on different platforms, which constitutes an experimental limitation, while overlap and processing parameters were kept constant. The results show that the lower-altitude flight produced denser data and better geometric performance, with lower reprojection error and lower check point RMSE. In contrast, the higher-altitude flight provided greater operational efficiency, covering a larger area with fewer images and lower computational demand. These findings indicate that both strategies are technically viable but suited to different objectives: lower altitudes favour geometric detail and positional accuracy, whereas higher altitudes improve productivity and area coverage. Therefore, flight altitude should be selected according to project requirements, balancing geometric quality and operational efficiency.
Remote sensing is widely recognized as a key technology across a wide range of technical and scientific domains, especially in agriculture. Although satellite data have long supported crop monitoring, their limitations in spatial resolution, revisit frequency and cloud coverage have often constrained their applications. High-resolution satellites, available from the beginning of the 2000s, have improved performance, particularly in the field of precision agriculture, but they remain expensive and inflexible. Unmanned Aerial Vehicles perform better in precision agriculture, offering flexibility and high levels of detail; however, their limited operational areas and short endurance flight times constrain their effectiveness. In this evolving landscape, High Altitude Pseudo Satellites (HAPSs), particularly high-altitude balloons, are emerging as a promising new technology that could fill the gaps between satellite and drone remote sensing. These platforms provide large area coverage with high-resolution imagery and long endurance flights at low operational expenses and ease of deployment. This study investigates the operational characteristics, strengths, and geometric limitations of data acquired by the CubeHAPS® platform, a high-altitude pseudo-satellite system, as a prerequisite for its application in precision agriculture. Focusing on experimental campaigns conducted in northern Italy in summer 2024 and 2025, the research characterizes platform stability, image block consistency, and photogrammetric quality through internal metrics. The results demonstrate measurable improvements between the two campaigns, attributed to the introduction of a stabilization system in 2025 and establishing the conditions under which the platform can support reliable photogrammetric reconstruction.
Lorenza Bovio, Victor Miherea, Jannis Fath et al.· Geomatics· 0 citations
This study presents a UAV photogrammetry and GIS-based workflow for generating high-accuracy three-dimensional cadastral models in urban environments. The proposed framework integrates RTK-enabled UAV image acquisition, ground control point (GCP) surveying, photogrammetric reconstruction, GIS-based spatial data management, and accuracy assessment within a unified workflow. A total of 454 aerial images were acquired and processed to generate a dense point cloud, digital surface model, orthomosaic, and textured 3D urban model. Positional accuracy was evaluated using 15 independently surveyed RTK GNSS checkpoints distributed throughout the study area. The results demonstrated a relative accuracy of 1.7 cm and an absolute positional accuracy of 2.47 cm based on independent checkpoint validation, confirming the suitability of the proposed workflow for large-scale cadastral mapping applications. The generated 3D cadastral model enabled accurate extraction and visualization of parcel boundaries, building footprints, and urban spatial features. The findings indicate that UAV photogrammetry combined with GIS provides a cost-effective and reliable approach for developing high-precision three-dimensional cadastral datasets that support modern land administration, urban planning, and digital city management.
Salar Mirzapour, Z. Azizi, H. Zavar et al.· Scientific Reports· 0 citations
Abstract. With the in-depth penetration of Unmanned Aerial Vehicle (UAV) technology in fields such as geographic information surveying and mapping, the urban low-altitude economy has ushered in a critical opportunity for rapid development. However, surveying and mapping UAVs are confronted with the core technical bottleneck of "accurately determining the safety of flight routes", while issues such as airspace congestion and collision risks have become increasingly prominent. How to enable UAVs to perceive the complex environment in which they operate has thus emerged as a key challenge. Based on remote sensing images, 3D geographic data, and other relevant datasets, this study comprehensively applies multi-source data fusion technology to construct the theoretical framework and technical system of the "Urban Low-Altitude Surveying UAV Flight Safety Zones". It classifies the core causal factors affecting flight safety into three major categories: building height, electromagnetic interference, and controlled areas. Through a series of key technical processes, a standardized 3D spatial grid system is established, and a computable "risk perception" model is developed. Taking Shanghai Municipality as the empirical research area, empirical analysis is conducted using remote sensing images, ultimately generating a low-altitude flight safety field grid dataset covering the entire administrative region of Shanghai. Verification results indicate that this achievement can effectively identify the spatial distribution characteristics of potential safety hazards and height constraints, significantly reduce the collision probability between UAVs and obstacles, and provide standardized technical support for the flight safety of low-altitude surveying UAVs.
Sijian Wang, Wen Zhang· The International Archives o...· 0 citations
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.
Lucas De Burggrave, E. Bartczak, S. Cuypers et al.· The International Archives o...· 0 citations
Abstract. We evaluate the performance of the newly introduced DJI Zenmuse L3 UAV-borne LiDAR system in comparison to its predecessor L2. We conducted test flights over three representative environments — built-up, infrastructure, and forested areas — to assess accuracy, precision, spatial resolution, and vegetation penetration. The L3 introduces a single high-performance 1535nm laser with reduced beam divergence and increased pulse repetition rate, enabling higher point density and improved measurement quality. Results show significantly enhanced precision (cm-level), better strip alignment, and improved capability to resolve fine structures such as power lines. Residual analysis indicates reduced noise and tighter point distributions compared to L2. Furthermore, vegetation penetration is substantially improved, achieving up to 77% ground coverage compared to 48% for L2 in our experiment. Despite minor systematic offsets, the L3 demonstrates clear advantages in all tested aspects, confirming its suitability for high-resolution 3D mapping and representing an advancement in low-cost UAV LiDAR technology.
Gottfried Mandlburger, Elisabeth Ötsch, Philipp Knopf· The International Archives o...· 0 citations
Abstract. Unmanned aerial vehicle (UAV) photogrammetry is indispensable for Arctic sea ice research, enabling high-resolution mapping and supporting critical operations. However, drifting sea ice, which is characterized by continuous motion that violates the fundamental ‘static-scene’ assumption, and no ground control points (GCPs), poses challenges to orthomosaic accuracy. This study presents a systematic framework for assessing and improving the relative accuracy of UAV photogrammetry over drifting Arctic sea ice, using 18 shipborne UAV missions conducted during the Following Arctic/Antarctic iCE 2024 expedition. A time-dependent correction method based on synchronized vessel GNSS data, referred to as drift correction, was employed to compensate for drift in the exterior orientation parameters of the UAV imagery. In the absence of GCPs, relative accuracy was evaluated using shipborne constrained and check scale bars. Results show that under raw conditions, with a ground sampling distance (GSD) of 2–5 cm, the orthomosaics achieved a mean root mean square error (RMSE) of 0.304 m. The RMSE showed a strong positive correlation with ice drift speed (r = 0.71) and drift distance (r = 0.79), while the flight–drift angle showed negligible influence (r = −0.13). Drift correction alone reduced the mean RMSE to 0.075 m, achieving error reductions of up to 0.6 m under high-drift conditions. The incorporation of scale bar constraints further enhanced accuracy to a mean RMSE of 0.043 m. These findings validate the effectiveness of drift correction and scale-constraint-based optimization, offering a practical framework for accuracy assessment and mission implementation in dynamic polar environments.
Zhiqi He, Shuhang Zhang, Daikun Yang et al.· The International Archives o...· 0 citations
