Search Results (220)

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

The preservation of historical monuments is vital, especially in societies that do not have a rich written history. One method to ensure the preservation and transmission of cultural heritage is to reuse abandoned historical buildings. “On-site documentation” is fundamental for effective adaptive reuse. During this process, the plans and construction phases of many historical buildings are obtained for the first time. This study goes beyond theoretical boundaries and focuses on approaching the documentation, evaluation, reuse and preservation of cultural heritage from an operational perspective. The historical building in question was built as a primary school by Armenian craftsmen at the end of the 19th century in the town of Zara, Sivas. After changing hands, it became a mansion and is currently abandoned. This study discusses and proposes the buildings’ reuse as an urban memory museum by means of CAD-supported on-site analytical surveys based on classical, laser, and total station measurements. Full article

This study focuses on a subtropical evergreen broad-leaved forest in China, utilizing a large permanent plot established in the Yaoluoping National Nature Reserve. By integrating data from a full-stem census and total station surveying, we analyzed the phylogenetic structure of the plant community as a whole and across different life-history stages (saplings, juveniles, and adults) while quantitatively assessing microtopographic variables and an interspecific competition index. The results indicate that the overall community in the Yaoluoping plot exhibited a weakly overdispersed pattern, and key microtopographic factors—including aspect, terrain position index (TPI), terrain ruggedness index (TRI), roughness, and flow direction—significantly influenced the evolution of phylogenetic structure. Distinctions were also observed among saplings, juveniles, and adults in phylogenetic structuring across life-history stages. Specifically, saplings displayed a higher degree of phylogenetic clustering, significantly influenced by density, elevation, TPI, and flow direction—suggesting that environmental filtering predominates at this stage, possibly due to lower environmental tolerance, limited dispersal ability, and conspecific negative density dependence. In contrast, juveniles and adults showed a more dispersed phylogenetic structure, with density, interspecific competition, aspect, TRI, TPI, and roughness significantly correlated with phylogenetic patterns, indicating that competition and niche differentiation become increasingly important as trees mature and establish within the community. Interspecific competition was found to play a crucial role in community structuring: the competition index was generally negatively correlated with the net relatedness index (NRI) and nearest taxon index (NTI) in juveniles and adults, implying that intense competition leads to the exclusion of some species and reduces overall diversity, with the strength and significance of competitive effects differing across stages. This study enhances our understanding of the complex interplay between microtopography and interspecific competition in shaping the phylogenetic structure and diversity of subtropical evergreen broad-leaved forests, elucidates the coupled mechanisms among microtopography, phylogenetic structure, and competition, and provides a scientific basis for forest conservation and management. Full article

Field data, as the basis for planning and designing forest roads, must have high spatial accuracy. Classical (using a theodolite and a level) and modern (based on total stations and GNSSs) surveying methods are used in current field data survey for forest road design. This study analyzed the spatial accuracy of classical and modern surveying methods, the accuracy of spatial data recorded using a UAV equipped with an RGB camera at different flight altitudes, and the accuracy of lidar data of the Republic of Croatia. This study was conducted on a forest area where salvage logging was carried out, which enabled the use of a GNSS receiver in RTK mode as a reference method. The highest RMSE values of the spatial coordinates were recorded for measurements obtained with the classical surveying method (0.89 m) and a total station (0.33 m). The flight altitude of the UAV did not significantly affect the spatial error of the collected data, which ranged between 0.07 and 0.09 m. The cross-terrain slope, as one of the factors that significantly affect the amount of earthworks, did not differ statistically significantly between the methods. The ALS error was strongly influenced by the cross-terrain slope. The authors conclude that the new survey methods (SfM and lidar data) provide high-accuracy data but also draw attention to challenges in their use, such as vegetation and biomass on the ground. Full article

This study presents an integrated surveying methodology for efficient and accurate cadastral documentation, combining UAV photogrammetry, SLAM-based terrestrial and aerial scanning, and conventional geodetic measurements. Designed to be scalable across various cadastral and planning contexts, the workflow was tested in Charlottenburg, Romania’s only circular heritage village. The approach addresses challenges in built environments where traditional total station or GNSS techniques face limitations due to obstructed visibility and complex architectural geometries. The SLAM system was initially deployed in mobile scanning mode using a backpack configuration for ground-level data acquisition, and was later mounted on a UAV to capture building sides and areas inaccessible from the main road. The results demonstrate that the integration of aerial and terrestrial data acquisition enables precise building footprint extraction, with a reported RMSE of 0.109 m between the extracted contours and ground-truth total station measurements. The final cadastral outputs are fully compatible with GIS and CAD systems, supporting efficient land registration, urban planning, and historical site documentation. The findings highlight the method’s applicability for modernizing cadastral workflows, particularly in dense or irregularly structured areas, offering a practical, accurate, and time-saving solution adaptable to both national and international land administration needs. Beyond the combination of known technologies, the innovation lies in the practical integration of terrestrial and aerial SLAM (dual SLAM) with RTK UAV workflows under real-world constraints, offering a field-validated solution for complex cadastral scenarios where traditional methods are limited. Full article

This article examines the combined use of UAV (Unmanned Aerial Vehicle) photogrammetry and TLS (Terrestrial Laser Scanning) to detect changes in coastal cliffs in the Strunjan Nature Reserve. Coastal cliffs present unique surveying challenges, including limited access, unstable reference points due to erosion, GNSS (Global Navigation Satellite System) signal obstruction, dense vegetation, private property restrictions and weak mobile data. To overcome these limitations, UAV and TLS techniques are used with the help of GNSS and TPS (Total Positioning Station) surveying to establish a network of GCPs (Ground Control Points) for georeferencing. The methodology includes several epochs of data collection between 2019 and 2024, using a DJI Phantom 4 RTK for UAV surveys and a Riegl VZ-400 scanner for TLS. The data processing includes point cloud filtering, mesh comparison and a DoD (DEM of difference) analysis to quantify cliff surface changes. This study addresses the effects of vegetation by focusing on vegetation-free regions of interest distributed across the cliff face. The results aim to demonstrate the effectiveness and limitations of both methods for detecting and monitoring cliff erosion and provide valuable insights for coastal management and risk assessment. Full article

Planning in forestry should be based on accurate and reliable data. UAVs equipped with RGB cameras can enable fast and relatively cheap surveys, but their accuracy depends on many factors. Therefore, it is necessary to determine when UAVs can be used and when this type of survey gives data that does not reflect the true ground situation. This research analyzed the usability of a UAV, equipped with a RGB camera, for recording normal cross-sections and side ditch depths of the forest road in a lowland forest. The research was conducted in two time periods: during winter and spring, i.e., outside and during the vegetation season. DTMs of the area researched were created based on aerial photographs taken with the UAV, Z values of terrain points were read, and the depths of side ditches were calculated based on read Z values. The water depth in the side ditches and the vegetation height on the entire road body width were recorded to determine the influence of these two variables on the UAV survey error. Terrain points were recorded with the total station, which was the reference measurement method. An analysis of the obtained (read) DTM Z values revealed RMSE values of 10.09 cm for winter (outside vegetation) and 36.41 cm for spring (vegetation) UAV survey. The side ditch, calculated based on the DTM of the winter and spring periods of UAV recording, were statistically significantly different from the side ditch depths measured using the total station. Correcting the obtained data with water depth and vegetation height lowered the differences in Z values, as well as the ditch depths visible from ${RMSE}_Z$ (7.70 cm) for the winter UAV survey, with no statistically significant difference in side ditch depths. In the case of the correction of spring recording data, ${RMSE}_Z$ was smaller (23.41 cm) than before correction (36.41 cm), and the depth of the side ditches was still statistically significantly different. The authors conclude that water and ground vegetation can significantly affect UAV survey accuracy. In the winter period, side ditch depth measurement is possible in areas where water is not present. If water is present, manual measurement of water height and correction of obtained UAV data can improve data accuracy. On the other hand, spring or vegetation period UAV surveys are highly affected by ground vegetation height and the authors do not recommend surveys in that period. Full article

In electrical power systems, from generation power stations down to distribution substations, power transformers play a key role in ensuring reliable electricity transfer in the correct range from the generating source to the end-users. Over time, due to their operational demands and other various factors, transformers become susceptible to failures which threaten their reliability and life span. To address this issue, various transformer fault diagnosis methods are employed to detect and monitor the state of transformers, such as the dissolved gas analysis (DGA) method. In this paper, a systematic literature review (SLR) is conducted using the Preferred Reporting Items for Systematic Reviews (PRISMA) framework to record and screen current research work pertaining to the application of machine learning algorithms for DGA-based transformer fault classification. This study intends to assess and identify potential literature and methodology gaps that must be explored in this research field. In the assessment of the literature, a total of 124 screened papers published between 2014 and 2024 were surveyed using the developed PRISMA framework. The survey results show that the majority of the research conducted for transformer fault classification using DGA employs the support vector machine (32%), artificial neural network (17%), and k-Nearest Neighbor (12%) algorithms. The survey also reveals the countries at the forefront of transformer fault diagnosis and a classification based on DGA using machine learning algorithms. Furthermore, the survey shows that the majority of research conducted revolves around fault diagnosis with an emphasis on improving the accuracy of techniques such as SVM and ANN. At the same time, limited effort is put into other key metrics such as precision, Mean Squared Error, and R-Squared, and also, current works surveyed do not explore regularization techniques for preventing overfitting and underfitting of the proposed models. Full article

Between 2022 and 2023, four systematic fish surveys were carried out in the Poyang Lake basin (PLB), capturing 49,192 fish (7017 kg) and identifying 120 species from 10 orders, 21 families, and 70 genera. Cypriniformes were the most dominant, accounting for 79 species. The spring and autumn surveys collected 25,734 and 23,458 individuals, respectively, with corresponding biomasses of 3978 kg and 3038 kg. Dominant species (IRI > 1000) in the study area included Hemiculter leucisculus, Megalobrama skolkovii, Hypophthalmichthys molitrix, and Aristichthys nobilis. Additionally, critically endangered species such as Ochetobius elongatus, Myxocyprinus asiaticus, and Acipenser sinensis as well as exotic species like Cirrhinus mrigala and euryhaline species like Cynoglossus gracilis and Hyporhamphus intermedius were observed. Hierarchical clustering grouped the survey stations into three distinct areas (PYS, XBMS, and XBUS), with the ANOSIM analysis showing highly significant differences (R = 0.893, p < 0.01). Redundancy analysis (RDA) indicated that in spring, total phosphorus (TP) and temperature were the main factors influencing variability (80.50%), while in autumn, temperature, oil, and pH were the key factors (75.20%). This study emphasizes the predictable changes in fish community composition caused by environmental gradients and highlights the need for ongoing monitoring to effectively manage and protect the ecosystem, particularly in the post-fishing ban period. Full article

The main objective of this paper is to investigate the performance of the Network Real-time Kinematic (NRTK) technique in hydrographic surveying and check whether it meets the International Hydrography Organization (IHO) minimum bathymetry standards for the safety of navigation hydrographic surveys. To this end, the KAU-Hydrography 2 vessel was used to conduct a hydrographic survey session at Sharm Obhur. NRTK corrections were streamed in real time from the KSA-CORS NTRIP server and GNSS data were collected at the same time at the base station using a Trimble SPS855 GNSS receiver. Multibeam records were collected using a Teledyne RESON SeaBat T50-P multibeam echosounder in addition to Valeport’s sound velocity profiler records and Applanix POSMV data. Applanix POSPac MMS 8.3 software was used to process the GNSS data of the base station along with the POSMV data to obtain the Smoothed Best Estimate of Trajectory (SBET) file, which is used as a reference solution. The NRTK solution is then compared with the reference solution. It is shown that the Total Horizontal Uncertainty (THU) and the Total Vertical Uncertainty (TVU) of the NRTK solution are 6.38 cm and 3.10 cm, respectively. Statistical analysis of the differences between the seabed surface generated using the NRTK solution and the seabed surface generated using the Post-Processed Kinematic (PPK) technique showed an average of −0.19 cm and a standard deviation of 2.4 cm. From these results, we can conclude that the KSA-CORS NRTK solution successfully meets IHO minimum bathymetry standards for the safety of navigation hydrographic surveys at a 95% confidence level for all orders of hydrographic surveys. Full article

The accuracy and stability of Very Long Baseline Interferometry (VLBI) systems are essential for maintaining global geodetic reference frames such as the International Terrestrial Reference Frame (ITRF). This study focuses on the precise determination of the VLBI Invariant Point (IVP) and the detection of antenna axis offset. Ground-based surveys were conducted at the Sejong Space Geodetic Observatory using high-precision instruments, including total station, to measure slant distances, as well as horizontal and vertical angles from fixed pillars to reflectors attached to the VLBI instrument. The reflectors comprised both prisms and reflective sheets to enhance redundancy and data reliability. A detailed stochastic model incorporating variance component estimation was employed to manage the varying precision of the observations. The analysis revealed significant measurement variability, particularly in slant distance measurements involving prisms. Iterative refinement of the variance components improved the reliability of the IVP and antenna axis offset estimates. The study identified an antenna axis offset of 5.6 mm, which was statistically validated through hypothesis testing, confirming its significance at a 0.01 significance level. This is a significance level corresponding to approximately a 2.576 sigma threshold, which represents a 99% confidence level. This study highlights the importance of accurate stochastic modeling in ensuring the precision and reliability of the estimated VLBI IVP and antenna axis offset. Additionally, the results can serve as a priori information for VLBI data analysis. Full article

Limited information exists on the diet of snow leopards (SL), factors affecting livestock mortality, and local attitudes toward SL conservation in the Manaslu Conservation Area (MCA), Nepal. Therefore, we aim to investigate the dietary preferences of SL, the factors influencing livestock mortality, and local conservation attitudes. From November 2021 to January 2022, 23 SL scats were collected along 24 transects (total length: 21.6 km) in MCA. Camera traps, set within 4 km × 4 km grids at 28 stations for 661 trap nights, were used to assess prey availability. Jacobs’ index calculated prey preference, while a Generalized Linear Mixed Model (GLMM) assessed factors linked to livestock depredation. Additionally, 65 households from two villages were randomly selected in a survey on depredation and conservation attitudes. Scat analysis identified six wild prey species, including pika (Ochotona sp.), Himalayan tahr (Hemitragus jemlahicus), and blue sheep (Pseudois nayaur), as well as three domestic species: ox/cow, yak, and horse. Himalayan tahr had the highest presence in the SL diet (40%). Despite pika having the highest Relative Abundance Index (RAI), SL strongly preferred horses and avoided pika. Larger prey, such as horses, Himalayan tahr, and blue sheep, were highly preferred. Households with more livestock experienced higher depredation rates. Local attitudes toward SL conservation were generally positive, with an average score of 2.59. We recommend an integrated SL conservation plan in MCA, incorporating local participation, income diversification, and employment programs to mitigate conflicts and promote coexistence. Full article

Background/Objectives: The COVID-19 pandemic has emphasized the importance of preparedness in preventing the spread of infectious diseases, especially in Emergency Departments (EDs), where initial patient assessments and triage occur. This study aims to evaluate the current practices and available tools for infection control in Pediatric EDs across Italy, focusing on the differences between various hospital types and regional settings. Methods: A cross-sectional national survey was conducted in February 2022, targeting healthcare workers in Pediatric EDs across Italy. The survey, distributed via the Italian Society for Pediatric Emergency and Urgent Medicine (SIMEUP) mailing list, collected data on infection control measures, including the availability of hand hygiene stations, personal protective equipment, disinfection protocols, and the use of rapid diagnostic tests. Results: A total of 80 questionnaires were completed from 119 (67.2%) different ERs. The majority of respondents were from Northern Italy (47.5%) and worked in hospitals with 24 h pediatric assistance (48.8%). Less than half of non-pediatric hospitals had separate access for children, potentially exposing them to adult pathogens. Across all settings, basic infection control measures, such as providing masks and hand gel, were widely implemented. However, significant differences were observed in the availability of social distancing, informational materials, and dedicated pediatric pathways, with I level assistance hospitals less likely to have these resources. Rapid diagnostic tests were available in most settings, but the focus was predominantly on SARS-CoV-2, despite other respiratory pathogens’ relevance in pediatric care. Conclusions: Strengthening preparations for future pandemics will be crucial in enhancing the resilience of healthcare systems and ensuring the safety of both patients and healthcare workers in the face of emerging infectious threats. Full article

This study evaluates the performance of the ZEB Horizon RT portable mobile laser scanner (MLS) in simulating silvicultural thinning operations across three different Tuscan forests dominated by Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), Italian cypress (Cupressus sempervirens L.), and Stone pine (Pinus pinea L.). The aim is to compare the efficiency and accuracy of the MLS with traditional dendrometric methods. The study established three marteloscopes, each covering a 50 m × 50 m plot area (0.25 ha). Traditional dendrometric methods involved a team georeferencing trees using a total station and measuring the diameter at breast height (DBH) and selected tree heights (H) to calculate the growing stock volume (GSV). The MLS survey was carried out by a two-person team, who processed the point cloud data with LiDAR 360 software to automatically identify the tree positions, DBH, and H. The methods were compared based on the time, cost, and simulated felling volume. The MLS method was more time-efficient, saving nearly one and a half hours per marteloscope, equivalent to EUR 170. This advantage was most significant in denser stands, especially the Italian cypress forest. Both methods were comparable in terms of accuracy for Douglas-fir and Stone pine stands, with no significant differences in felling number or volume, although greater differences were noted for the Italian cypress forest. Full article

Real-time monitoring of riverine-dissolved organic carbon (DOC) and its controlling factors is critical for formulating strategies regarding the river basin and marginal seas pollution prevention and control. In this study, we established a linear regression formulation that relates the permanganate index (COD_Mn) to the DOC concentration based on in situ measurements collected on five field surveys in 2023–2024. This regression formulation was used on a large number of data collected from automatic monitoring stations in the Qiantang River area to construct a daily quasi-in situ database of DOC concentration. By combining the quasi-in situ DOC data and Sentinel-2 measurements, an enhanced algorithm for empirical DOC estimation was developed (R² = 0.66) using the extreme gradient boosting (XGBoost) method and its spatial and temporal variations in the Qiantang River were analyzed from 2016 to 2023. Spatially, the main stream of the Qiantang River exhibited an overall decreasing and increasing trend influenced by population density, economic development, and pollutant discharge in the basin area, and the temporal distribution of DOC was controlled by meteorological conditions. The DOC contents had the highest in summer, primarily due to high rainfall and leaching. The inter-annual variation in DOC concentration was influenced by the total annual runoff volumes, with a minimum level of 2.24 mg L⁻¹ in 2023 and a maximum level of 2.45 mg L⁻¹ in 2019. The monthly DOC fluxes ranged from 6.3 to 13.8 × 10⁴ t, with the highest values coinciding with the maximum river discharge volumes in June and July. The DOC levels in the Qiantang River remained relatively high in recent years (2016–2023). This study enables the concerned stakeholders and researchers to better understand carbon transportation and its dynamics in the Qiantang River and its coastal areas. Full article