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Traditional photogrammetry techniques require the use of Ground Control Points (GCPs) to accurately georeference aerial images captured by unmanned aerial vehicles (UAVs). However, the process of collecting GCPs can be time-consuming, labor-intensive, and costly. Real-time kinematic (RTK) georeferencing systems eliminate the need for GCPs without deteriorating the accuracy of photogrammetric products. In this study, a statistical comparison of four RTK georeferencing systems (continuously operating reference station (CORS)-RTK, CORS-RTK + post-processed kinematic (PPK), RTK + dynamic RTK 2 (DRTK2), and RTK + DRTK2 + GCP) is presented. The aerial photo was acquired using a Dà-Jiāng Innovation Phantom 4 RTK. The digital photogrammetric processing was performed in Agisoft Metashape Professional software. A pair of global navigation satellite systems (GNSSs) receiving antennas model CHC x900 were used for the establishment of check points (CPs). The accuracy of photogrammetric products was based on a comparison between the modeled and CP coordinates. The four methods showed acceptable planimetric accuracies, with a root mean square error (RMSE) ranging from 0.0164 to 0.0529 m, making the RTK-CORS + PPK method the most accurate (RMSE = 0.0164 m). RTK-CORS + PPK, RTK-DRTK2, and RTK-DRTK2 + GCP methods showed high altimetric accuracies, with RMSE values ranging from 0.0201 to 0.0334 m. In general, RTK methods showed a high planimetric and altimetric accuracy, similar to the accuracy of the photogrammetric products obtained using a large number of GCPs.

Global navigation satellite systems (GNSSs) provide a common positioning method that utilizes satellite signals to determine the spatial location of a receiver. However, there are several error factors in standalone GNSS positioning due to instrumental, procedural, and environmental factors that arise during the signal transmission process, and the final positioning error can be up to several meters or greater in length. Thus, real-time kinematic (RTK) correction and post-mission precise point positioning (PPP) processing technologies are proposed to improve accuracy and accomplish precise position measurements. To evaluate the geolocation accuracy of mosaicked UAV images of an abandoned mine site, we compared each orthomosaic image and digital elevation model obtained using standalone GNSS positioning, differential (RTK) GNSS positioning, and post-mission PPP processing techniques. In the three types of error evaluation measure (i.e., relative camera location error, ground control points-based absolute image mapping error, and volumetric difference of mine tailings), we found that the RTK GNSS positioning method obtained the best performance in terms of the relative camera location error and the absolute image mapping error evaluations, and the PPP post-processing correction effectively reduced the error (69.5% of the average total relative camera location error and 59.3% of the average total absolute image mapping error) relative to the standalone GNSS positioning method. Although differential (RTK) GNSS positioning is widely used in positioning applications that require very high accuracy, post-mission PPP processing can also be used in various fields in which it is either not feasible to operate expensive equipment to receive RTK GNSS signals or network RTK services are unavailable.

Annotation of foot-contact and foot-off events is the initial step in post-processing for most quantitative gait analysis workflows. If clean force plate strikes are present, the events can be automatically detected. Otherwise, annotation of gait events is performed manually, since reliable automatic tools are not available. Automatic annotation methods have been proposed for normal gait, but are usually based on heuristics of the coordinates and velocities of motion capture markers placed on the feet. These heuristics do not generalize to pathological gait due to greater variability in kinematics and anatomy of patients, as well as the presence of assistive devices. In this paper, we use a data-driven approach to predict foot-contact and foot-off events from kinematic and marker time series in children with normal and pathological gait. Through analysis of 9092 gait cycle measurements we build a predictive model using Long Short-Term Memory (LSTM) artificial neural networks. The best-performing model identifies foot-contact and foot-off events with an average error of 10 and 13 milliseconds respectively, outperforming popular heuristic-based approaches. We conclude that the accuracy of our approach is sufficient for most clinical and research applications in the pediatric population. Moreover, the LSTM architecture enables real-time predictions, enabling applications for real-time control of active assistive devices, orthoses, or prostheses. We provide the model, usage examples, and the training code in an open-source package.

Post-processing kinematics (PPK) is positioning process in which signals received from a mobile receiving device store location data can be adjusted using corrections from a reference station after data has been collected. The processed kinematic screening method provides the surveyor with a technique for high production survey measurements and can be used in areas with minimal satellite barriers. PPK uses significantly reduced observation times compared to static or fast static observations. This method requires least squares adjustment or another multiple basic statistical analysis that can produce a weighted average of observations. The results obtained using PPK are between 1 cm and 3 cm for horizontal coordinates and from 1 cm to 10 cm for vertical coordinates.

We studied some exposures of the Roccacaramanico Conglomerate (RCC), a calcareous-clastic mega-bed intercalated within the Late Messinian–Early Pliocene pelitic succession of the La Queglia and Maiella tectonic units (central Apennines). The outcrops, localized in the overturned limb of a kilometric-scale syncline, show a complex array of fractures, including multiple systems of closely spaced cleavages, joints, and mesoscopic faults, which record the progressive deformation associated with the Late Pliocene thrusting. Due to the extent of the investigated sites and a large amount of data to collect, we applied a multi-methodology survey technique integrating unmanned aerial vehicle (UAV) technologies and digital mapping in the field. We reconstructed the 3D digital outcrop model of the RCC in the type area and defined the 3D pattern of fractures and their time–space relationships. The field survey played a pivotal role in determining the various sets of structures, their kinematics, the associated displacements, and relative chronology. The results unveiled the investigated area’s tectonic evolution and provide a deformation model that could be generalized in similar tectonic contexts. Furthermore, the methodology allows for evaluating the reliability of the applied remote survey techniques (i.e., using UAV) compared to those based on the direct measurements of structures using classic devices. Our purpose was to demonstrate that our multi-methodology approach can describe the tectonic evolution of the study area, providing consistent 3D data and using a few ground control points. Finally, we propose two alternative working methods and discuss their different fields of application.

The aim of this paper is to study and analyze the Jack Up Vessel (JUV) foundation height accuracy, with the objective of the precise installation of an Offshore Wind Farm (OWF), based on Real Time Kinematic (RTK) and Post-Processing Kinematic (PPK) modes applied on short and long baselines length. The offshore wind farm project is located far from the coastline, not always in the standard working range of RTK. The standard allowed vertical installation tolerance for foundations is less than 10 cm. Taking into account all error sources, deformation of the vessel, motion, lever arms that impact the height measurement of the foundation, it is required that RTK and PPK perform within an accuracy less than 5 cm. In this work, all measures will be evaluated according to the tolerance specification of ±2.5 cm. The survey GNSS tests executed during the project on board of a JUV should be able to provide answers to the following questions: Despite the critical environment, does RTK method allow reaching the theoretical specifications? Does PPK improve accuracy compared to the RTK solution? What is the influence of the baseline length? How much of the time the results fall within the range tolerance? What is the ideal logging period in which accurate and reliable results can be obtained? What is the influence of the hardware and software variants used in testing process on the results accuracy? Based on the test results and analysis a clear description of the influence of different parameters in the OWF precise height measurement in challenging environment will be exposed.

This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-exploring random tree (RRT). The proposed algorithm applies interpolation to the path generated by the sampling-based path planning algorithm. In this study, the proposed algorithm is applied to the path created by RRT-connect and six environmental maps were used for the verification. It was visually and quantitatively confirmed that, in all maps, not only path lengths but also the piecewise linear shape were decreased compared to the path generated by RRT-connect. To check the proposed algorithm’s performance, visibility graph, RRT-connect algorithm, Triangular-RRT-connect algorithm and post triangular processing of midpoint interpolation (PTPMI) were compared in various environmental maps through simulation. Based on these experimental results, the proposed algorithm shows similar planning time but shorter path length than previous RRT-like algorithms as well as RRT-like algorithms with PTPMI having a similar number of samples.

Unmanned aerial photogrammetric surveys are increasingly being used for mapping and studying natural hazards, such as rockfalls. Surveys using unmanned aerial vehicles (UAVs) can be performed in remote, hardly accessible, and dangerous areas, while the photogrammetric-derived products, with high spatial and temporal accuracy, can provide us with detailed information about phenomena under consideration. However, as photogrammetry commonly uses indirect georeferencing through bundle block adjustment (BBA) with ground control points (GCPs), data acquisition in the field is not only time-consuming and labor-intensive, but also extremely dangerous. Therefore, the main goal of this study was to investigate how accurate photogrammetric products can be produced by using BBA without GCPs and auxiliary data, namely using the coordinates X0, Y0 and Z0 of the camera perspective centers computed with PPK (Post-Processing Kinematic). To this end, orthomosaics and digital surface models (DSMs) were produced for three rockfall sites by using images acquired with a DJI Phantom 4 RTK and the two different BBA methods mentioned above (hereafter referred to as BBA_traditional and BBA_PPK). The accuracy of the products, in terms of the Root Mean Square Error (RMSE), was computed by using verification points (VPs). The accuracy of both BBA methods was also assessed. To test the differences between the georeferencing methods, two statistical test were used, namely a paired Student’s t-test, and a non-parametric Wilcoxon signed-rank. The results show that the accuracy of the BBA_PPK is inferior to that of BBA_traditional, with the total RMSE values for the three sites being 0.056, 0.066, and 0.305 m, respectively, compared to 0.019, 0.036 and 0.014 m obtained with BBA_traditional. The accuracies of the BBA methods are reflected in the accuracy of the orthomosaics, whose values for the BBA_PPK are 0.039, 0.043 and 0.157 m, respectively, against 0.029, 0.036 and 0.020 m obtained with the BBA_traditional. Concerning the DSM, those produced with the BBA_PPK method present accuracy values of 0.065, 0.072 and 0.261 m, respectively, against 0.038, 0.060 and 0.030 m obtained with the BBA_traditional. Even though that there are statistically significant differences between the georeferencing methods, one can state that the BBA_PPK presents a viable solution to map dangerous and exposed areas, such as rockfall transit and deposit areas, especially for applications at a regional level.

Walking is one of the fundamental motor tasks executed during aquatic therapy. Previous kinematics analyses conducted using waterproofed video cameras were limited to the sagittal plane and to only one or two consecutive steps. Furthermore, the set-up and post-processing are time-consuming and thus do not allow a prompt assessment of the correct execution of the movements during the aquatic session therapy. The aim of the present study was to estimate the 3D joint kinematics of the lower limbs and thorax-pelvis joints in sagittal and frontal planes during underwater walking using wearable inertial and magnetic sensors. Eleven healthy adults were measured during walking both in shallow water and in dry-land conditions. Eight wearable inertial and magnetic sensors were inserted in waterproofed boxes and fixed to the body segments by means of elastic modular bands. A validated protocol (Outwalk) was used. Gait cycles were automatically segmented and selected if relevant intraclass correlation coefficients values were higher than 0.75. A total of 704 gait cycles for the lower limb joints were normalized in time and averaged to obtain the mean cycle of each joint, among participants. The mean speed in water was 40% lower than that of the dry-land condition. Longer stride duration and shorter stride distance were found in the underwater walking. In the sagittal plane, the knee was more flexed (≈ 23°) and the ankle more dorsiflexed (≈ 9°) at heel strike, and the hip was more flexed at toe-off (≈ 13°) in water than on land. On the frontal plane in the underwater walking, smoother joint angle patterns were observed for thorax-pelvis and hip, and ankle was more inversed at toe-off (≈ 7°) and showed a more inversed mean value (≈ 7°). The results were mainly explained by the effect of the speed in the water as supported by the linear mixed models analysis performed. Thus, it seemed that the combination of speed and environment triggered modifications in the joint angles in underwater gait more than these two factors considered separately. The inertial and magnetic sensors, by means of fast set-up and data analysis, can supply an immediate gait analysis report to the therapist during the aquatic therapy session.

One of the most promising applications of satellite data is providing users in charge of land and emergency management with information and data to support decision making for geohazard mapping, monitoring and early warning. In this work, we consider ground displacement data obtained via interferometric processing of satellite radar imagery, and we provide a novel post-processing approach based on a Functional Data Analysis paradigm capable of detecting precursors in displacement time series. The proposed approach appropriately accounts for the spatial and temporal dependencies of the data and does not require prior assumptions on the deformation trend. As an illustrative case, we apply the developed method to the identification of precursors to a mud volcano eruption in the Santa Barbara village in Sicily, southern Italy, showing the advantages of using a Functional Data Analysis framework for anticipating the warning signal. Indeed, the proposed approach is able to detect precursors of the paroxysmal event in the time series of the locations close to the eruption vent and provides a warning signal months before a scalar approach would. The method presented can potentially be applied to a wide range of geological events, thus representing a valuable and far-reaching monitoring tool.