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ABSTRACT Unmanned aerial vehicles (UAVs) have gained popularity in geological deformation monitoring due to their flexibility, cost‐effectiveness, and ease of image acquisition. However, accurate co‐registration of multi‐phase UAV images, essential for effective monitoring, requires numerous ground control points (GCPs), challenging in deformation‐prone areas. This study introduces a UAV‐based monitoring method that eliminates the need for GCPs. Initially, two‐phase images are integrated for joint aerial triangulation. The first‐phase image and tie points undergo bundle adjustment refinement. Control points are identified as tie points with minimal deviation and used to refine the second‐phase image. Three‐dimensional (3D) models are generated from these refined adjustments and differential analysis between the models reveals geological deformation. Experimental results show that this method automatically identifies stable areas and effectively captures both the location and extent of geological deformation, achieving a relative change accuracy of 0.06 m, which is twice the average ground resolution. Compared to traditional aerial triangulation methods without control points, this approach offers more than a tenfold increase in accuracy. The accuracy is on par with methods that utilize multiple control points, indicating the promising potential of this approach for geological deformation monitoring. [ABSTRACT FROM AUTHOR]

This research investigates precision enhancement in regional quasi-geoid refinement through ADS80 tri-linear array scanning stereoscopic imagery for aerial triangulation coupled with GNSS gravity-potential modeling. By acquiring stereoscopic imagery and analyzing triangulation accuracy using an ADS80 camera, we performed this study over the Qinghai–Tibet Plateau's elevated, desolate terrain, collecting 593 GNSS points following high-precision stereoscopic imagery modeling. By utilizing 12 gravity satellite models, we computed geoid heights and China's 1985 Yellow Sea elevations for 28 benchmarks and GNSS points, thereby refining the Qinghai Province Quasi-Geoid Model (QPQM) using geometric techniques. The findings reveal that POS-assisted ADS80 stereoscopic imagery yields high-precision triangulation with maximal horizontal and elevation accuracies of 0.083/0.116 cm and 0.053/0.09 cm, respectively, across five control point arrangements. The RMSE of normal heights for 1985, processed via these GNSS points, achieved decimeter precision. By applying error corrections from benchmarks to the 1985 elevation data from gravity satellites and performing weighted averaging, the precision of EGM2008, SGG-UGM-2, and SGG-UGM-1 models improved to 8.61 cm, 9.09 cm, and 9.38 cm, respectively, surpassing the QPQM by 9.22 cm to 9.99 cm. This research demonstrates that the proposed methods can significantly enhance the precision of regional quasi-geoid surfaces. Additionally, these methods offer a novel approach for rapidly establishing regional quasi-geoid models in the uninhabited areas of the Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

Drones are used by surveyors as an alternative to traditional methods of obtaining orthophoto maps and large-scale topographical maps, but several factors affect the accuracy of its data, one of them is software used in image processing. Because there are many types of software, choosing one of them is a real problem in survey projects using drones. Processing software is divided into commercial and open source software. Commercial software is a black box situation, which highlights the challenge of isolating accurate sources of errors and judging the accuracy of processing products.In this research, the capabilities of the commercial software Pix4Dmapper, Agisoft Metashape, and 3DF Zephyr Aerial were compared in calculating the aerial triangulation of the image blocks taken by drones, with a comparison of the capabilities of these softwares in getting the most important spatial products for surveyors from these images (Digital Elevation Model and Orthophoto). The results showed that Pix4Dmapper was able to perform aerial triangulation more accurate than Agisoft Metashape and 3DF Zephyr Aerial, with great convergence between the results of Agisoft Metashape and 3DF Zephyr A. The results also showed that 3DF Zephyr Aerial had extracted the densest point cloud. Another finding is that Pix4Dmapper produced the most accurate orthophoto and took the shortest processing time, and that the Agisoft Metashape interface is more flexible and user-friendly than the rest of the tested software.

In the last decade, many aerial photographic archives have started to be digitized for multiple purposes, including digital preservation and geoprocessing. This paper analyzes the effects of professional photogrammetric versus consumer-grade scanners on the processing of analog historical aerial photographs. An image block over Warsaw is considered, featuring 38 photographs acquired in 1986 (Wild RC10, Normal Aviogon II lens, 23 × 23 cm format) with a ground sampling distance (GSD) of 4 cm. Aerial triangulation (AT) and dense image matching (DIM) procedures are considered, analyzing how scanning modalities are important in the massive digitization of analog images for georeferencing and 3D product generation. The achieved results show how consumer-grade scanners, unlike more expensive photogrammetric scanners, do not possess adequate recording quality to ensure high accuracy and geometric precision for geoprocessing purposes. However, consumer-grade scanners can be used for time and cost-efficient applications where a partial loss of data quality is not critical. [ABSTRACT FROM AUTHOR]

Drones are used by surveyors as an alternative to traditional methods of obtaining orthophoto maps and large-scale topographical maps, but several factors affect the accuracy of its data, one of them is software used in image processing. Because there are many types of software, choosing one of them is a real problem in survey projects using drones. Processing software is divided into commercial and open-source software. Commercial software is a black box situation, which highlights the challenge of isolating accurate sources of errors and judging the accuracy of processing products. In this research, the capabilities of the commercial software Pix4Dmapper, Agisoft Metashape, and 3DF Zephyr Aerial were compared in calculating the aerial triangulation of the image blocks taken by drones, with a comparison of the capabilities of this software in getting the most important spatial products for surveyors from these images (Digital Elevation Model and Orthophoto). The results showed that Pix4Dmapper was able to perform aerial triangulation more accurately than Agisoft Metashape and 3DF Zephyr Aerial, with great convergence between the results of Agisoft Metashape and 3DF Zephyr A. The results also showed that 3DF Zephyr Aerial had extracted the densest point cloud. Another finding is that Pix4Dmapper produced the most accurate orthophoto and took the shortest processing time, and that the Agisoft Metashape interface is more flexible and user-friendly than the rest of the tested software. [ABSTRACT FROM AUTHOR]

In scenarios such as road detection and emergency mapping, single strip photogrammetry without ground control points (GCPs) can effectively improve data acquisition efficiency. Positioning and orientation system (POS) assisted single strip aerial triangulation utilizes relative orientation to construct a strip model. However, due to factors such as cumulative errors, the strip model can experience distortion. The distortion affects the accuracy of aerial triangulation solutions and can even render the results unavailable. In addition, the attitude data from POS may not be precise enough, especially the yaw angle. To address this issue, this article proposes a POS assisted aerial triangulation method for single flight strip without GCPs. This method establishes an error correction model. By utilizing the exterior orientation elements observed by the POS system, this method corrects the less accurate position and attitude parameters obtained after relative orientation. This correction process results in obtaining high precision exterior orientation elements for the images. Moreover, the error correction model maintains a constant number of parameters, regardless of the quantity of images, with only 18 parameters, thus ensuring efficient model solving. Ultimately, through experimental validation, it has been demonstrated that the method proposed in this article has improved the overall accuracy by approximately 13.22% and 17.72% compared to traditional POS assisted bundle adjustment methods under different flight strips and varying attitude angle errors, separately.

This research investigates precision enhancement in regional quasi-geoid refinement through ADS80 tri-linear array scanning stereoscopic imagery for aerial triangulation coupled with GNSS gravity-potential modeling. By acquiring stereoscopic imagery and analyzing triangulation accuracy using an ADS80 camera, we performed this study over the Qinghai–Tibet Plateau’s elevated, desolate terrain, collecting 593 GNSS points following high-precision stereoscopic imagery modeling. By utilizing 12 gravity satellite models, we computed geoid heights and China’s 1985 Yellow Sea elevations for 28 benchmarks and GNSS points, thereby refining the Qinghai Province Quasi-Geoid Model (QPQM) using geometric techniques. The findings reveal that POS-assisted ADS80 stereoscopic imagery yields high-precision triangulation with maximal horizontal and elevation accuracies of 0.083/0.116 cm and 0.053/0.09 cm, respectively, across five control point arrangements. The RMSE of normal heights for 1985, processed via these GNSS points, achieved decimeter precision. By applying error corrections from benchmarks to the 1985 elevation data from gravity satellites and performing weighted averaging, the precision of EGM2008, SGG-UGM-2, and SGG-UGM-1 models improved to 8.61 cm, 9.09 cm, and 9.38 cm, respectively, surpassing the QPQM by 9.22 cm to 9.99 cm. This research demonstrates that the proposed methods can significantly enhance the precision of regional quasi-geoid surfaces. Additionally, these methods offer a novel approach for rapidly establishing regional quasi-geoid models in the uninhabited areas of the Qinghai–Tibet Plateau.

In the last decade, many aerial photographic archives have started to be digitized for multiple purposes, including digital preservation and geoprocessing. This paper analyzes the effects of professional photogrammetric versus consumer-grade scanners on the processing of analog historical aerial photographs. An image block over Warsaw is considered, featuring 38 photographs acquired in 1986 (Wild RC10, Normal Aviogon II lens, 23 × 23 cm format) with a ground sampling distance (GSD) of 4 cm. Aerial triangulation (AT) and dense image matching (DIM) procedures are considered, analyzing how scanning modalities are important in the massive digitization of analog images for georeferencing and 3D product generation. The achieved results show how consumer-grade scanners, unlike more expensive photogrammetric scanners, do not possess adequate recording quality to ensure high accuracy and geometric precision for geoprocessing purposes. However, consumer-grade scanners can be used for time and cost-efficient applications where a partial loss of data quality is not critical.

Thermal infrared images can show the temperature change of objects that represent the significant characteristics, therefore they have been applied on many fields. With the development of UAS (Unmanned Aircraft Systems), the thermal infrared camera can be carried on the Helicopter UAS to collect thermal images with high resolution in a local area more efficiently. However, the ground control marks for thermal images are uneasy to be set up. In this study, the Trimble BD970 GNSS OEM board was carried on the Helicopter UAS to collect Global Positioning System (GPS) data and the bundle adjustment fbr the positioning and orientation of collected thermal images, i.e., AT (Aerial Triangulation), was supported by Virtual Base Station--Real Time Kinematic (VBS-RTK) GPS technique. In theory, the GPS antenna offset is not changed and can be viewed as constant. Therefore, in this study, the new model based on bundle adjustment was developed to solve GPS antenna offset, exterior orientation parameters and the object coordinate of tie points simultaneously by unified least squares adjustment. Besides, thermal infrared camera is a non-metric camera. In order to acquire high precision camera parameters for AT, thermal infrared camera was calibrated by field method. In this study, due to the bad accuracy of GPS observations in real data collection, the GPS antenna offset could be not solved. Although the accuracy of GPS observations was bad, the GPS observations could also be used to support the bundle adjustment for the positioning and orientation of thermal images under better block geometry and ground control points still could be reduced. [ABSTRACT FROM AUTHOR]

Objectives: Incremental structure from motion（SfM） has become the widely used workflow for aerial triangulation（AT） of unmanned aerial vehicle （UAV） images. Recently, extensive research has been conducted to improve the efficiency, precision and scalability of SfM-based AT for UAV images. Meanwhile, deep learning-based methods have also been exploited for the geometry processing in the fields of photogrammetry and computer vision, which have been verified with large potential in the AT of UAV images. This paper aims to give a review of recent work in the SfM-based AT for UAV images. Methods:Firstly, the workflow of SfM-based AT is briefly presented in terms of feature matching and geometry solving,in which the former aims to obtain enough and accurate correspondences, and the latter attempts to solve unknown parameters. Secondly, literature review is given for feature matching and geometry solving. For feature matching, classical hand-crafted and recent learning-based methods are presented from the aspects of feature extraction, feature matching and outlier removal. For geometry solving, the principle of SfM-based AT is firstly given with some well-known and widely-used open-source SfM software. Efficiency improvement and large-scale processing are then summarized, which focus on improving the capability of SfM to process large-scale UAV images. Finally, further search is concluded from four aspects, including the change of data acquisition modes, the scalability for large-scale scenes, the development of communication and hardware, and the fusion of deep learning-based methods. Results: The review demonstrates that the existing research promotes the development of SfM-based AT towards the direction of high efficiency, high precision and high robustness, and also promotes the development of both commercial and open-source software packages. Conclusions: Considering the characteristics of UAV images, the efficiency, precision and robustness of SfMbased AT and its application need further improvement and exploitation. This paper could give an extensive conclusion and be a useful reference to the related researchers [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution. [ABSTRACT FROM AUTHOR]

The sweeping camera systems in the surveying and mapping industry are usually efficient in image acquisition, for the photography coverage of a single strip is relatively large. The triangulation angle of correspondence is overly tiny to adopt traditional block adjustment (BA). This study analysed the imaging principle of the Chinese APS7K comprehensive camera system and proposed an aerial triangulation method for the data this system acquired. The proposed method first determines the adjacent matrix from the POS data and trajectory information. The other part of the method is to overcome the weak relative geometry in a single strip by introducing the digital elevation model (DEM) data into the block adjustment scheme. The optimal solution of adjustment is obtained by iteratively solving the problem. We verified the optimisation's effectiveness by checking stitched orthophoto and check points from Google Earth. The results show that mosaic discrepancy is eliminated, the reprojection error is reduced to subpixel level, and positioning accuracy is better than 0.4 meter (ground sample distance is 0.2 meter) after adjustment with ground control points. Finally, the method's shortcomings and prospects are summarized. [ABSTRACT FROM AUTHOR]

Geospatial information acquired with Unmanned Aerial Vehicles (UAV) provides valuable decision-making support in many different domains, and technological advances coincide with a demand for ever more sophisticated data products. One consequence is a research and development focus on more accurately referenced images and derivatives, which has long been a weakness especially of low to medium cost UAV systems equipped with relatively inexpensive inertial measurement unit (IMU) and Global Navigation Satellite System (GNSS) receivers. This research evaluates the positional accuracy of the real-time kinematics (RTK) GNSS on the DJI Matrice 600 Pro, one of the first available and widely used UAVs with potentially surveying-grade performance. Although a very high positional accuracy of the drone itself of 2 to 3 cm is claimed by DJI, the actual accuracy of the drone RTK for positioning the images and for using it for mapping purposes without additional ground control is not known. To begin with, the actual GNSS RTK position of reference center (the physical point on the antenna) on the drone is not indicated, and uncertainty regarding this also exists among the professional user community. In this study the reference center was determined through a set of experiments using the dual frequency static Leica GNSS with RTK capability. The RTK positioning data from the drone were then used for direct georeferencing, and its results were evaluated. Test flights were carried out over a 70 x 70 m area with an altitude of 40 m above the ground, with a ground sampling distance of 1.3 cm. Evaluated against ground control points, the planimetric accuracy of direct georeferencing for the photogrammetric product ranged between 30 and 60 cm. Analysis of direct georeferencing results showed a time delay of up to 0.28 seconds between the drone GNSS RTK and camera image acquisition affecting direct georeferencing results.

Every type of remote sensing sensor has its own advantages and limitations. Integration of data from various remote sensing devices is increasingly becoming common to produce a better mapping product. For example, Light Detection and Ranging (LiDAR) data has better vertical accuracy compared to horizontal accuracy, whereas 3D data produced using aerial images has better horizontal accuracy compared to vertical accuracy. LiDAR and aerial images have several complementary properties. Therefore, integration of these two datasets could result in a better topographic product. In this article, the LiDAR data are used as vertical control to perform aerial triangulation using aerial images. The vertical measurement of LiDAR data and image plane coordinates of the corresponding point from aerial images were considered as known parameters. This method was implemented using synthetic data consisting of 54 ground points and three aerial images. Eight different scenarios were experimented that showed increased horizontal and vertical accuracy when compared to LiDAR or aerial images alone. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since the digital orthoimage and orthomosaic maps have come to be used more and more as the fundamental basis for many studies, the demand for such products has been gradually increasing in the recent years. Owing to the fact that they can be produced more rapidly and cheaper than the traditional topographic maps, the orthoimage maps are currently much in demand. The production accuracy of the orthoimage maps, obtained through aerial photographs or satellite images, has been an important research topic. The number and distribution of the ground control points have a significant bearing on the accuracy of aerial triangulation. Therefore, the accuracy of the orthoimage maps, being the end products, is related to the number and distribution of the ground control points within the block. This study has aimed to study the influence of the number and distribution of ground control points and check points on the accuracy of aerial triangulation by using different GNSS/IMU systems. Five different configurations have been designed depending on the distribution of the ground control and check points within rectangular shaped blocks in different combinations and numbers. Such configurations were then tested in different types of terrain such as forest lands, residential and agricultural areas. The objective of the study was to identify the most ideal geodesic structure and the most accurate photogrammetric triangulation adjustment suitable for various different systems based on such terrain classification. The results were evaluated based on the ASPRS accuracy standards.

In this article, a structure from motion (SfM) framework for oblique aerial images of man-made environments is proposed, covering the issues of determining overlapping images, feature extraction, image matching, rejection of erroneous correspondences, feature tracking, automatic transfer of ground control points (GCPs), and bundle block adjustment. One of the challenges that it is intended to solve is the reduction of the required manual work concerning the measurement of GCPs, in order to increase the degree of automation of the exterior orientation estimation process, through the usage of geometric constraints automatically imposed. Yet another challenge is the difficulty in matching correctly feature points among multiple oblique views that depict scenes with repetitive patterns and homogeneous textures. The proposed algorithm solves this by eliminating all erroneous tie points through the combination of multiple checks and geometric constraints imposed during the image matching procedure and a robust iterative bundle adjustment framework. The proposed SfM methodology is applied in different configurations of oblique images under non-ideal aerial triangulation scenarios characterized by lack of well-distributed GCPs as well as minimum manual image measurements. The results are analysed, focusing on the improvement of the accuracy of the exterior orientation parameters thanks to the proposed robust outlier removal technique as well as on the impact of the proposed scale-based weighting strategy for bundle adjustment of oblique images on the exterior orientation results. The proposed SfM framework proves to be a good alternative solution to existing commercial SfM methods. [ABSTRACT FROM AUTHOR]

Geospatial information acquired with Unmanned Aerial Vehicles (UAV) provides valuable decision-making support in many different domains, and technological advances coincide with a demand for ever more sophisticated data products. One consequence is a research and development focus on more accurately referenced images and derivatives, which has long been a weakness especially of low to medium cost UAV systems equipped with relatively inexpensive inertial measurement unit (IMU) and Global Navigation Satellite System (GNSS) receivers. This research evaluates the positional accuracy of the real-time kinematics (RTK) GNSS on the DJI Matrice 600 Pro, one of the first available and widely used UAVs with potentially surveying-grade performance. Although a very high positional accuracy of the drone itself of 2 to 3 cm is claimed by DJI, the actual accuracy of the drone RTK for positioning the images and for using it for mapping purposes without additional ground control is not known. To begin with, the actual GNSS RTK position of reference center (the physical point on the antenna) on the drone is not indicated, and uncertainty regarding this also exists among the professional user community. In this study the reference center was determined through a set of experiments using the dual frequency static Leica GNSS with RTK capability. The RTK positioning data from the drone were then used for direct georeferencing, and its results were evaluated. Test flights were carried out over a 70 x 70 m area with an altitude of 40 m above the ground, with a ground sampling distance of 1.3 cm. Evaluated against ground control points, the planimetric accuracy of direct georeferencing for the photogrammetric product ranged between 30 and 60 cm. Analysis of direct georeferencing results showed a time delay of up to 0.28 seconds between the drone GNSS RTK and camera image acquisition affecting direct georeferencing results. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are still an interesting and current research topic in photogrammetry. An important issue in this area is determining the elements of exterior orientation of image data acquired at low altitudes. The article presents selected mathematical methods (TGC, TIC, TAD) of estimating elements of exterior orientation for image data obtained at low altitudes. The measurement data for the experimental test were recorded by the Unmanned Aerial Vehicle platform Trimble UX-5. In the framework of the test photogrammetric flight, the authors obtained 506 images and navigation data specifying the position and orientation of the Unmanned Aerial Vehicle. As a result of the research, it is proven possible to show the usefulness of the mathematical models (TGC, TIC, TAD) in estimation of elements of exterior orientation. [ABSTRACT FROM AUTHOR]

Camera self-calibration determines the precision and robustness of AT (aerial triangulation) for UAV (unmanned aerial vehicle) images. The UAV images collected from long transmission line corridors are critical configurations, which may lead to the “bowl effect” with camera self-calibration. To solve such problems, traditional methods rely on more than three GCPs (ground control points), while this study designs a new self-calibration method with only one GCP. First, existing camera distortion models are grouped into two categories, i.e., physical and mathematical models, and their mathematical formulas are exploited in detail. Second, within an incremental SfM (Structure from Motion) framework, a camera self-calibration method is designed, which combines the strategies for initializing camera distortion parameters and fusing high-precision GNSS (Global Navigation Satellite System) observations. The former is achieved by using an iterative optimization algorithm that progressively optimizes camera parameters; the latter is implemented through inequality constrained BA (bundle adjustment). Finally, by using four UAV datasets collected from two sites with two data acquisition modes, the proposed algorithm is comprehensively analyzed and verified, and the experimental results demonstrate that the proposed method can dramatically alleviate the “bowl effect” of self-calibration for weakly structured long corridor UAV images, and the horizontal and vertical accuracy can reach 0.04 m and 0.05 m, respectively, when using one GCP. In addition, compared with open-source and commercial software, the proposed method achieves competitive or better performance.

Observing coastal water depths is very important to understand physical processes of the coastal environment and manage coastal resources. In this study, a low-altitude remote sensing system, Helikite, with an optic sensor was used to measure shallow water depths. This system not only enables us to observe the highresolution water depths in the coastal waters in a very short time, but also allow us to estimate water depths of the breaking wave zone where erosion is most active. The "Anmok Beach" study area has undergone severe coastal erosion from typhoons in summer and abnormally high waves in winter. Therefore, aerial photographs were taken and a field water depth survey was carried out at Anmok Beach to estimate water depths. In order to convert aerial orthomosaic images to water depths, the following three steps were undertaken. First, georeferencing was performed via the Oceanic Ground Control Point based on a ground reference point available on the sea surface. Second, error values generated from the aeolian current and sunglint were filtered out from the orthomosaic images. Third, the relationships between in-situ water depth data and brightness values of the orthomosaic image were calculated using the second polynomial regression equation. The obtained regression coefficients (R2) values were 0.90, 0.95, and 0.91 for the R, G, and B-bands, respectively and the corresponding RMSE values were 0.45 m, 0.30 m, and 0.44 m for the R, G, and B-bands, respectively. The accuracy of the G-band based water depth was highest. Using this result, we could estimate the submarine topography of the crescent bar produced by complex coastal currents in the study area. [ABSTRACT FROM AUTHOR]

This paper shows the influence of the selection of photogrammetric control points as natural, identifiable points instead of signalized, premarked control points on the results of aerial triangulation of high-resolution aerial images with GSD below 10 cm. In the experiment, different selections of controls were tested using point-type and linear-type points with measurement of their centre or corner. In the experiment, 2 blocks with GSD of 5 and 10 cm were selected using the same measurements in 4 tested approaches with sets of natural identifiable points used by comparing the result with the reference variant. The experiment proves the possibility of using natural controls instead of premarked controls for images of urban areas. This can significantly reduce the cost of photogrammetric missions in urban areas where it is easy to find uniquely identifiable control points that can be used for image orientation. [ABSTRACT FROM AUTHOR]

Abstract Vacuum phototriodes have been used for a number of years in particle physics experiments. For example, they were used in the OPAL experiment at LEP and are currently used in the endcap calorimeter of the CMS experiment at CERN's Large Hadron Collider. A simulation of a CMS vacuum phototriode (RIE type FEU-188) has been implemented using the COMSOL multi-physics software environment. In addition, a new vacuum phototriode configured with a segmented anode, to provide four independent channels within the same overall device envelope, is presented. The induced signal as a function of time, and the effects of cross-talk in adjacent quadrants have been studied. Highlights • COMSOL simulations demonstrate particle trajectories in strong magnetic fields. • The induced currents using Shockley–Ramo theorem are calculated on the anode. • Simulation of a new prototype vacuum phototriode with a segmented anode is presented. • The signal and cross talk is investigated via controlled illumination within COMSOL. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

VLS (Vehicle-borne Laser Scanning) can easily scan the road surface in the close range with high density. UAV (Unmanned Aerial Vehicle) can capture a wider range of ground images. Due to the complementary features of platforms of VLS and UAV, combining the two methods becomes a more effective method of data acquisition. In this paper, a non-rigid method for the aerotriangulation of UAV images assisted by a vehicle-borne light detection and ranging (LiDAR) point cloud is proposed, which greatly reduces the number of control points and improves the automation. We convert the LiDAR point cloud-assisted aerotriangulation into a registration problem between two point clouds, which does not require complicated feature extraction and match between point cloud and images. Compared with the iterative closest point (ICP) algorithm, this method can address the non-rigid image distortion with a more rigorous adjustment model and a higher accuracy of aerotriangulation. The experimental results show that the constraint of the LiDAR point cloud ensures the high accuracy of the aerotriangulation, even in the absence of control points. The root-mean-square error (RMSE) of the checkpoints on the x, y, and z axes are 0.118 m, 0.163 m, and 0.084m, respectively, which verifies the reliability of the proposed method. As a necessary condition for joint mapping, the research based on VLS and UAV images in uncontrolled circumstances will greatly improve the efficiency of joint mapping and reduce its cost.

This article aims to study the importance ofin situcamera calibration for the integration of light detection and ranging (LIDAR) and photogrammetric data sets by indirect georeferencing. For this purpose, thein situcamera calibration was performed to estimate the interior orientation parameters (IOP) in the flight condition, using a sub-block of images (six images from two opposite flight strips), extracted from the entire block and a set of LIDAR control points (LCPs) computed by three planes intersection, extracted from the LIDAR point cloud on the building roofs. In order to evaluate the accuracies of the LIDAR and photogrammetric integration, two experiments were performed: the first used IOP from terrestrial calibration, and the second employed the IOP from thein situcalibration. The analysis of the obtained results from the performed experiments showed that the horizontal and vertical accuracies, computed by checkpoints discrepancies, are improved significantly when the IOP fromin situcalibration are used. For this condition, the values of horizontal and vertical RMSEs of discrepancies are close to 0.40 and to 0.50 m, respectively. [ABSTRACT FROM AUTHOR]

We extend the application of real-time kinematic PPP to aerial triangulation using GPS to determine coordinates of the antenna installed on the airplane, using real-time satellite products from IGS and the CNES Analysis Center. In order to verify the performance of real-time kinematic PPP for aerial triangulation, three tests with varying aerial and ground conditions are assessed. Numerical results show that real-time kinematic PPP using IGS real-time products of 5-cm orbit accuracy and 0.1- to 0.3-ns clock precision can provide comparable accuracy for aerial photogrammetric mapping at the scale of 1:1000 as does post-mission kinematic PPP using IGS final products. Millimeter-to-centimeter-level differences and centimeter-to-2-decimeter differences are identified for horizontal and vertical coordinates of ground check points, respectively, in the three tests. The comparison between real-time IGS and CNES products for GPS positioning and aerial triangulation unveils that real-time products with a better clock precision can result in better performance of GPS real-time kinematic PPP as applied to aerial triangulation. [ABSTRACT FROM AUTHOR]

Towards tackling the evident practical challenges of fault detection and diagnosis for PV modules, especially in large-scale installations, this paper proposes two different techniques for advanced inspection mapping of PV plants; aerial triangulation and terrestrial georeferencing . The former uses data of aerial thermal/visual imagery of operating PV modules, obtained by an unmanned aerial vehicle (UAV), to generate static “inspection maps”, in the form of true orthophoto mosaics. On the other hand, georeferencing is used to associate terrestrial thermal/visual imagery, obtained at distinct positions in a PV plant, with geographic data. By such way, inspection is based on a dynamic virtual map of the installation. Both mapping techniques were tested in two grid-connected PV systems, of a total installed power of 70.2 KW p . Several defective modules were easily and accurately detected, typically as abnormal temperature profiles, in the infrared (IR) spectrum. In addition, specific thermal image patterns of operating modules, were validated and quantified by additional diagnostic measurements, and were assigned to possible fault types. On the basis of the experience feedback, the potential of the proposed techniques and their limitations, for further application to PV plants of larger scale, are also discussed. [ABSTRACT FROM AUTHOR]

UAV Photogrammetry today already enjoys a largely automated and efficient data processing pipeline. However, the goal of dispensing with Ground Control Points looks closer, as dual-frequency GNSS receivers are put on board. This paper reports on the accuracy in object space obtained by GNSS-supported orientation of four photogrammetric blocks, acquired by a senseFly eBee RTK and all flown according to the same flight plan at 80 m above ground over a test field. Differential corrections were sent to the eBee from a nearby ground station. Block orientation has been performed with three software packages: PhotoScan, Pix4D and MicMac. The influence on the checkpoint errors of the precision given to the projection centers has been studied: in most cases, values in Z are critical. Without GCP, the RTK solution consistently achieves a RMSE of about 2-3 cm on the horizontal coordinates of checkpoints. In elevation, the RMSE varies from flight to flight, from 2 to 10 cm. Using at least one GCP, with all packages and all test flights, the geocoding accuracy of GNSS-supported orientation is almost as good as that of a traditional GCP orientation in XY and only slightly worse in Z. [ABSTRACT FROM AUTHOR]

Bundle adjustment (BA) using parallax angle feature parameterization (ParallaxBA), has been recently reported to have better convergence and more accurate structure estimation in. However, ParallaxBA is a merely free-net BA model and is incapable of geolocating tie points in the global (geodetic) coordinate system. This study presents a novel BA method that incorporates Ground Control Points (GCPs) into ParallaxBA based on hybrid feature parameterization (ParallaxBA-GCP). Different from other BA methods based on feature parameterization using Euclidean xyz coordinates, the tie points in ParallaxBA are parameterized with three types of angles: azimuth, elevation and parallax angles. Therefore, the observation function of the tie points and that of GCPs were described with hybrid feature parameterization in the form of angles and xyz parameterization, respectively. The result of one real data set demonstrates that, when a poor initialization is given, ParallaxBA-GCP can converge within a very few iterations and rapidly triangulate high-quality tie points that satisfies the accuracy requirement of the aerial triangulation. [ABSTRACT FROM PUBLISHER]

Real-time image georeferencing is essential to the prompt generation of spatial information such as orthoimages from the image sequence acquired by an airborne multi-sensor system. It is mostly based on direct georeferencing using a GPS/INS system, but its accuracy is limited by the quality of the GPS/INS data. More accurate results can be acquired using traditional aerial triangulation (AT) combined with GPS/INS data, which can be performed only as a post-processing method due to intense computational requirements. In this study, we propose a sequential AT algorithm that can produce accurate results comparable to those from the simultaneous AT algorithm in real time. Whenever a new image is added, the proposed algorithm rapidly performs AT with minimal computation at the current stage using the computational results from the previous stage. The experimental results show that the georeferencing of an image sequence at any stage took less than 0.1 s and its accuracy was determined within ± 5 cm on the estimated ground points, which is comparable to the results of simultaneous AT. This algorithm may be used for applications requiring real-time image georeferencing such as disaster monitoring and image-based navigation.

In this paper, we use multimode GNSS instead of single GPS constellation to resolve the three exterior line elements of each image. The principles of differential GNSS positioning and GNSS-supported aerial triangulation (AT) are presented and an implementation case is demonstrated. With multi-constellation system, the number of visible satellites is significantly increased and the geometry distribution of the satellites is well improved. The positioning accuracy and robustness are therefore getting better compared to GPS positioning. Experimental results show that differential GNSS has remarkable increment on the integer rate of ambiguity solution when GPS has few number and low elevation angle of satellites. The combined AT adjustment of GNSS resolution and 10 ground control points (GCPs) achieve the horizontal accuracy of ±18 cm and vertical accuracy of ±23 cm for the check points, which are comparable with traditional bundle adjustment with dense GCPs and better than GPS-supported AT. The achieved accuracy also satisfies the requirement for 1:500 topographic maps with the bonus of 84% GCPs eliminated. In conclusion, GNSS-supported AT is of feasibility and superiority for large scale Unmanned Aerial Vehicle-based photogrammetry. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Roadway pavement surface distress information is critical for effective pavement asset management, and subsequently, transportation management agencies at all levels (i.e., federal, state, and local) dedicate a large amount of time and money to routinely evaluate pavement surface distress conditions as the core of their asset management programs. However, currently adopted ground-based evaluation methods for pavement surface conditions have many disadvantages, like being time-consuming and expensive. Aircraft-based evaluation methods, although getting more attention, have not been used for any operational evaluation programs yet because the acquired images lack the spatial resolution to resolve finer scale pavement surface distresses. Hyper-spatial resolution natural color aerial photography (HSR-AP) provides a potential method for collecting pavement surface distress information that can supplement or substitute for currently adopted evaluation methods. Using roadway pavement sections located in the State of New Mexico as an example, this research explored the utility of aerial triangulation (AT) technique and HSR-AP acquired from a low-altitude and low-cost small-unmanned aircraft system (S-UAS), in this case a tethered helium weather balloon, to permit characterization of detailed pavement surface distress conditions. The Wilcoxon Signed Rank test, Mann-Whitney U test, and visual comparison were used to compare detailed pavement surface distress rates measured from HSR-AP derived products (orthophotos and digital surface models generated from AT) with reference distress rates manually collected on the ground using standard protocols. The results reveal that S-UAS based hyper-spatial resolution imaging and AT techniques can provide detailed and reliable primary observations suitable for characterizing detailed pavement surface distress conditions comparable to the ground-based manual measurement, which lays the foundation for the future application of HSR-AP for automated detection and assessment of detailed pavement surface distress conditions. [ABSTRACT FROM AUTHOR]