Search

Optical remote sensing using unmanned aerial vehicles (UAVs) is proposed to monitor changes in marine environments effectively. Optical measurements were performed using a UAV multispectral camera (RedEdge, five spectral wavelengths of 475, 560, 668, 717, and 842 nm) with high spatial (5 cm) and temporal (1 s) resolutions to monitor the rapidly changing suspended sediment concentration (SSC) in the Saemangeum coastal area on the western coast of Korea. To develop the SSC algorithm, optical field, and water sample measurements were obtained from outside (11 stations) and inside (three stations) regions separated by a seawall, accounting for 100 measurements from 2018 to 2020. Accordingly, the remote sensing reflectance (Rrs) was estimated at each sampling station and used to develop the SSC algorithm based on multiple linear regression. The algorithm reasonably estimated the SSC with an R2 and root mean square error of 0.83 and 4.27 (mg L−1), respectively. Continuous individual UAV measurements over the coastal area of Saemangeum were combined to generate a wider SSC map. For the UAV observational data, the atmospheric influence at each altitude was reduced to the surface altitude level using a relative atmospheric correction technique. The SSC map enabled front monitoring of SSC fluctuations caused by discharge water due to the sluice gate opening. These results demonstrated the usability of the UAV-based SSC algorithm and confirmed the possibility of monitoring rapid SSC fluctuations. [ABSTRACT FROM AUTHOR]

The spatial accuracy of unmanned aerial vehicles (UAVs) and the images they capture play a crucial role in the mapping process. Researchers are exploring solutions that use image-based techniques such as structure from motion (SfM) to produce topographic maps using UAVs while accessing locations with extremely high accuracy and minimal surface measurements. Advancements in technology have enabled real-time kinematic (RTK) to increase positional accuracy to 1–3 times the ground sampling distance (GSD). This paper focuses on post-processing kinematic (PPK) of positional accuracy to achieve a GSD or better. To achieve this, precise satellite orbits, clock information, and UAV global navigation satellite system observation files are utilized to calculate the camera positions with the highest positional accuracy. RTK/PPK analysis is conducted to improve the positional accuracies obtained from different flight patterns and altitudes. Data are collected at altitudes of 80 and 120 meters, resulting in GSD values of 1.87 cm/px and 3.12 cm/px, respectively. The evaluation of ground checkpoints using the proposed PPK methodology with one ground control point demonstrated root mean square error values of 2.3 cm (horizontal, nadiral) and 2.4 cm (vertical, nadiral) at an altitude of 80 m, and 1.4 cm (horizontal, oblique) and 3.2 cm (vertical, terrain-following) at an altitude of 120 m. These results suggest that the proposed methodology can achieve high positional accuracy for UAV image georeferencing. The main contribution of this paper is to evaluate the PPK approach to achieve high positional accuracy with unmanned aerial vehicles and assess the effect of different flight patterns and altitudes on the accuracy of the resulting topographic maps. [ABSTRACT FROM AUTHOR]

At active volcanoes, the surface temperature and its spatial distribution can indicate changes in the underlying magmatic and hydrothermal system. Surface temperature monitoring has been widely performed using thermal remote sensing with thermal infrared (TIR) cameras. One of the drawbacks of this method is that the unknown viewing orientation of TIR images inhibits quantitative evaluations of the spatial extent and distributions of thermal anomalies. Therefore, many studies have performed 3D temperature-field reconstructions by processing TIR images photogrammetrically. However, these studies have not included the correction of TIR wave atmospheric attenuation and viewing-angle variation in emissivity in the reconstruction procedure, which can result in significant temperature misestimation. We propose a simple method that incorporates the correction into the reconstruction process, which can improve the estimation of surface temperature, especially in rugged terrains. We demonstrate our method for the active crater of Aso volcano in Japan. We create digital elevation models by applying the Structure from Motion–Multi-view Stereo algorithm to aerial visible images taken at the same time as the TIR images and then project the TIR images onto the DEM with the direct georeferencing method. The correction is carried out using the geometric parameters acquired in the process. We create 1-m resolution orthorectified thermal images of the crater on two separate dates (18 August 2020 and 16 March 2022) and calculate the heat discharge rates from steaming grounds and a volcanic lake. We find that the heat discharge rate from the fumarolic field on the south crater wall showed a sevenfold increase after the phreatic explosions that occurred on 14 and 20 October 2021. [ABSTRACT FROM AUTHOR]

Image-based 3D modeling has been widely used in many areas. Structure from motion is the key to image-based reconstruction. However, the rapid growth of data poses challenges to current SfM solutions. A hierarchical SfM reconstruction methodology for large-scale oblique images is proposed. Firstly, match pairs are selected using positioning and orientation (POS) data and the terrain of the survey area. Then, images are divided to image groups by traversing the selected match pairs. After pairwise image matching, tracks are decimated using an adaptive track selection method. Thirdly, submaps are reconstructed from the image groups in parallel based on incremental SfM in the object space. A novel method based on statistics of the positional difference between common tracks is proposed to detect the outliers in submap merging. Finally, the reconstructed submaps are incrementally merged and optimized. The proposed methodology was used on a large oblique image set. The proposed methodology was compared with the state-of-the-art image-based reconstruction systems COLMAP and Metashape for SfM reconstruction. Experimental results show that the proposed methodology achieved the highest accuracy on the experimental dataset, i.e., about 22.37, and 3.52 times faster than COLMAP and Metashape, respectively. The experimental results demonstrate that the proposed hierarchical SfM methodology is accurate and efficient for large-scale oblique images. [ABSTRACT FROM AUTHOR]

The current research presents the way to obtain direct georeferencing of photogrammetric imagery and to obtain rigorously georeferenced orthophoto plans without using ground control points. The direct georeferencing procedure is studied in Romania's atypical coordinate systems (planimetric system based on an ellipsoid different than GRS80 and a vertical system of normal elevations, different than the ellipsoidal elevations used in GNSS technology), but it can also be applied to other systems of coordinates. To generate superior photogrammetric products, an innovative orthorectification methodology based on LIDAR data acquired simultaneously with photogrammetric images is presented. LIDAR data is also acquired by a direct georeferencing procedure and transformed with high precision using an application designed for this purpose. Therefore, a much faster way to generate orthophoto plans is presented, with lower production costs, without a substantial loss of the positional quality of the final product. Finally, there is presented the first stereo restitution project in Romania using small size images, acquired with a UAV system by direct georeferencing. The focus on the atypical case of Romania underlines the innovative features of this research. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial vehicles (UAVs) have increased rapidly and successfully established themselves as a tool for the rapid collection of high-resolution images as baseline data in land cover studies and topographic mapping. In photogrammetry using the SfM-MVS method of processing captured images, indirect georeferencing of the digital data through ground control points (GCPs) is usually applied. But selecting, marking, and coordinating GCPs in hardto-reach terrains is time-consuming and sometimes dangerous or impossible. The main objective of this study is to evaluate the accuracy of high-resolution topographic data (HRTD) products of photogrammetric processing of PPK-directly georeferenced images by SfM-MVS workflow. Direct and indirect methods of georeferencing digital products are compared. The planimetric and vertical root mean square error (RMSE) in the position of the validation points were calculated by the differences between measured coordinates in dense point clouds, orthophoto mosaics, and terrain surfaces (DSM), and precisely measured coordinates of the validation points by GNSSRTK receivers. The analysis is based on a statistical evaluation of experimental data obtained from a TAROT X6-based hexacopter equipped with two different image sensor configurations: 1) Sony RX0 action camera and 2) Sony A6000 mirrorless camera, and 3) DJI Phantom 4 Pro quadcopter with integrated additional L1-GNSS module for direct georeferencing by PPKmethod. HRTD generation was performed with three block control configurations for each UAV: 1) Indirect georeferencing via GCP only, 2) PPK direct georeferencing without GCP, and 3) PPK georeferencing using one GCP. Our research showed that when using L1-GNSS onboard receivers for PPK-georeferencing without any GCPs, the point cloud's planimetric accuracy (RMSExy) was from 0.125 to 0.231 cm, depending on the UAV/camera configuration. However, two flight missions produced significant vertical offsets, most likely due to ionospheric disturbances affecting the resolution of phase cycle ambiguities in the single-frequency receivers used. When adding one control point in the PPK georeferencing method, the planimetric and vertical accuracy of the data is comparable to the indirect GCP referencing method. Furthermore, our results show that camera properties (i.e., focal length, resolution, sensor quality) affect the quality and accuracy of digital products. The HRTDs were also evaluated according to the ASPRS (American Photogrammetry and Remote Sensing Society) Standards for Accuracy of Digital Geospatial Data. Analyzing the accuracy of the HRTDs obtained with the experimental UAV/camera configurations for the test area, the present study shows that the PPK-SfM-MVS workflow can provide quality data with a centimeters accuracy of the photogrammetric products. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) equipped with global navigation satellite system-real-time kinematic (GNSS RTK) receivers allow direct georeferencing of the photogrammetric project without using ground control points (GCPs). However, it is necessary to establish the correct methodologies to reduce the errors inherent in these systems, i.e. to reduce the systematic error of the elevation data. For this purpose, multiple GNSS fixed base stations have been used simultaneously. The results showed how the fact of using different bases and averaging their corrections allows to obtain results that improve the altimetric accuracy without the need to use GCPs or oblique photographs. For flight altitudes of 50 m, improvements in altimetric accuracy of 14% were obtained, while for flight altitudes of 70 and 90 m, the improvements in altimetric accuracy reached 35%. Regarding planimetric accuracy, no significant improvements have been found. However, the total errors are similar to those obtained with various combinations of GCPs and closed to the ground sampling distance (GSD) of the photogrammetric project. [ABSTRACT FROM AUTHOR]

Traditionally, photogrammetric product accuracy at cm level is obtained with Ground Control Points (GCP) in UAV photogrammetry. In recent years, UAVs equipped with Post-Processing Kinematic & Real-Time Kinematic (PPK/RTK) have become widespread. Accuracy in cm-level can be obtained with relative/differential positioning with these equipment. On the other hand, PPP (Precise Point Positioning), which is a special type of absolute positioning, is used effectively in many applications. In this study, performances of PPP and PPP-AR (PPP positioning with ambiguity resolution) solutions of kinematic GNSS data obtained from UAVs were investigated and compared with PPK solutions based on relative positioning. Especially, the performance and potential of the PPP-AR approach in terms of quality and accuracy of the products generated in UAV-photogrammetry has been demonstrated. Thus, this study can significantly contribute to subjects such as the production of fast, accurate, and cost-effective products with UAV photogrammetry, earth sciences applications, precise agriculture, sustainable forest management, forest planning. [ABSTRACT FROM AUTHOR]

Copyright of Photogrammetric Record is the property of Wiley-Blackwell 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]

Recently, unmanned aerial vehicles (UAVs) have proven to be reliable and affordable alternatives to conventional manned-airplane aerial survey. UAV with small format rolling shutter camera that causes geometric distortion in image tends to suffer in accuracy, while uncertainty assessment mostly focuses on ground control point's and check point's accuracy, yet its impact on intrinsic parameters has not been fully explored. On the other hand, the advancement of small Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU) have enabled direct georeferencing that doesn't require ground control points, or at least minimum number. The use of less accurate GNSS and IMU in UAV than conventional aerial survey complicates parameter estimation in such as camera calibration parameters, exterior orientation parameters, and so on, which requires attention on the combined impact with rolling shutter compensation option. In this study, the focus is on investigating the combined effect of rolling shutter and GNSS/IMU Georeferencing. Four sets of data with different direct georeferencing and rolling shutter option scenarios were processed using Agisoft Metashape professional. They were analyzed in terms of control/check points accuracy, boresight misalignment, camera calibration parameters, and exterior orientation parameters. The study showed that rolling shutter compensation plays a role in meeting conservative horizontal 1/2 pixels and vertical 1 pixel Root Mean Square Error (RMSE) criteria and that lens distortion residuals are reduced noticeably with rolling shutter option ON. The further investigation showed a coupling effect between intrinsic parameters and rolling shutter compensation effect with different direct georeferencing scenarios, which indicates a strong dependency among principal point offset, affinity, and tangential distortion. [ABSTRACT FROM AUTHOR]

Regular as-built surveys have become a necessary input for building information modelling. Such large-scale 3D data capturing can be conducted effectively by combining structure-from-motion and unmanned aerial vehicles (UAV). Using a RTK-GNSS equipped UAV, 22 repeated weekly campaigns were conducted at two altitudes in various conditions. The photogrammetric approach yielded 3D models, which were compared to the terrestrial laser scanning based ground truth. Better than 2.8 cm geometry RMSE was consistently achieved using integrated georeferencing. It is concluded that the RTK-GNSS based georeferencing enables reaching better than 5 cm geometry accuracy by utilising at least one ground control point. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) or drones are lightly weighted platforms with numerous advantages and can acquire very high-resolution data rapidly with less expenditure. However, the processing of very high-resolution data acquired through the sensors mounted on the UAV platform is a major challenge, and the commercial UAV data processing software is expensive. These software packages require high-configuration hardware and follow the general workflow of conventional photogrammetric approach for image alignment, point cloud generation, mesh generation, DSM, and ortho-mosaic generation. The integration of computer vision algorithms into digital photogrammetric techniques has made it possible to process the high-resolution datasets quickly. A wide variety of open-source software utilities are available that can perform these tasks individually; however, an integrated solution is always desirable. An attempt is made to develop an open-source tool for photogrammetric processing of UAV data using open-source libraries in Python. The software provides a complete workflow for photogrammetric processing of UAV data ranging from camera calibration, point cloud generation from selective frames based on B/H ratio, direct georeferencing of generated point cloud and digital elevation model (DEM) generation. The developed software is compatible with both 32-bit and 64-bit operating systems and low configuration hardware. [ABSTRACT FROM AUTHOR]

Recent development of lightweight and small size multi-frequency GNSS receivers allows determination of the precise position of the moving platform and spatial data acquisition without the need for setting up and measuring of ground control points. The main advantage of this approach is a higher operational capacity with reduced time and cost of field measurement. This relates to fieldwork in inaccessible areas with demanding terrain configuration. In this paper development and use of a UAS with direct georeferencing of camera sensor for spatial data acquisition is described, and the possibility of 3D scene reconstruction based on the precise position of the camera with predetermined interior parameters is examined. Modern computer vision-based SfM photogrammetry algorithms are used for determining attitude parameters and reconstruction of the scene. For that purpose, several tests on two different test fields were performed using various system parameters for collecting and analysis of several spatial data sets. The presented results demonstrate a satisfactory accuracy (3.1 cm planar and 6.4 cm spatial) of the system for various applications in geodesy. [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]

The modular aerial camera system (MACS) is a development platform for optical remote sensing concepts, algorithms and special environments. For real-time services for maritime security (EMSec joint project), a new multi-sensor configuration MACS-Mar was realized. It consists of four co-aligned sensor heads in the visible RGB, near infrared (NIR, 700-950 nm), hyperspectral (HS, 450-900 nm) and thermal infrared (TIR, 7.5-14 µm) spectral range, a mid-cost navigation system, a processing unit and two data links. On-board image projection, cropping of redundant data and compression enable the instant generation of direct-georeferenced high-resolution image mosaics, automatic object detection, vectorization and annotation of floating objects on the water surface. The results were transmitted over a distance up to 50 km in real-time via narrow and broadband data links and were visualized in a maritime situation awareness system. For the automatic onboard detection of floating objects, a segmentation and classification workflow based on RGB, IR and TIR information was developed and tested. The completeness of the object detection in the experiment resulted in 95%, the correctness in 53%. Mostly, bright backwash of ships lead to an overestimation of the number of objects, further refinement using water homogeneity in the TIR, as implemented in the workflow, couldn't be carried out due to problems with the TIR sensor, else distinctly better results could have been expected. The absolute positional accuracy of the projected real-time imagery resulted in 2 m without postprocessing of images or navigation data, the relative measurement accuracy of distances is in the range of the image resolution, which is about 12 cm for RGB imagery in the EMSec experiment. [ABSTRACT FROM AUTHOR]

Copyright of Photogrammetric Record is the property of Wiley-Blackwell 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.)

Action cameras can operate in outdoor conditions, such as outside a car, and provide good quality imagery that can be exploited to collect geospatial data by photogrammetric means. Recent models include GPS, which can deliver position and time of individual images and video frames. That is the case of the very popular camera, Gopro Hero 5. This paper describes the implementation of a mobile mapping system, based on a GoPro Hero 5 camera mounted on the side rearview mirror of a car. Although the system can be dependent on the camera GPS positions only, it was developed to include a GNSS dual frequency receiver, carried inside the car, on the dashboard. Within good observation conditions, without tall buildings, differential positioning (either RTK or PPK) provides the trajectory with accuracy of a few centimetres. The precise time of individual frames is obtained from the camera GPS and positions are interpolated from the GNSS receiver. Assuming the car moves in a horizontal plane and the camera has no significant tilts, the system is treated in planimetric terms, with camera axis azimuth derived from the vehicle trajectory. Positions of observed objects, such as traffic signs, are derived from consecutive frames. Tests carried out in a sparse urban environment have shown planimetric accuracy better than 40 cm, appropriate for large scale mapping, such as 1:2000. The system can be improved in several forms, through processing techniques, such as structure from motion, but without the incorporation of additional hardware. [ABSTRACT FROM AUTHOR]

Many remote sensing applications demand for a fast and efficient way of generating orthophoto maps from raw aerial images. One prerequisite is direct georeferencing, which allows to geolocate aerial images to their geographic position on the earth's surface. But this is only half the story. When dealing with a large quantity of highly overlapping images, a major challenge is to select the most suitable image parts in order to generate seamless aerial maps of the captured area. This paper proposes a method that quickly determines such an optimal (rectangular) section for each single aerial image, which in turn can be used for generating seamless aerial maps. Its key approach is to clip aerial images depending on their geometric intersections with a terrain elevation model of the captured area, which is why we call it terrain aware image clipping (TAC). The method has a modest computational footprint and is therefore applicable even for rather limited embedded vision systems. It can be applied for both, real-time aerial mapping applications using data links as well as for rapid map generation right after landing without any postprocessing step. Referring to real-time applications, this method also minimizes transmission of redundant image data. The proposed method has already been demonstrated in several search-and-rescue scenarios and real-time mapping applications using a broadband data link and diffent kinds of camera and carrier systems. Moreover, a patent for this technology is pending. [ABSTRACT FROM AUTHOR]

Low-cost unmanned aerial vehicles (UAVs) utilizing push-broom hyperspectral scanners are poised to become a popular alternative to conventional remote sensing platforms such as manned aircraft and satellites. In order to employ this emerging technology in fields such as high-throughput phenotyping and precision agriculture, direct georeferencing of hyperspectral data using onboard integrated global navigation satellite systems (GNSSs) and inertial navigation systems (INSs) is required. Directly deriving the scanner position and orientation requires the spatial and rotational relationship between the coordinate systems of the GNSS/INS and hyperspectral scanner to be measured. The spatial offset (lever arm) between the scanner and GNSS/INS unit can be measured manually. However, the angular relationship (boresight angles) between the scanner and GNSS/INS coordinate systems, which is more critical for accurate generation of georeferenced products, is difficult to establish. This paper presents three calibration approaches to estimate the boresight angles relating hyperspectral push-broom scanner and GNSS/INS coordinate systems. For reliable/practical estimation of the boresight angles, this paper starts with establishing the optimal/minimal flight and control/tie point configuration through a bias impact analysis starting from the point positioning equation. Then, an approximate calibration procedure utilizing tie points in overlapping scenes is presented after making some assumptions about the flight trajectory and topography of covered terrain. Next, two rigorous approaches are introduced – one using ground control points and other using tie features. The approximate/rigorous approaches are based on enforcing the collinearity and coplanarity of the light rays connecting the perspective centers of the imaging scanner, object point, and the respective image points. To evaluate the accuracy of the proposed approaches, estimated boresight angles are used for orthorectification of six hyperspectral UAV dataset acquired over an agricultural field. Qualitative and quantitative evaluations of the results have shown significant improvement in the derived orthophotos to a level equivalent to the ground sampling distance of the used scanner (namely, 3–5 cm when flying at 60 m). [ABSTRACT FROM PUBLISHER]

During the last few years, the acquisition of geometric information about objects by using a moving sensor platform has gained increasing popularity in the surveying community. A large number of companies offer vehicle-based mobile mapping systems, which usually contain a fast profile laser scanner, a high-precision inertial measurement unit, and geodetic global navigation satellite system (GNSS) receivers to directly georeference the laser scans and build a consistent point cloud of the object. In contrast, there is a growing number of companies offering small and lightweight unmanned aerial vehicles (UAVs), which automatically fly over the area of interest and create dense point clouds of the environment by using camera images and photogrammetric-processing software. In this case, the georeferencing is usually realized by ground control points. This contribution summarizes activities performed by the authors to bring both fields closer together by developing a small (11×10×5 cm) and lightweight (240-g) direct-georeferencing unit, which is able to provide accurate position (<5 cm) and orientation (<1°) information in real time. The authors describe the development of the sensor unit and the sensor-fusion algorithms, address the topics of calibration and accuracy evaluation, and provide an overview of different applications in which the unit has been already used. These include the high-resolution acquisition of crop-surface models by using UAV-based imagery, the direct georeferencing of an autonomously flying robot with a laser scanner and multiple cameras, and the generation of laser point clouds using a human-carried mobile mapping system. [ABSTRACT FROM AUTHOR]

For some years now, UAVs (unmanned aerial vehicles) are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic) GPS (global positioning system) receiver and additional sensors (e.g. inertial sensors). In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies. [ABSTRACT FROM AUTHOR]

The declining costs of small Unmanned Aerial Systems (sUAS), in combination with Structure-from-Motion (SfM) photogrammetry have triggered renewed interest in image-based topography reconstruction. However, the potential uptake of sUAS-based topography is limited by the need for ground control acquired with expensive survey equipment. Direct georeferencing (DG) is a workflow that obviates ground control and uses only the camera positions to georeference the SfM results. However, the absence of ground control poses significant challenges in terms of the data quality of the final geospatial outputs. Notably, it is generally accepted that ground control is required to georeference, refine the camera calibration parameters, and remove any artefacts of optical distortion from the topographic model. Here, we present an examination of DG carried out with low-cost consumer-grade sUAS. We begin with a study of surface deformations resulting from systematic perturbations of the radial lens distortion parameters. We then test a number of flight patterns and develop a novel error quantification method to assess the outcomes. Our perturbation analysis shows that there exists families of predictable equifinal solutions of K1- K2 which minimize doming in the output model. The equifinal solutions can be expressed as K2 = f ( K1) and they have been observed for both the DJI Inspire 1 and Phantom 3 sUAS platforms. This equifinality relationship can be used as an external reliability check of the self-calibration and allow a DG workflow to produce topography exempt of non-affine deformations and with random errors of 0.1% of the flying height, linear offsets below 10 m and off-vertical tilts below 1°. Whilst not yet of survey-grade quality, these results demonstrate that low-cost sUAS are capable of producing reliable topography products without recourse to expensive survey equipment and we argue that direct georeferencing and low-cost sUAS could transform survey practices in both academic and commercial disciplines. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The georeferencing process is crucial to the accuracy of terrestrial laser scanner (TLS) data, in particular in the context of diachronic studies relying on multi-temporal surveys. The use of Ground Control Points in the georeferencing process can however be complex when confronted with the practical constraints of coastal surveying. A simple and quick alternative method called “pseudo-direct georeferencing” is proposed in the present paper. This method involves internal inclinometers to measure roll and pitch angles and a centimetric GPS to measure the position of the TLS center and the position of one backsight target. When assessing the transformational uncertainty by using a set of independent ground validation points for both classical indirect and proposed pseudo-direct methods, we respectively obtain root mean square errors of 4.4 cm for the indirect method and 3.8 cm for the pseudo-direct method. [ABSTRACT FROM PUBLISHER]

Photogrammetric procedures using the integration of imagery and light detection and ranging (Lidar) datasets are becoming common in mapping companies nowadays. When photogrammetric and Lidar surveys are performed simultaneously while having the camera connected to the Lidar system, the image's exterior orientation parameters computed from the Lidar system can be used to perform photogrammetric applications. To implement such approach, camera calibration procedures should be applied to obtain accurate interior orientation parameters. This paper shows the performed study and experimental results from an in situ self-calibration using simultaneously collected imagery and Lidar datasets. The experimental study is conducted to devise a methodology for the in situ self-calibration that uses a set of vertical control points, extracted from Lidar point cloud, as well as the three-dimensional coordinates of the camera exposure stations, computed from the Lidar trajectory. For the small photogrammetric block used in this study, the results from the performed experiments demonstrated that the in situ self-calibration is required to obtain horizontal accuracies of approximately one image pixel on the ground in bundle adjustment assisted by direct measured of the coordinates of the camera exposure stations. [ABSTRACT FROM PUBLISHER]

Position and orientation system (POS) is widely applied to the various mapping sensors for airborne direct georeferencing. As the accuracy requirements vary in different mapping applications, the POS error analysis is important for the system design. In this paper, an analytical approach to the POS error analysis for ground alignment and constant-velocity flight is proposed. First, the simplified system model is obtained for the error analysis. Then, by applying the two-stage Kalman filter, the analytical relations between the attitude errors and estimation errors of the biases of the inertial sensors are derived. Finally, the experiment is carried out to confirm the effectiveness of the proposed method. The proposed method is not only effective and straightforward but also provides us some new insights into the POS error characteristics. [ABSTRACT FROM AUTHOR]

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to investigate the potential of using Unmanned Aerial Vehicles (UAVs) as a platform to collect geospatial data for rapid response applications, especially in hard-to-access and hazardous areas. The UAVs are low-cost mapping vehicles, and they are easy to handle and deploy in-field. These characteristics make UAVs ideal candidates for rapid-response and disaster mitigation scenarios. The majority of the available UAV systems are not capable of real-time/near real-time data processing. This paper introduces a low-cost UAV-based multi-sensor mapping payload which supports real-time processing and can be effectively used in rapid-response applications. The paper introduces the main components of the system, and provides an overview of the proposed payload architecture. Then, it introduces the implementation details of the major building blocks of the system. Finally, the paper presents our conclusions and the future work, in order to achieve real-time/near real-time data processing and product delivery capabilities. [ABSTRACT FROM AUTHOR]

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs. [ABSTRACT FROM AUTHOR]

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process. [ABSTRACT FROM AUTHOR]

Direct Georeferencing was shown to be an important alternative to standard indirect image orientation using classical or GPS-supported aerial triangulation. Since direct Georeferencing without ground control relies on an extrapolation process only, particular focus has to be laid on the overall system calibration procedure. The accuracy performance of integrated GPS/inertial systems for direct Georeferencing in airborne photogrammetric environments has been tested extensively in the last years. In this approach, the limiting factor is a correct overall system calibration including the GPS/inertial component as well as the imaging sensor itself. Therefore remaining errors in the system calibration will significantly decrease the quality of object point determination. This research paper presents an error analysis for the airborne direct Georeferencing technique, where integrated GPS/IMU positioning and navigation systems are used, in conjunction with aerial cameras for airborne mapping compared with GPS/INS supported AT through the implementation of certain amount of error on the EOP and Boresight parameters and study the effect of these errors on the final ground coordinates. The data set is a block of images consists of 32 images distributed over six flight lines, the interior orientation parameters, IOP, are known through careful camera calibration procedure, also 37 ground control points are known through terrestrial surveying procedure. The exact location of camera station at time of exposure, exterior orientation parameters, EOP, is known through GPS/INS integration process. The preliminary results show that firstly, the DG and GPS-supported AT have similar accuracy and comparing with the conventional aerial photography method, the two technologies reduces the dependence on ground control (used only for quality control purposes). Secondly, In the DG Correcting overall system calibration including the GPS/inertial component as well as the imaging sensor itself is the limiting factor to achieve good object space. [ABSTRACT FROM AUTHOR]

GNSS/INS system composed of Global Navigation Satellite System and Inertial Navigation System together can provide orientation parameters directly by the observations collected during the flight. Thus orientation parameters can be obtained by GNSS/INS integration process without any need for aero triangulation after the flight. In general, positional uncertainty can be estimated with known coordinates of Ground Control Points (GCP) which require field works such as marker construction and GNSS measurement leading additional cost to the project. Here the question arises what should be the theoretical uncertainty of point coordinates depending on the uncertainties of orientation parameters. In this study the contribution of each orientation parameter on positional uncertainty is examined and theoretical positional uncertainty is computed without GCP measurement for direct georeferencing using a graphical user interface developed in MATLAB. [ABSTRACT FROM AUTHOR]

Synergistic applications based on integrated hyperspectral and lidar data are receiving a growing interest from the remote-sensing community. A prerequisite for the optimum sensor fusion of hyperspectral and lidar data is an accurate geometric coalignment. The simple unadjusted integration of lidar elevation and hyperspectral reflectance causes a substantial loss of information and does not exploit the full potential of both sensors. This paper presents a novel approach for the geometric coalignment of hyperspectral and lidar airborne data, based on their respective adopted return intensity information. The complete approach incorporates ray tracing and subpixel procedures in order to overcome grid inherent discretization. It aims at the correction of extrinsic and intrinsic (camera resectioning) parameters of the hyperspectral sensor. In additional to a tie-point-based coregistration, we introduce a ray-tracing-based back projection of the lidar intensities for area-based cost aggregation. The approach consists of three processing steps. First is a coarse automatic tie-point-based boresight alignment. The second step coregisters the hyperspectral data to the lidar intensities. Third is a parametric coalignment refinement with an area-based cost aggregation. This hybrid approach of combining tie-point features and area-based cost aggregation methods for the parametric coregistration of hyperspectral intensity values to their corresponding lidar intensities results in a root-mean-square error of 1/3 pixel. It indicates that a highly integrated and stringent combination of different coalignment methods leads to an improvement of the multisensor coregistration. [ABSTRACT FROM AUTHOR]

Efficient mapping from unmanned aerial platforms cannot rely on aerial triangulation using known ground control points. The cost and time of setting ground control, added to the need for increased overlap between flight lines, severely limits the ability of small VTOL platforms, in particular, to handle mapping-grade missions of all but the very smallest survey areas. Applanix has brought its experience in manned photogrammetry applications to this challenge, setting out the requirements for increasing the efficiency of mapping operations from small UAVs, using survey-grade GNSS-Inertial technology to accomplish direct georeferencing of the platform and/or the imaging payload. The Direct Mapping Solution for Unmanned Aerial Vehicles (DMS-UAV) is a complete and ready-to-integrate OEM solution for Direct Georeferencing (DG) on unmanned aerial platforms. Designed as a solution for systems integrators to create mapping payloads for UAVs of all types and sizes, the DMS produces directly georeferenced products for any imaging payload (visual, LiDAR, infrared, multispectral imaging, even video). Additionally, DMS addresses the airframe's requirements for high-accuracy position and orientation for such tasks as precision RTK landing and Precision Orientation for Air Data Systems (ADS), Guidance and Control. This paper presents results using a DMS comprised of an Applanix APX-15 UAV with a Sony a7R camera to produce highly accurate orthorectified imagery without Ground Control Points on a Microdrones md4-1000 platform conducted by Applanix and Avyon. APX-15 UAV is a single-board, small-form-factor GNSS-Inertial system designed for use on small, lightweight platforms. The Sony a7R is a prosumer digital RGB camera sensor, with a 36MP, 4.9-micron CCD producing images at 7360 columns by 4912 rows. It was configured with a 50mm AF-S Nikkor f/1.8 lens and subsequently with a 35mm Zeiss Sonnar T* FE F2.8 lens. Both the camera/lens combinations and the APX-15 were mounted to a Microdrones md4-1000 quad-rotor VTOL UAV. The Sony A7R and each lens combination were focused and calibrated terrestrially using the Applanix camera calibration facility, and then integrated with the APX-15 GNSS-Inertial system using a custom mount specifically designed for UAV applications. The mount is constructed in such a way as to maintain the stability of both the interior orientation and IMU boresight calibration over shock and vibration, thus turning the Sony A7R into a metric imaging solution. In July and August 2015, Applanix and Avyon carried out a series of test flights of this system. The goal of these test flights was to assess the performance of DMS APX-15 direct georeferencing system under various scenarios. Furthermore, an examination of how DMS APX-15 can be used to produce accurate map products without the use of ground control points and with reduced sidelap was also carried out. Reducing the side lap for survey missions performed by small UAVs can significantly increase the mapping productivity of these platforms. The area mapped during the first flight campaign was a 250m x 300m block and a 775m long railway corridor in a rural setting in Ontario, Canada. The second area mapped was a 450m long corridor over a dam known as Fryer Dam (over Richelieu River in Quebec, Canada). Several ground control points were distributed within both test areas. The flight over the block area included 8 North-South lines and 1 cross strip flown at 80m AGL, resulting in a ~1cm GSD. The flight over the railway corridor included 2 North-South lines also flown at 80m AGL. Similarly, the flight over the dam corridor included 2 North-South lines flown at 50m AGL. The focus of this paper was to analyse the results obtained from the two corridors. Test results from both areas were processed using Direct Georeferencing techniques, and then compared for accuracy against the known positions of ground control points in each test area. The GNSS-Inertial data collected by the APX-15 was post-processed in Single Base mode, using a base station located in the project area via POSPac UAV. For the block and railway corridor, the base-station's position was precisely determined by processing a 12-hour session using the CSRS-PPP Post Processing service. Similarly, for the flight over Fryer Dam, the base-station's position was also precisely determined by processing a 4-hour session using the CSRS-PPP Post Processing service. POSPac UAV's camera calibration and quality control (CalQC) module was used to refine the camera interior orientation parameters using an Integrated Sensor Orientation (ISO) approach. POSPac UAV was also used to generate the Exterior Orientation parameters for images collected during the test flight. The Inpho photogrammetric software package was used to develop the final map products for both corridors under various scenarios. The imagery was first imported into an Inpho project, with updated focal length, principal point offsets and Exterior Orientation parameters. First, a Digital Terrain/Surface Model (DTM/DSM) was extracted from the stereo imagery, following which the raw images were orthorectified to produce an orthomosaic product. [ABSTRACT FROM AUTHOR]

The main purpose of any aerial photo archive is to allow quick access to images based on content and location. Therefore, next to a description of technical parameters and depicted content, georeferencing of every image is of vital importance. This can be done either by identifying the main photographed object (georeferencing of the image content) or by mapping the center point and/or the outline of the image footprint. The paper proposes a new image archiving workflow. The new pipeline is based on the parameters that are logged by a commercial, but cost-effective GNSS/IMU solution and processed with in-house-developed software. Together, these components allow one to automatically geolocate and rectify the (oblique) aerial images (by a simple planar rectification using the exterior orientation parameters) and to retrieve their footprints with reasonable accuracy, which is automatically stored as a vector file. The data of three test flights were used to determine the accuracy of the device, which turned out to be better than 1| for roll and pitch (mean between 0.0 and 0.21 with a standard deviation of 0.17-0.46) and better than 2.5± for yaw angles (mean between 0.0 and -0.14 with a standard deviation of 0.58-0.94). This turned out to be sufficient to enable a fast and almost automatic GIS-based archiving of all of the imagery. [ABSTRACT FROM AUTHOR]

Efficient mapping from unmanned aerial platforms cannot rely on aerial triangulation using known ground control points. The cost and time of setting ground control, added to the need for increased overlap between flight lines, severely limits the ability of small VTOL platforms, in particular, to handle mapping-grade missions of all but the very smallest survey areas. Applanix has brought its experience in manned photogrammetry applications to this challenge, setting out the requirements for increasing the efficiency of mapping operations from small UAVs, using survey-grade GNSS-Inertial technology to accomplish direct georeferencing of the platform and/or the imaging payload. The Direct Mapping Solution for Unmanned Aerial Vehicles (DMS-UAV) is a complete and ready-to-integrate OEM solution for Direct Georeferencing (DG) on unmanned aerial platforms. Designed as a solution for systems integrators to create mapping payloads for UAVs of all types and sizes, the DMS produces directly georeferenced products for any imaging payload (visual, LiDAR, infrared, multispectral imaging, even video). Additionally, DMS addresses the airframe's requirements for high-accuracy position and orientation for such tasks as precision RTK landing and Precision Orientation for Air Data Systems (ADS), Guidance and Control. This paper presents results using a DMS comprised of an Applanix APX-15 UAV with a Sony a7R camera to produce highly accurate orthorectified imagery without Ground Control Points on a Microdrones md4-1000 platform conducted by Applanix and Avyon. APX-15 UAV is a single-board, small-form-factor GNSS-Inertial system designed for use on small, lightweight platforms. The Sony a7R is a prosumer digital RGB camera sensor, with a 36MP, 4.9-micron CCD producing images at 7360 columns by 4912 rows. It was configured with a 50mm AF-S Nikkor f/1.8 lens and subsequently with a 35mm Zeiss Sonnar T* FE F2.8 lens. Both the camera/lens combinations and the APX-15 were mounted to a Microdrones md4-1000 quad-rotor VTOL UAV. The Sony A7R and each lens combination were focused and calibrated terrestrially using the Applanix camera calibration facility, and then integrated with the APX-15 GNSS-Inertial system using a custom mount specifically designed for UAV applications. The mount is constructed in such a way as to maintain the stability of both the interior orientation and IMU boresight calibration over shock and vibration, thus turning the Sony A7R into a metric imaging solution. In July and August 2015, Applanix and Avyon carried out a series of test flights of this system. The goal of these test flights was to assess the performance of DMS APX-15 direct georeferencing system under various scenarios. Furthermore, an examination of how DMS APX-15 can be used to produce accurate map products without the use of ground control points and with reduced sidelap was also carried out. Reducing the side lap for survey missions performed by small UAVs can significantly increase the mapping productivity of these platforms. The area mapped during the first flight campaign was a 250m x 300m block and a 775m long railway corridor in a rural setting in Ontario, Canada. The second area mapped was a 450m long corridor over a dam known as Fryer Dam (over Richelieu River in Quebec, Canada). Several ground control points were distributed within both test areas. The flight over the block area included 8 North-South lines and 1 cross strip flown at 80m AGL, resulting in a ~1cm GSD. The flight over the railway corridor included 2 North-South lines also flown at 80m AGL. Similarly, the flight over the dam corridor included 2 North-South lines flown at 50m AGL. The focus of this paper was to analyse the results obtained from the two corridors. Test results from both areas were processed using Direct Georeferencing techniques, and then compared for accuracy against the known positions of ground control points in each test area. The GNSS-Inertial data collected by the APX-15 was post-processed in Single Base mode, using a base station located in the project area via POSPac UAV. For the block and railway corridor, the base-station's position was precisely determined by processing a 12-hour session using the CSRS-PPP Post Processing service. Similarly, for the flight over Fryer Dam, the base-station's position was also precisely determined by processing a 4-hour session using the CSRS-PPP Post Processing service. POSPac UAV's camera calibration and quality control (CalQC) module was used to refine the camera interior orientation parameters using an Integrated Sensor Orientation (ISO) approach. POSPac UAV was also used to generate the Exterior Orientation parameters for images collected during the test flight. The Inpho photogrammetric software package was used to develop the final map products for both corridors under various scenarios. The imagery was first imported into an Inpho project, with updated focal length, principal point offsets and Exterior Orientation parameters. First, a Digital Terrain/Surface Model (DTM/DSM) was extracted from the stereo imagery, following which the raw images were orthorectified to produce an orthomosaic product. [ABSTRACT FROM AUTHOR]

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process. [ABSTRACT FROM AUTHOR]

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs. [ABSTRACT FROM AUTHOR]

In recent years, kinematic laser scanning has become increasingly popular because it offers many benefits compared to static laser scanning. The advantages include both saving of time in the georeferencing and a more favorable scanning geometry. Often mobile laser scanning systems are installed on wheeled platforms, which may not reach all parts of the object. Hence, there is an interest in the development of portable systems, which remain operational even in inaccessible areas. The development of such a portable laser scanning system is presented in this paper. It consists of a lightweight direct georeferencing unit for the position and attitude determination and a small low-cost 2D laser scanner. This setup provides advantages over existing portable systems that employ heavy and expensive 3D laser scanners in a profiling mode. A special emphasis is placed on the system calibration, i. e. the determination of the transformation between the coordinate frames of the direct georeferencing unit and the 2D laser scanner. To this end, a calibration field is used, which consists of differently orientated georeferenced planar surfaces, leading to estimates for the lever arms and boresight angles with an accuracy of mm and one-tenth of a degree. Finally, point clouds of the mobile laser scanning system are compared with georeferenced point clouds of a high-precision 3D laser scanner. Accordingly, the accuracy of the system is in the order of cm to dm. This is in good agreement with the expected accuracy, which has been derived from the error propagation of previously estimated variance components. [ABSTRACT FROM AUTHOR]

The complexity of the single linear hyperspectral pushbroom imaging based on a high altitude airship (HAA) without a three-axis stabilized platform is much more than that based on the spaceborne and airborne. Due to the effects of air pressure, temperature and airflow, the large pitch and roll angles tend to appear frequently that create pushbroom images highly characterized with severe geometric distortions. Thus, the in-flight calibration procedure is not appropriate to apply to the single linear pushbroom sensors on HAA having no three-axis stabilized platform. In order to address this problem, a new ground-based boresight calibration method is proposed. Firstly, a coordinate's transformation model is developed for direct georeferencing (DG) of the linear imaging sensor, and then the linear error equation is derived from it by using the Taylor expansion formula. Secondly, the boresight misalignments are worked out by using iterative least squares method with few ground control points (GCPs) and ground-based side-scanning experiments. The proposed method is demonstrated by three sets of experiments: (i) the stability and reliability of the method is verified through simulation-based experiments; (ii) the boresight calibration is performed using ground-based experiments; and (iii) the validation is done by applying on the orthorectification of the real hyperspectral pushbroom images from a HAA Earth observation payload system developed by our research team--"LanTianHao". The test results show that the proposed boresight calibration approach significantly improves the quality of georeferencing by reducing the geometric distortions caused by boresight misalignments to the minimum level. [ABSTRACT FROM AUTHOR]

In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5°) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05° for the roll and the pitch angle and 0.2° for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases. [ABSTRACT FROM AUTHOR]

Over the last decade, Unmanned Airbone Vehicles (UAVs) have been largely used for civil applications. Airborne photogrammetry has found place in these applications not only for 3D modeling but also as a measurement tool. Vinci-Construction-Terrassement is a private company specialized in public works sector and uses airborn photogrammetry as a mapping solution and metrology investigation tool on its sites. This technology is very efficient for the calculation of stock volumes for instance, or for time tracking of specific areas with risk of landslides. The aim of the present work is to perform a direct georeferencing of images acquired by the camera leaning on an embedded GPS receiver. UAV, GPS receiver and camera used are low-cost models and therefore data processing is adapted to this particular constraint. [ABSTRACT FROM AUTHOR]

This paper presents results from a Direct Mapping Solution (DMS) comprised of an Applanix APX-15 UAV GNSS-Inertial system integrated with a Sony a7R camera to produce highly accurate ortho-rectified imagery without Ground Control Points on a Microdrones md4-1000 platform. A 55 millimeter Nikkor f/1.8 lens was mounted on the Sony a7R and the camera was then focused and calibrated terrestrially using the Applanix camera calibration facility, and then integrated with the APX-15 UAV GNSS-Inertial system using a custom mount specifically designed for UAV applications. In July 2015, Applanix and Avyon carried out a test flight of this system. The goal of the test flight was to assess the performance of DMS APX-15 UAV direct georeferencing system on the md4-1000. The area mapped during the test was a 250 x 300 meter block in a rural setting in Ontario, Canada. Several ground control points are distributed within the test area. The test included 8 North-South lines and 1 cross strip flown at 80 meters AGL, resulting in a ~1 centimeter Ground Sample Distance (GSD). Map products were generated from the test flight using Direct Georeferencing, and then compared for accuracy against the known positions of ground control points in the test area. The GNSS-Inertial data collected by the APX-15 UAV was post-processed in Single Base mode, using a base station located in the project area via POSPac UAV. The base-station's position was precisely determined by processing a 12-hour session using the CSRS-PPP Post Processing service. The ground control points were surveyed in using differential GNSS post-processing techniques with respect to the base-station. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial vehicles (UAVs) have increasingly been used in various application areas, such as in the remote sensing or surveying. For these applications the UAV has to be equipped with a mapping sensor, which is mostly a camera. Furthermore, a georeferencing of the UAV platform and/or the acquired mapping data is required. The most efficient way to realize this georeferencing is the direct georeferencing, which is based on an onboard multi-sensor system. In recent decades, direct georeferencing systems have been researched and used extensively in airborne, ship and land vehicle applications. However, these systems cannot easily be adapted to UAV platforms, which is mainly due to weight and size limitations. In this paper a direct georeferencing system for micro- and mini-sized UAVs is presented, which consists of a dual-frequency geodetic grade OEM GPS board, a low-cost single-frequency GPS chip, a tactical grade IMU and a magnetometer. To allow for cm-level position and sub-degree attitude accuracies, RTK GPS (real-time kinematic) and GPS attitude (GPS compass) determination algorithms are running on this system, as well as a GPS/IMU integration. Beside the direct georeferencing, also the precise time synchronization of the camera, which acts as the main sensor for mobile mapping applications, and the calibration of the lever arm between the camera reference point and the direct georeferencing reference point are explained in this paper. Especially the high accurate time synchronization of the camera is very important, to still allow for high surveying accuracies, when the images are taken during the motion of the UAV. Results of flight tests demonstrate that the developed system, the camera synchronization and the lever arm calibration make directly georeferenced UAV based single point measurements possible, which have cm-level accuracies on the ground. [ABSTRACT FROM AUTHOR]

There are many disasters happened because the weather changes extremely in these years. To facilitate applications such as environment detection or monitoring becomes very important. Therefore, the development of rapid low cost systems for collecting near real-time spatial information is very critical. Rapid spatial information collection has become an emerging trend for remote sensing and mapping applications. This study develops a Direct Georeferencing (DG) based Unmanned Aerial Vehicle (UAV) helicopter photogrammetric platform where an Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated Positioning and Orientation System (POS) system is implemented to provide the DG capability of the platform. The performance verification indicates that the proposed platform can capture aerial images successfully. A flight test is performed to verify the positioning accuracy in DG mode without using Ground Control Points (GCP). The preliminary results illustrate that horizontal DG positioning accuracies in the x and y axes are around 5 meter with 100 meter flight height. The positioning accuracy in the z axis is less than 10 meter. Such accuracy is good for near real-time disaster relief. The DG ready function of proposed platform guarantees mapping and positioning capability even in GCP free environments, which is very important for rapid urgent response for disaster relief. Generally speaking, the data processing time for the DG module, including POS solution generalization, interpolation, Exterior Orientation Parameters (EOP) generation, and feature point measurements, is less than 1 hour. [ABSTRACT FROM AUTHOR]

Copyright of Photogrammetric Record is the property of Wiley-Blackwell 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.)