scholarly journals Utilizing Airborne LiDAR and UAV Photogrammetry Techniques in Local Geoid Model Determination and Validation

2020 ◽  
Vol 9 (9) ◽  
pp. 528 ◽  
Author(s):  
Serdar Erol ◽  
Emrah Özögel ◽  
Ramazan Alper Kuçak ◽  
Bihter Erol
Keyword(s):  
Point Clouds ◽  
Satellite System ◽  
Airborne Lidar ◽  
Geoid Model ◽  
Digital Terrain ◽  
Novel Approach ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Regional Gravimetric Geoid ◽  
Local Geoid

This investigation evaluates the performance of digital terrain models (DTMs) generated in different vertical datums by aerial LiDAR and unmanned aerial vehicle (UAV) photogrammetry techniques, for the determination and validation of local geoid models. Many engineering projects require the point heights referring to a physical surface, i.e., geoid, rather than an ellipsoid. When a high-accuracy local geoid model is available in the study area, the physical heights are practically obtained with the transformation of global navigation satellite system (GNSS) ellipsoidal heights of the points. Besides the commonly used geodetic methods, this study introduces a novel approach for the determination and validation of the local geoid surface models using photogrammetry. The numeric tests were carried out in the Bergama region, in the west of Turkey. Using direct georeferenced airborne LiDAR and indirect georeferenced UAV photogrammetry-derived point clouds, DTMs were generated in ellipsoidal and geoidal vertical datums, respectively. After this, the local geoid models were calculated as differences between the generated DTMs. Generated local geoid models in the grid and pointwise formats were tested and compared with the regional gravimetric geoid model (TG03) and a high-resolution global geoid model (EIGEN6C4), respectively. In conclusion, the applied approach provided sufficient performance for modeling and validating the geoid heights with centimeter-level accuracy.

scholarly journals Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices

2020 ◽  
Vol 12 (21) ◽  
pp. 3616
Author(s):  
Stefano Tavani ◽  
Antonio Pignalosa ◽  
Amerigo Corradetti ◽  
Marco Mercuri ◽  
Luca Smeraglia ◽  
...  
Keyword(s):  
3D Model ◽  
Model Building ◽  
Satellite System ◽  
Test Case ◽  
Digital Terrain ◽  
Ground Control Points ◽  
Terrain Models ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
The Impact

Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation.

scholarly journals Unmanned Aerial Vehicle Surveying For Monitoring Road Construction Earthworks

2019 ◽  
Vol 14 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Kalev Julge ◽  
Artu Ellmann ◽  
Romet Köök
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Road Construction ◽  
Point Clouds ◽  
Satellite System ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Sand And Gravel ◽  
The Impact

Unmanned aerial vehicle photogrammetry is a surveying technique that enables generating point clouds, 3D surface models and orthophoto mosaics. These are based on photos captured with a camera placed on an unmanned aerial vehicle. Within the framework of this research, unmanned aerial vehicle photogrammetry surveys were carried out over a sand and gravel embankment with the aim of assessing the vertical accuracy of the derived surface models. Flight altitudes, ground control points and cameras were varied, and the impact of various factors on the results was monitored. In addition, the traditional real-time-kinematic Global Navigation Satellite System surveys were conducted for verifications. Surface models acquired by different methods were used to calculate volumes and compare the results with requirements set by Estonian Road Administration. It was found that with proper measuring techniques an accuracy of 5.7 cm for the heights were achieved.

scholarly journals Sea Topography of the Ionian and Adriatic Seas Using Repeated GNSS Measurements

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 812
Author(s):  
Sotiris Lycourghiotis
Keyword(s):  
Satellite System ◽  
Geoid Model ◽  
Sea Surface Topography ◽  
Mean Sea Surface ◽  
The Mean ◽  
A New Technique ◽  
Gnss Measurements ◽  
Global Navigation Satellite ◽  
Constant Slope ◽  
Ionian And Adriatic Seas

The mean sea surface topography of the Ionian and Adriatic Seas has been determined. This was based on six-months of Global Navigation Satellite System (GNSS) measurements which were performed on the Ionian Queen (a ship). The measurements were analyzed following a double-path methodology based on differential GNSS (D-GNSS) and precise point positioning (PPP) analysis. Numerical filtering techniques, multi-parametric accuracy analysis and a new technique for removing the meteorological tide factors were also used. Results were compared with the EGM96 geoid model. The calculated differences ranged between 0 and 48 cm. The error of the results was estimated to fall within 3.31 cm. The 3D image of the marine topography in the region shows a nearly constant slope of 4 cm/km in the N–S direction. Thus, the effectiveness of the approach “repeated GNSS measurements on the same route of a ship” developed in the context of “GNSS methods on floating means” has been demonstrated. The application of this approach using systematic multi-track recordings on conventional liner ships is very promising, as it may open possibilities for widespread use of the methodology across the world.

scholarly journals Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

scholarly journals Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2810
Author(s):  
Krzysztof Naus ◽  
Piotr Szymak ◽  
Paweł Piskur ◽  
Maciej Niedziela ◽  
Aleksander Nowak
Keyword(s):  
Real Time ◽  
Spatial Orientation ◽  
Orientation Angle ◽  
Satellite System ◽  
Angle Measurement ◽  
Angle Correction ◽  
Lidar Measurements ◽  
Aerial Vehicle ◽  
Marine Applications ◽  
Global Navigation Satellite

Undoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical axis of the camera or LiDAR sensor. Usually, UAVs use a small and light Inertial Navigation System (INS) with an angle measurement error of up to 0.5∘ (RMSE). The methodology for spatial orientation angle correction presented in the article allows the reduction of this error even to the level of 0.01∘ (RMSE). It can be successfully used in coastal and port waters. To determine the corrections, only the Electronic Navigational Chart (ENC) and an image of the coastline are needed.

scholarly journals GNSS SATELLITE VISIBILITY ANALYSIS BASED ON 3D SPATIAL INFORMATION IN URBAN AREAS

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 123-128
Author(s):  
Y.-H. Lu ◽  
J.-Y. Han
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Spatial Information ◽  
Signal Transmission ◽  
Point Clouds ◽  
Satellite System ◽  
Topographic Effects ◽  
Analysis Technique ◽  
Satellite Visibility ◽  
Global Navigation Satellite

Abstract. Global Navigation Satellite System (GNSS) is a matured modern technique for spatial data acquisition. Its performance has a great correlation with GNSS receiver position. However, high-density building in urban areas causes signal obstructions and thus hinders GNSS’s serviceability. Consequently, GNSS positioning is weakened in urban areas, so deriving proper improvement resolutions is a necessity. Because topographic effects are considered the main factor that directly block signal transmission between satellites and receivers, this study integrated aerial borne LiDAR point clouds and a 2D building boundary map to provide reliable 3D spatial information to analyze topographic effects. Using such vector data not only reflected high-quality GNSS satellite visibility calculations, but also significantly reduced data amount and processing time. A signal obstruction analysis technique and optimized computational algorithm were also introduced. In conclusion, this paper proposes using superimposed column method to analyze GNSS receivers’ surrounding environments and thus improve GNSS satellite visibility predictions in an efficient and reliable manner.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals Monitoring and Computation of the Volumes of Stockpiles of Bulk Material by Means of UAV Photogrammetric Surveying

2019 ◽  
Vol 11 (12) ◽  
pp. 1471 ◽  
Author(s):  
Grazia Tucci ◽  
Antonio Gebbia ◽  
Alessandro Conti ◽  
Lidia Fiorini ◽  
Claudio Lubello
Keyword(s):  
Bulk Material ◽  
Laser Scanner ◽  
Ground Truth ◽  
Point Clouds ◽  
3D Models ◽  
Satellite System ◽  
3D Data ◽  
Current Survey ◽  
Close Range ◽  
Global Navigation Satellite

The monitoring and metric assessment of piles of natural or man-made materials plays a fundamental role in the production and management processes of multiple activities. Over time, the monitoring techniques have undergone an evolution linked to the progress of measure and data processing techniques; starting from classic topography to global navigation satellite system (GNSS) technologies up to the current survey systems like laser scanner and close-range photogrammetry. Last-generation 3D data management software allow for the processing of increasingly truer high-resolution 3D models. This study shows the results of a test for the monitoring and computing of stockpile volumes of material coming from the differentiated waste collection inserted in the recycling chain, performed by means of an unmanned aerial vehicle (UAV) photogrammetric survey and the generation of 3D models starting from point clouds. The test was carried out with two UAV flight sessions, with vertical and oblique camera configurations, and using a terrestrial laser scanner for measuring the ground control points and as ground truth for testing the two survey configurations. The computations of the volumes were carried out using two software and comparisons were made both with reference to the different survey configurations and to the computation software.

scholarly journals Processing Chain for Estimation of Tree Diameter from GNSS-IMU-Based Mobile Laser Scanning Data

2019 ◽  
Vol 11 (6) ◽  
pp. 615 ◽  
Author(s):  
Juraj Čerňava ◽  
Martin Mokroš ◽  
Ján Tuček ◽  
Michal Antal ◽  
Zuzana Slatkovská
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Point Clouds ◽  
Satellite System ◽  
Forest Road ◽  
Forest Mapping ◽  
Fitting Method ◽  
Progressive Technology ◽  
Global Navigation Satellite

Mobile laser scanning (MLS) is a progressive technology that has already demonstrated its ability to provide highly accurate measurements of road networks. Mobile innovation of the laser scanning has also found its use in forest mapping over the last decade. In most cases, existing methods for forest data acquisition using MLS result in misaligned scenes of the forest, scanned from different views appearing in one point cloud. These difficulties are caused mainly by forest canopy blocking the global navigation satellite system (GNSS) signal and limited access to the forest. In this study, we propose an approach to the processing of MLS data of forest scanned from different views with two mobile laser scanners under heavy canopy. Data from two scanners, as part of the mobile mapping system (MMS) Riegl VMX-250, were acquired by scanning from five parallel skid trails that are connected to the forest road. Misaligned scenes of the forest acquired from different views were successfully extracted from the raw MLS point cloud using GNSS time based clustering. At first, point clouds with correctly aligned sets of ground points were generated using this method. The loss of points after the clustering amounted to 33.48%. Extracted point clouds were then reduced to 1.15 m thick horizontal slices, and tree stems were detected. Point clusters from individual stems were grouped based on the diameter and mean GNSS time of the cluster acquisition. Horizontal overlap was calculated for the clusters from individual stems, and sufficiently overlapping clusters were aligned using the OPALS ICP module. An average misalignment of 7.2 mm was observed for the aligned point clusters. A 5-cm thick horizontal slice of the aligned point cloud was used for estimation of the stem diameter at breast height (DBH). DBH was estimated using a simple circle-fitting method with a root-mean-square error of 3.06 cm. The methods presented in this study have the potential to process MLS data acquired under heavy forest canopy with any commercial MMS.

scholarly journals The Katwijk beach planetary rover dataset

2017 ◽  
Vol 37 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Robert A Hewitt ◽  
Evangelos Boukas ◽  
Martin Azkarate ◽  
Marco Pagnamenta ◽  
Joshua A Marshall ◽  
...  
Keyword(s):  
Satellite System ◽  
Entire Area ◽  
Mapping Algorithms ◽  
Planetary Rover ◽  
Localization And Mapping ◽  
Stereo Cameras ◽  
Landing Sites ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Rock Size

This paper describes a dataset collected along a 1 km section of beach near Katwijk, The Netherlands, which was populated with a collection of artificial rocks of varying sizes to emulate known rock size densities at current and potential Mars landing sites. First, a fixed-wing unmanned aerial vehicle collected georeferenced images of the entire area. Then, the beach was traversed by a rocker-bogie-style rover equipped with a suite of sensors that are envisioned for use in future planetary rover missions. These sensors, configured so as to emulate the ExoMars rover, include stereo cameras, and time-of-flight and scanning light-detection-and-ranging sensors. This dataset will be of interest to researchers developing localization and mapping algorithms for vehicles traveling over natural and unstructured terrain in environments that do not have access to the global navigation satellite system, and where only previously taken satellite or aerial imagery is available.

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