scholarly journals Using Geomatic Techniques to Estimate Volume–Area Relationships of Watering Ponds

2021 ◽  
Vol 10 (8) ◽  
pp. 502
Author(s):  
Ubaldo Marín-Comitre ◽  
Álvaro Gómez-Gutiérrez ◽  
Francisco Lavado-Contador ◽  
Manuel Sánchez-Fernández ◽  
Alberto Alfonso-Torreño
Keyword(s):  
Storage Capacity ◽  
Laser Scanner ◽  
Satellite System ◽  
Volume Estimation ◽  
Quadratic Functions ◽  
Average Error ◽  
Power Relationship ◽  
Hydrological Simulation ◽  
Stereo Photogrammetry ◽  
Global Navigation Satellite

Watering ponds represent an important part of the hydrological resources in some water-limited environments. Knowledge about their storage capacity and geometrical characteristics is crucial for a better understanding and management of water resources in the context of climate change. In this study, the suitability of different geomatic approaches to model watering pond geometry and estimate pond-specific and generalized volume–area–height (V–A–h) relationships was tested. Terrestrial structure-from-motion and multi-view-stereo photogrammetry (SfM-MVS), terrestrial laser scanner (TLS), laser-imaging detection and ranging (LIDAR), and aerial SfM-MVS were tested for the emerged terrain, while the global navigation satellite system (GNSS) was used to survey the submerged terrain and to test the resulting digital elevation models (DEMs). The combined use of terrestrial SfM-MVS and GNSS produced accurate DEMs of the ponds that resulted in an average error of 1.19% in the maximum volume estimation, comparable to that obtained by the TLS+GNSS approach (3.27%). From these DEMs, power and quadratic functions were used to express pond-specific and generalized V–A–h relationships and checked for accuracy. The results revealed that quadratic functions fit the data particularly well (R2 ≥ 0.995 and NRMSE < 2.25%) and can therefore be reliably used as simple geometric models of watering ponds in hydrological simulation studies. Finally, a generalized V–A power relationship was obtained. This relationship may be a valuable tool to estimate the storage capacity of other watering ponds in comparable areas in a context of data scarcity.

scholarly journals Georeferencing of Laser Scanner-Based Kinematic Multi-Sensor Systems in the Context of Iterated Extended Kalman Filters Using Geometrical Constraints

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2280 ◽  
Author(s):  
Sören Vogel ◽  
Hamza Alkhatib ◽  
Johannes Bureick ◽  
Rozhin Moftizadeh ◽  
Ingo Neumann
Keyword(s):  
State Constraints ◽  
Laser Scanner ◽  
Measurement Data ◽  
Satellite System ◽  
Sensor Systems ◽  
Measurement Models ◽  
Non Linear ◽  
Geometrical Constraints ◽  
Global Navigation Satellite ◽  
The Impact

Georeferencing is an indispensable necessity regarding operating with kinematic multi-sensor systems (MSS) in various indoor and outdoor areas. Information from object space combined with various types of prior information (e.g., geometrical constraints) are beneficial especially in challenging environments where common solutions for pose estimation (e.g., global navigation satellite system or external tracking by a total station) are inapplicable, unreliable or inaccurate. Consequently, an iterated extended Kalman filter is used and a general georeferencing approach by means of recursive state estimation is introduced. This approach is open to several types of observation inputs and can deal with (non)linear systems and measurement models. The capability of using both explicit and implicit formulations of the relation between states and observations, and the consideration of (non)linear equality and inequality state constraints is a special feature. The framework presented is evaluated by an indoor kinematic MSS based on a terrestrial laser scanner. The focus here is on the impact of several different combinations of applied state constraints and the dependencies of two classes of inertial measurement units (IMU). The results presented are based on real measurement data combined with simulated IMU measurements.

scholarly journals RTK GNSS-Assisted Terrestrial SfM Photogrammetry without GCP: Application to Coastal Morphodynamics Monitoring

2020 ◽  
Vol 12 (11) ◽  
pp. 1889 ◽  
Author(s):  
Marion Jaud ◽  
Stéphane Bertin ◽  
Mickaël Beauverger ◽  
Emmanuel Augereau ◽  
Christophe Delacourt
Keyword(s):  
Standard Deviation ◽  
Low Cost ◽  
Laser Scanner ◽  
Satellite System ◽  
Mean Error ◽  
Ground Control Points ◽  
Participatory Science ◽  
Gnss Network ◽  
Global Navigation Satellite

The present article describes a new and efficient method of Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) assisted terrestrial Structure-from-Motion (SfM) photogrammetry without the need for Ground Control Points (GCPs). The system only requires a simple frame that mechanically connects a RTK GNSS antenna to the camera. The system is low cost, easy to transport, and offers high autonomy. Furthermore, not requiring GCPs enables saving time during the in situ acquisition and during data processing. The method is tested for coastal cliff monitoring, using both a Reflex camera and a Smartphone camera. The quality of the reconstructions is assessed by comparison to a synchronous Terrestrial Laser Scanner (TLS) acquisition. The results are highly satisfying with a mean error of 0.3 cm and a standard deviation of 4.7 cm obtained with the Nikon D800 Reflex camera and, respectively, a mean error of 0.2 cm and a standard deviation of 3.8 cm obtained with the Huawei Y5 Smartphone camera. This method will be particularly interesting when simplicity, portability, and autonomy are desirable. In the future, it would be transposable to participatory science programs, while using an open RTK GNSS network.

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 ANALYSIS OF THE VOLUME COMPARATION OF 3’S (TS, GNSS and TLS)

2019 ◽  
Vol 94 ◽  
pp. 01014
Author(s):  
Khomsin ◽  
Danar Guruh Pratomo ◽  
Ira Mutiara Anjasmara ◽  
Faizzuddin Ahmad
Keyword(s):  
3D Model ◽  
Laser Scanner ◽  
Satellite System ◽  
Navigation Satellite ◽  
Scanner Data ◽  
Total Station ◽  
Volume Calculation ◽  
Laser Scanners ◽  
Technological Developments ◽  
Global Navigation Satellite

Recently, technological developments in the field of surveys and mapping are growing very rapidly such as total station, navigation satellite (Global Navigation Satellite System), drones and laser scanners. One application of this technology is to measure a stockpile area quickly and accurately. This research will measure two stockpiles (coal warehouses) using total station (TS), GNSS and terrestrial laser scanner (TLS). This research will compare the results of volume calculations with the data generated by 3’S (TS, GNSS and TLS). Research is conducted at Coal Yard PT. Barkalin Surabaya in Benowo District, Surabaya, East City with geographically located at 112°39'11'’ E and 7°07’13‘' S. The first step is to make 3D model of Laser Scanner data by TLS Faro 3D 120 and to do regristrastion and filltering using Faro Scene. After that the data export to be 3D model from Faro Scene format to Recap 2016 (.rcp) to present and get coordinates. The next step is to compare the coordinates from TLS, TS and GNSS RTK. Finally, the accuracy of volume calculation from TS and GNSS RTK can be compared to TLS. The volume differences between TS and TLS data are -7.31 m3 (-0.45%) for the 1st location and -6.89 m3 (-0.24%) for the 2nd location. While the volume differences between GNSS RTK and TLS are -10.34 m3 (-0.63%) and -9.05 m3 (-0.31%) for the 1st location and the 2nd location respectively. Generally, the volume differences between TLS, TS and GNSS RTK are not significant. Therefore, 3’S can be used to measure a volume of stockpile.

scholarly journals Automatic Mapping of Center Line of Railway Tracks using Global Navigation Satellite System, Inertial Measurement Unit and Laser Scanner

2020 ◽  
Vol 12 (3) ◽  
pp. 411 ◽  
Author(s):  
Sangeetha Shankar ◽  
Michael Roth ◽  
Lucas Andreas Schubert ◽  
Judith Anne Verstegen
Keyword(s):  
Laser Scanner ◽  
Satellite System ◽  
Sensor Data ◽  
Measurement Unit ◽  
Center Line ◽  
Railway Tracks ◽  
Combination Of Methods ◽  
Global Navigation Satellite ◽  
Inertial Measurements ◽  
Gnss Data

Up-to-date geodatasets on railway infrastructure are valuable resources for the field of transportation. This paper investigates three methods for mapping the center lines of railway tracks using heterogeneous sensor data: (i) conditional selection of satellite navigation (GNSS) data, (ii) a combination of inertial measurements (IMU data) and GNSS data in a Kalman filtering and smoothing framework and (iii) extraction of center lines from laser scanner data. Several combinations of the methods are compared with a focus on mapping in tree-covered areas. The center lines of the railway tracks are extracted by applying these methods to a test dataset collected by a road-rail vehicle. The guard rails in the test area were also extracted during the center line detection process. The combination of methods (i) and (ii) gave the best result for the track on which the measurement vehicle had moved, mapping almost 100% of the track. The combination of methods (ii) and (iii) and the combination of all three methods gave the best result for the other parallel tracks, mapping between 25% and 80%. The mean perpendicular distance of the mapped center lines from the reference data was 1.49 meters.

scholarly journals MOVING OBJECT CLASSIFICATION USING MULTILAYER LASER SCANNING WITH SPACE SUBDIVISION FRAMEWORK

2020 ◽  
Vol V-4-2020 ◽  
pp. 103-108
Author(s):  
M. Nakagawa ◽  
M. Taguchi
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Object Classification ◽  
Point Clouds ◽  
Satellite System ◽  
Space Subdivision ◽  
Position Data ◽  
Global Navigation Satellite

Abstract. In this paper, we focus on the development of intelligent construction vehicles to improve the safety of workers in construction sites. Generally, global navigation satellite system positioning is utilized to obtain the position data of workers and construction vehicles. However, construction fields in urban areas have poor satellite positioning environments. Therefore, we have developed a 3D sensing unit mounted on a construction vehicle for worker position data acquisition. The unit mainly consists of a multilayer laser scanner. We propose a real-time object measurement, classification and tracking methodology with the multilayer laser scanner. We also propose a methodology to estimate and visualize object behaviors with a spatial model based on a space subdivision framework consisting of agents, activities, resources, and modifiers. We applied the space subdivision framework with a geofencing approach using real-time object classification and tracking results estimated from temporal point clouds. Our methodology was evaluated using temporal point clouds acquired from a construction vehicle in drilling works.

scholarly journals Direct Aerial Visual Geolocalization Using Deep Neural Networks

2021 ◽  
Vol 13 (19) ◽  
pp. 4017
Author(s):  
Winthrop Harvey ◽  
Chase Rainwater ◽  
Jackson Cothren
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Ground Level ◽  
Satellite System ◽  
Input Image ◽  
Average Error ◽  
Washington County ◽  
Localization Accuracy ◽  
Landscape Information ◽  
Global Navigation Satellite

Unmanned aerial vehicles (UAVs) must keep track of their location in order to maintain flight plans. Currently, this task is almost entirely performed by a combination of Inertial Measurement Units (IMUs) and reference to GNSS (Global Navigation Satellite System). Navigation by GNSS, however, is not always reliable, due to various causes both natural (reflection and blockage from objects, technical fault, inclement weather) and artificial (GPS spoofing and denial). In such GPS-denied situations, it is desirable to have additional methods for aerial geolocalization. One such method is visual geolocalization, where aircraft use their ground facing cameras to localize and navigate. The state of the art in many ground-level image processing tasks involve the use of Convolutional Neural Networks (CNNs). We present here a study of how effectively a modern CNN designed for visual classification can be applied to the problem of Absolute Visual Geolocalization (AVL, localization without a prior location estimate). An Xception based architecture is trained from scratch over a >1000 km2 section of Washington County, Arkansas to directly regress latitude and longitude from images from different orthorectified high-altitude survey flights. It achieves average localization accuracy on unseen image sets over the same region from different years and seasons with as low as 115 meters average error, which localizes to 0.004% of the training area, or about 8% of the width of the 1.5 × 1.5km input image. This demonstrates that CNNs are expressive enough to encode robust landscape information for geolocalization over large geographic areas. Furthermore, discussed are methods of providing uncertainty for CNN regression outputs, and future areas of potential improvement for use of deep neural networks in visual geolocalization.

scholarly journals Hybrid 3D Models: When Geomatics Innovations Meet Extensive Built Heritage Complexes

2019 ◽  
Vol 8 (3) ◽  
pp. 124 ◽  
Author(s):  
Filiberto Chiabrando ◽  
Giulia Sammartano ◽  
Antonia Spanò ◽  
Alessandra Spreafico
Keyword(s):  
Three Dimensional ◽  
Laser Scanner ◽  
3D Models ◽  
Satellite System ◽  
3D Data ◽  
Mapping System ◽  
Aerial Vehicle ◽  
Mobile Mapping System ◽  
Global Navigation Satellite ◽  
Topographic Surveys

This article proposes the use of a multiscale and multisensor approach to collect and model three-dimensional (3D) data concerning wide and complex areas to obtain a variety of metric information in the same 3D archive, which is based on a single coordinate system. The employment of these 3D georeferenced products is multifaceted and the fusion or integration among different sensors’ data, scales, and resolutions is promising, and it could be useful in the generation of a model that could be defined as a hybrid. The correct geometry, accuracy, radiometry, and weight of the data models are hereby evaluated when comparing integrated processes and results from Terrestrial Laser Scanner (TLS), Mobile Mapping System (MMS), Unmanned Aerial Vehicle (UAV), and terrestrial photogrammetry, while using Total Station (TS) and Global Navigation Satellite System (GNSS) for topographic surveys. The entire analysis underlines the potentiality of the integration and fusion of different solutions and it is a crucial part of the ‘Torino 1911’ project whose main purpose is mapping and virtually reconstructing the 1911 Great Exhibition settled in the Valentino Park in Turin (Italy).

scholarly journals TLS for Dynamic Measurement of the Elastic Line of Bridges

2020 ◽  
Vol 10 (3) ◽  
pp. 1182 ◽  
Author(s):  
Serena Artese ◽  
Raffaele Zinno
Keyword(s):  
Prestressed Concrete ◽  
Vertical Section ◽  
Laser Scanner ◽  
Metal Structure ◽  
Satellite System ◽  
Load Test ◽  
Elastic Line ◽  
Prestressed Concrete Bridge ◽  
Global Navigation Satellite ◽  
Line Scanner

The evaluation of the structural health of a bridge and the monitoring of its bearing capacity are performed by measuring different parameters. The most important ones are the displacements due to fixed or mobile loads, whose monitoring can be performed using several methods, both conventional and innovative. Terrestrial Laser Scanner (TLS) is effectively used to obtain the displacements of the decks for static loads, while for dynamic measurements, several punctual sensors are in general used. The proposed system uses a TLS, set as a line scanner and positioned under the bridge deck. The TLS acquires a vertical section of the intrados, or a line along a section to be monitored. The instantaneous deviations between the lines detected in dynamic conditions and the reference one acquired with the unloaded bridge, allow to extract the displacements and, consequently, the elastic curve. The synchronization of TLS acquisitions and load location, obtained from a Global Navigation Satellite System GNSS receiver or from a video, is an important feature of the method. Three tests were carried out on as many bridges. The first was performed during the maneuvers of a heavy truck traveling on a bridge characterized by a simply supported metal structure deck. The second concerned a prestressed concrete bridge with cantilever beams. The third concerned the pylon of a cantilever spar cable-stayed bridge during a load test. The results show high precision and confirm the usefulness of this method both for performing dynamic tests and for monitoring bridges.

scholarly journals Signal Extraction from GNSS Position Time Series Using Weighted Wavelet Analysis

2020 ◽  
Vol 12 (6) ◽  
pp. 992 ◽  
Author(s):  
Kunpu Ji ◽  
Yunzhong Shen ◽  
Fengwei Wang
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Satellite System ◽  
Signal Extraction ◽  
Average Error ◽  
North East ◽  
Observation Network ◽  
Position Time Series ◽  
Global Navigation Satellite ◽  
Gnss Position Time Series

The daily position time series derived by Global Navigation Satellite System (GNSS) contain nonlinear signals which are suitably extracted by using wavelet analysis. Considering formal errors are also provided in daily GNSS solutions, a weighted wavelet analysis is proposed in this contribution where the weight factors are constructed via the formal errors. The proposed approach is applied to process the position time series of 27 permanent stations from the Crustal Movement Observation Network of China (CMONOC), compared to traditional wavelet analysis. The results show that the proposed approach can extract more exact signals than traditional wavelet analysis, with the average error reductions are 13.24%, 13.53% and 9.35% in north, east and up coordinate components, respectively. The results from 500 simulations indicate that the signals extracted by proposed approach are closer to true signals than the traditional wavelet analysis.

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