GNSS-based operational monitoring devices for forest logging operation chains

The first results of a new approach for implementing operational monitoring tool to control the performance of forest mechanisation chains are proposed and discussed. The solution is based on Global Navigation Satellite System (GNSS) tools that are the core of a datalogging system that, in combination with a specific inference-engine, is able to analyse process times, work distances, forward speeds, vehicle tracking and number of working cycles in forest operations. As a consequence the operational monitoring control methods could provide an evaluation of the efficiency of the investigated forest operations. The study has monitored the performance of a tower yarder with crane and processor-head, during logging operations. The field surveys consisted on the installation of the GNSS device directly on the forest equipment for monitoring its movements. Simultaneously the field survey considered the integration of the GNSS information with a time study of work elements based on the continuous time methods supported by a time study board. Additionally, where possible, the onboard computer of the forest machine was also used in order to obtain additional information to be integrated to the GNSS data and the time study. All the recorded GNSS data integrated with the work elements study were thus post-processed through GIS analysis. The preliminary overview about the application of this approach on harvesting operations has permitted to assess a good feasibility of the use of GNSS in the relief of operative times in high mechanised forest chains. Results showed an easy and complete identification of the different operative cycles and elementary operations phases, with a maximum difference between the two methodologies of 10.32%. The use of GNSS installed on forest equipment, integrated with the inferenceengine and also with an interface for data communication or data storage, will permit an automatic or semi-automatic operational monitoring, improving the quantity of data and reducing the engagement of the surveyor.

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Study the Effect of Radio Interference of the EHV Transmission Line on GNSS Signals

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.805-806.851 ◽

2013 ◽

Vol 805-806 ◽

pp. 851-854

Author(s):

Zhi Ge Jia ◽

Zhao Sheng Nie ◽

Wei Wang ◽

Xiao Guan ◽

Di Jin Wang

Keyword(s):

Transmission Line ◽

Transmission Lines ◽

Internal Noise ◽

Field Testing ◽

Satellite System ◽

Field Analysis ◽

Radio Interference ◽

Gnss Receiver ◽

Global Navigation Satellite ◽

Gnss Data

This work describes the field testing process of Global Navigation Satellite System (GNSS) receiver under 220KV, 500KV UHV transmission line and standard calibration field. Analysis for GNSS data results shows that the radio interference generated by EHV transmission lines have no effect on GNSS receiver internal noise levels and valid GNSS observation rate. Within 50 meters of the EHV transmission lines, the multi-path effects (mp1 and mp2 value) significantly exceeded the normal range and becomes larger with the increase of the voltage .outside 50 meters of the EHV transmission line, the multi-path effects have almost no effect on the high-precision GNSS observations.

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Terrain changes from images acquired on opportunistic flights by SfM photogrammetry

The Cryosphere ◽

10.5194/tc-11-827-2017 ◽

2017 ◽

Vol 11 (2) ◽

pp. 827-840 ◽

Cited By ~ 12

Author(s):

Luc Girod ◽

Christopher Nuth ◽

Andreas Kääb ◽

Bernd Etzelmüller ◽

Jack Kohler

Keyword(s):

Low Cost ◽

Rapid Change ◽

Satellite System ◽

Light Transport ◽

Area Of Interest ◽

Accuracy And Precision ◽

Global Navigation Satellite ◽

The Cost ◽

Gnss Data

Abstract. Acquiring data to analyse change in topography is often a costly endeavour requiring either extensive, potentially risky, fieldwork and/or expensive equipment or commercial data. Bringing the cost down while keeping the precision and accuracy has been a focus in geoscience in recent years. Structure from motion (SfM) photogrammetric techniques are emerging as powerful tools for surveying, with modern algorithm and large computing power allowing for the production of accurate and detailed data from low-cost, informal surveys. The high spatial and temporal resolution permits the monitoring of geomorphological features undergoing relatively rapid change, such as glaciers, moraines, or landslides. We present a method that takes advantage of light-transport flights conducting other missions to opportunistically collect imagery for geomorphological analysis. We test and validate an approach in which we attach a consumer-grade camera and a simple code-based Global Navigation Satellite System (GNSS) receiver to a helicopter to collect data when the flight path covers an area of interest. Our method is based and builds upon Welty et al. (2013), showing the ability to link GNSS data to images without a complex physical or electronic link, even with imprecise camera clocks and irregular time lapses. As a proof of concept, we conducted two test surveys, in September 2014 and 2015, over the glacier Midtre Lovénbreen and its forefield, in northwestern Svalbard. We were able to derive elevation change estimates comparable to in situ mass balance stake measurements. The accuracy and precision of our DEMs allow detection and analysis of a number of processes in the proglacial area, including the presence of thermokarst and the evolution of water channels.

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Spaceborne GNSS-R Observation of Global Lake Level: First Results from the TechDemoSat-1 Mission

Remote Sensing ◽

10.3390/rs11121438 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1438 ◽

Cited By ~ 2

Author(s):

Liwen Xu ◽

Wei Wan ◽

Xiuwan Chen ◽

Siyu Zhu ◽

Baojian Liu ◽

...

Keyword(s):

Satellite System ◽

Temporal Variations ◽

Strong Correlations ◽

Lake Levels ◽

The Caspian Sea ◽

First Results ◽

The Uk ◽

Global Navigation Satellite ◽

Inland Water Bodies ◽

First Time

Spaceborne global navigation satellite system reflectometry (GNSS-R) data collected by the UK TechDemoSat-1 (TDS-1) satellite is applied to retrieve global lake levels for the first time. Lake levels of 351 global lakes (area greater than 500 km2 and elevation lower than 3000 m each) are estimated using TDS-1 Level 1b data over 2015–2017. Strong correlations (overall R2 greater than 0.95) are observed among lake levels derived from TDS-1 and other altimetry satellites such as CryoSat-2, Jason, and Envisat (the latter two are collected by Hydroweb), although with large root-mean-square error (RMSE) (tens of meters) mainly due to the fact that TDS-1 is not dedicated for altimetry measuring purpose. Examples of the Caspian Sea and the Poyang Lake show consistent spatial and temporal variations between TDS-1 and other data sources. The results in this paper provide supportive information for further application of GNSS-R constellations to measure altimetry of inland water bodies.

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

Remote Sensing ◽

10.3390/rs12030411 ◽

2020 ◽

Vol 12 (3) ◽

pp. 411 ◽

Cited By ~ 2

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.

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Integrated GNSS Attitude and Position Determination based on an Affine Constrained Model

Journal of Navigation ◽

10.1017/s0373463317000522 ◽

2017 ◽

Vol 71 (1) ◽

pp. 134-150

Author(s):

Haiying Liu ◽

Lei Xu ◽

Xiaolin Meng ◽

Xibei Chen ◽

Junyi Li

Keyword(s):

Attitude Determination ◽

Satellite System ◽

Determination Method ◽

Position Determination ◽

Static Data ◽

Constraint Information ◽

Constrained Model ◽

Global Navigation Satellite ◽

Constraint Model ◽

Gnss Data

Global Navigation Satellite System (GNSS) attitude determination and positioning play an important role in many navigation applications. However, the two GNSS-based problems are usually treated separately. This ignores the constraint information of the GNSS antenna array and the accuracy is limited. To improve the performance of navigation, an integrated attitude and position determination method based on an affine constraint model is presented. In the first part, the GNSS array model and affine constrained attitude determination method are compared with the unconstrained methods. Then the integrated attitude and position determination method is presented. The performance of the proposed method is tested with a series of static data and dynamic experimental GNSS data. The results show that the proposed method can improve the success rate of ambiguity resolution to further improve the accuracy of attitude determination and relative positioning compared to the unconstrained methods.

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Subsidence determination in the Central Valley, California

Reports on Geodesy and Geoinformatics ◽

10.2478/rgg-2018-0012 ◽

2018 ◽

Vol 106 (1) ◽

pp. 35-42 ◽

Cited By ~ 1

Author(s):

Marcelo Romero ◽

Mike Mustafa Berber

Keyword(s):

Central Valley ◽

Satellite System ◽

Geodetic Survey ◽

Reference Station ◽

National Geodetic Survey ◽

The North ◽

Elevation Changes ◽

System Data ◽

Global Navigation Satellite ◽

Gnss Data

Abstract Twenty four hour GNSS (Global Navigation Satellite System) data acquired monthly for 5 years from 8 CORS (Continuously Operating Reference Station) stations in Central Valley, California are processed and vertical velocities of the points are determined. To process GNSS data, online GNSS data processing service APPS (Automatic Precise Positioning Service) is used. GNSS data downloaded from NGS (National Geodetic Survey) CORS are analyzed and subsidence at these points is portrayed with graphics. It is revealed that elevation changes range from 5 mm uplift in the north to 163 mm subsidence in the southern part of the valley.

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An overview of methodologies for real-time detection, characterisation and tracking of traveling ionospheric disturbances developed in the TechTIDE project

Journal of Space Weather and Space Climate ◽

10.1051/swsc/2020043 ◽

2020 ◽

Vol 10 ◽

pp. 42

Author(s):

Anna Belehaki ◽

Ioanna Tsagouri ◽

David Altadill ◽

Estefania Blanch ◽

Claudia Borries ◽

...

Keyword(s):

Real Time ◽

Large Scale ◽

Tracking System ◽

Warning System ◽

Satellite System ◽

Ionospheric Disturbances ◽

Time Activity ◽

Travelling Ionospheric Disturbances ◽

Additional Information ◽

Global Navigation Satellite

The main objective of the TechTIDE project (warning and mitigation technologies for travelling ionospheric disturbances effects) is the development of an identification and tracking system for travelling ionospheric disturbances (TIDs) which will issue warnings of electron density perturbations over large world regions. The TechTIDE project has put in operation a real-time warning system that provides the results of complementary TID detection methodologies and many potential drivers to help users assess the risks and develop mitigation techniques tailored to their applications. The TechTIDE methodologies are able to detect in real time activity caused by both large-scale and medium-scale TIDs and characterize background conditions and external drivers, as an additional information required by the users to assess the criticality of the ongoing disturbances in real time. TechTIDE methodologies are based on the exploitation of data collected in real time from Digisondes, Global Navigation Satellite System (GNSS) receivers and Continuous Doppler Sounding System (CDSS) networks. The results are obtained and provided to users in real time. The paper presents the achievements of the project and discusses the challenges faced in the development of the final TechTIDE warning system.

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An improved pixel-based water vapor tomography model

Annales Geophysicae ◽

10.5194/angeo-37-89-2019 ◽

2019 ◽

Vol 37 (1) ◽

pp. 89-100

Author(s):

Yibin Yao ◽

Linyang Xin ◽

Qingzhi Zhao

Keyword(s):

Water Vapor ◽

Three Dimensional ◽

Satellite System ◽

Reference Station ◽

Weather Forecasts ◽

Satellite Positioning ◽

Optimal Polynomial ◽

Improved Model ◽

Global Navigation Satellite ◽

Gnss Data

Abstract. As an innovative use of Global Navigation Satellite System (GNSS), the GNSS water vapor tomography technique shows great potential in monitoring three-dimensional water vapor variation. Most of the previous studies employ the pixel-based method, i.e., dividing the troposphere space into finite voxels and considering water vapor in each voxel as constant. However, this method cannot reflect the variations in voxels and breaks the continuity of the troposphere. Moreover, in the pixel-based method, each voxel needs a parameter to represent the water vapor density, which means that huge numbers of parameters are needed to represent the water vapor field when the interested area is large and/or the expected resolution is high. In order to overcome the abovementioned problems, in this study, we propose an improved pixel-based water vapor tomography model, which uses layered optimal polynomial functions obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) by adaptive training for water vapor retrieval. Tomography experiments were carried out using the GNSS data collected from the Hong Kong Satellite Positioning Reference Station Network (SatRef) from 25 March to 25 April 2014 under different scenarios. The tomographic results are compared to the ECMWF data and validated by the radiosonde. Results show that the new model outperforms the traditional one by reducing the root-mean-square error (RMSE), and this improvement is more pronounced, at 5.88 % in voxels without the penetration of GNSS rays. The improved model also has advantages in more convenient expression.

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RobHortic: A Field Robot to Detect Pests and Diseases in Horticultural Crops by Proximal Sensing

Agriculture ◽

10.3390/agriculture10070276 ◽

2020 ◽

Vol 10 (7) ◽

pp. 276 ◽

Cited By ~ 1

Author(s):

Sergio Cubero ◽

Ester Marco-Noales ◽

Nuria Aleixos ◽

Silvia Barbé ◽

Jose Blasco

Keyword(s):

Field Tests ◽

Satellite System ◽

Negative Influence ◽

Proximal Sensing ◽

Horticultural Crops ◽

Pests And Diseases ◽

Candidatus Liberibacter ◽

Global Navigation Satellite ◽

Gnss Data ◽

Field Robot

RobHortic is a remote-controlled field robot that has been developed for inspecting the presence of pests and diseases in horticultural crops using proximal sensing. The robot is equipped with colour, multispectral, and hyperspectral (400–1000 nm) cameras, located looking at the ground (towards the plants). To prevent the negative influence of direct sunlight, the scene was illuminated by four halogen lamps and protected from natural light using a tarp. A GNSS (Global Navigation Satellite System) was used to geolocate the images of the field. All sensors were connected to an on-board industrial computer. The software developed specifically for this application captured the signal from an encoder, which was connected to the motor, to synchronise the acquisition of the images with the advance of the robot. Upon receiving the signal, the cameras are triggered, and the captured images are stored along with the GNSS data. The robot has been developed and tested over three campaigns in carrot fields for the detection of plants infected with ‘Candidatus Liberibacter solanacearum’. The first two years were spent creating and tuning the robot and sensors, and data capture and geolocation were tested. In the third year, tests were carried out to detect asymptomatic infected plants. As a reference, plants were analysed by molecular analysis using a specific real-time Polymerase Chain Reaction (PCR), to determine the presence of the target bacterium and compare the results with the data obtained by the robot. Both laboratory and field tests were done. The highest match was obtained using Partial Least Squares-Discriminant Analysis PLS-DA, with a 66.4% detection rate for images obtained in the laboratory and 59.8% for images obtained in the field.

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Algorithm Research Using GNSS-TEC Data to Calibrate TEC Calculated by the IRI-2016 Model over China

Remote Sensing ◽

10.3390/rs13194002 ◽

2021 ◽

Vol 13 (19) ◽

pp. 4002

Author(s):

Wen Zhang ◽

Xingliang Huo ◽

Yunbin Yuan ◽

Zishen Li ◽

Ningbo Wang

Keyword(s):

Mean Absolute Error ◽

Absolute Error ◽

Satellite System ◽

Electron Content ◽

Iri Model ◽

Ionospheric Electron Content ◽

The Mean ◽

Spatial Grid ◽

Global Navigation Satellite ◽

Gnss Data

The International Reference Ionosphere (IRI) is an empirical model widely used to describe ionospheric characteristics. In the previous research, high-precision total ionospheric electron content (TEC) data derived from global navigation satellite system (GNSS) data were used to adjust the ionospheric global index IG12 used as a driving parameter in the standard IRI model; thus, the errors between IRI-TEC and GNSS-TEC were minimized, and IRI-TEC was calibrated by modifying IRI with the updated IG12 index (IG-up). This paper investigates various interpolation strategies for IG-up values calculated from GNSS reference stations and the calibrated TEC accuracy achieved using the modified IRI-2016 model with the interpolated IG-up values as driving parameters. Experimental results from 2015 and 2019 show that interpolating IG-up with a 2.5° × 5° spatial grid and a 1-h time resolution drives IRI-2016 to generate ionospheric TEC values consistent with GNSS-TEC. For 2015 and 2019, the mean absolute error (MAE) of the modified IRI-TEC is improved by 78.57% and 77.42%, respectively, and the root mean square error (RMSE) is improved by 78.79% and 77.14%, respectively. The corresponding correlations of the linear regression between GNSS-TEC and the modified IRI-TEC are 0.986 and 0.966, more than 0.2 higher than with the standard IRI-TEC.

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