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GNSS CORS Application

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 13214

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Prof. Dr. Gino Dardanelli

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Guest Editor

Department of Engineering, Università degli Studi di Palermo, 90100 Palermo, Italy
Interests: Galileo; GLONASS; GPS; GNSS; CORS; remote sensing; geomatics; dam displacements
Special Issues, Collections and Topics in MDPI journals

Dr. Mariusz Specht

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Guest Editor

Department of Transport and Logistics, Gdynia Maritime University, Morska 81-87, 81-225 Gdynia, Poland
Interests: global navigation satellite systems; civil engineering; geomatics; navigation; hydrography; mapping; earth observation; geospatial science; geoinformation; spatial analysis; geodesy; applied mathematics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Global Navigation Satellite System (GNSS) revolution has made it easier for scientists all over the world to construct infrastructure suitable for wide-ranging Earth monitoring investigations. Currently, there are several fully operational satellite navigation systems, such as the Chinese BeiDou Navigation Satellite System (BDS, http://en.beidou.gov.cn/), the European Galileo (https://www.gsc-europa.eu/system-service-status/constellation-information), the Russian Glonass (https://www.glonass-iac.ru/en/GLONASS/) and the American Navstar GPS (https://www.gps.gov/). Many other GNSS systems will be available in the next few years, such as those defined as Regional Navigation Satellite Systems (RNSS) including the Indian Regional Navigation Satellite System IRNSS/NavIC (https://www.isro.gov.in/irnss-programme) or Japanese Quasi‑Zenith Satellite System (QZSS, https://qzss.go.jp/en/) and Regional South Korean Positioning System (KPS, https://www.gpsworld.com/korea-will-launch-its-own-satellite-positioning-system/). This represents a massive potential for the scientific community to develop studies that will certainly improve the lives of the world's population.

GNNS applications have historically been found in positioning for the analysis of three-dimensional (3D) positioning by using Continuously Operating Reference Stations (CORS). The scientific and technical applications developed in different parts of the continents involved CORS networks for evaluating 3D positioning in real time (Network Real-Time Kinematic, NRTK) and in post-process analyses. Indeed, the innovative framework of GNSS CORS networks allowed receiving the most reliable differential corrections over an area by using the Virtual Reference Station (VRS), the Flächen-Korrektur-Parameter (FKP) or Multi Reference Station (MRS) approaches. Many studies were also carried out by applying the multi-GNSS Precise Point Positioning (PPP) technique. As a consequence, the use of CORS networks allowed increasing the distances between reference stations, contemporary reducing the total amount of CORS distributed over the same area. Moreover, many advantages have been observed in terms of economic impact and network management. The scientific implementations using CORS networks were subjects of focus in the analysis and correction of ionospheric and tropospheric errors by using Zenith Tropospheric Delay (ZTD) estimations. Many analyses have been developed to evaluate the use of a global reference system with respect to its inconstancy, as well as geodynamic studies over seismic areas. Nowadays, the GNSS CORS networks are globally and widely distributed, and they are classified as global, regional, national and local networks based on the covered region.

The aim of this Special Issue is to present the latest state-of-the-art findings examine GNSS CORS applications. Contributions that are solicited include, but are not limited to, the following topics: GNSS, CORS, NRTK, PPP, Geodesy, Geohazards, GNSS volcanology and crustal deformation.

Dr. Gino Dardanelli
Dr. Mariusz Specht
Guest Editors

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Keywords

GNSS
CORS
NRTK
PPP
geodesy
geohazards
crustal deformation
volcanology
UAV

Published Papers (8 papers)

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Research

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22 pages, 8969 KiB

Open AccessArticle

Research on Reliable Long-Baseline NRTK Positioning Method Considering Ionospheric Residual Interpolation Uncertainty

by Hao Liu, Wang Gao, Weiwei Miao, Shuguo Pan, Xiaolin Meng and Longlei Qiao

Remote Sens. 2023, 15(22), 5353; https://doi.org/10.3390/rs15225353 - 14 Nov 2023

Viewed by 673

Abstract

In the past few decades, network real-time kinematic (NRTK) positioning technology has developed rapidly. Generally, in the continuously operating reference stations (CORS) network, within a moderate baseline length, e.g., 80–100 km, atmospheric delay can be effectively processed through regional modeling and, thus, can support almost instantaneous centimeter-level NRTK positioning. However, in long-baseline CORS networks, especially during the active period of the ionosphere, ionospheric delays cannot be fully eliminated through modeling, leading to decreased NRTK positioning accuracy. To address this issue, this study proposes a long-baseline NRTK positioning method considering ionospheric residual interpolation uncertainty (IRIU). The method utilizes the ionospheric residual interpolation standard deviation (IRISTD) calculated during atmospheric delay modeling, then fits an IRISTD-related stochastic model through the fitting of the absolute values of the ionospheric delay modeling residuals and IRISTD. Finally, based on the ionosphere-weighted model, the IRISTD processed by the stochastic model is used to constrain the ionospheric pseudo-observations. This method achieves good comprehensive performance in handling ionospheric delay and model strength, and the advantage is validated through experiments using CORS data with baseline lengths ranging from 54 km to 106 km in western China and from 84 km to 180 km in AUSCORS data. Quantitative results demonstrate that, across the three sets of experiments, the proposed ionosphere-weighted model achieves an average increase in the fixed rate of 16.9% compared to the ionosphere-fixed model and 25.6% compared to the ionosphere-float model. In terms of positioning accuracy, the proposed model yields average improvements of 67.4%, 76.4%, and 66.0% in the N/E/U directions, respectively, compared to the ionosphere-fixed model, and average improvements of 21.0%, 32.0%, and 24.4%, respectively, compared to the ionosphere-float model. Overall, the proposed method can achieve better NRTK positioning performance in situations where ionospheric delay modeling is inaccurate, such as long baselines and ionospheric activity. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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19 pages, 8891 KiB

Open AccessArticle

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis

by Zhen Li, Tieding Lu, Kegen Yu and Jie Wang

Remote Sens. 2023, 15(18), 4374; https://doi.org/10.3390/rs15184374 - 05 Sep 2023

Cited by 1 | Viewed by 1198

Abstract

The global navigation satellite system (GNSS) position time series provides essential data for geodynamic and geophysical studies. Interpolation of the GNSS position time series is necessary because missing data will produce inaccurate conclusions made from the studies. The spatio-temporal correlations between GNSS reference stations cannot be considered when using traditional interpolation methods. This paper examines the use of machine learning models to reflect the spatio-temporal correlation among GNSS reference stations. To form the machine learning problem, the time series to be interpolated are treated as output values, and the time series from the remaining GNSS reference stations are used as input data. Specifically, three machine learning algorithms (i.e., the gradient boosting decision tree (GBDT), eXtreme gradient boosting (XGBoost), and random forest (RF)) are utilized to perform interpolation with the time series data from five GNSS reference stations in North China. The results of the interpolation of discrete points indicate that the three machine learning models achieve similar interpolation precision in the Up component, which is 45% better than the traditional cubic spline interpolation precision. The results of the interpolation of continuous missing data indicate that seasonal oscillations caused by thermal expansion effects in summer significantly affect the interpolation precision. Meanwhile, we improved the interpolation precision of the three models by adding data from five stations which have high correlation with the initial five GNSS reference stations. The interpolated time series for the North, East, and Up (NEU) are examined by principal component analysis (PCA), and the results show that the GBDT and RF models perform interpolation better than the XGBoost model. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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18 pages, 4995 KiB

Open AccessArticle

The Seasonal Variations Analysis of Permanent GNSS Station Time Series in the Central-East of Europe

by Stepan Savchuk, Sofiia Doskich, Paweł Gołda and Adam Rurak

Remote Sens. 2023, 15(15), 3858; https://doi.org/10.3390/rs15153858 - 03 Aug 2023

Cited by 1 | Viewed by 985

Abstract

Observations from permanent GNSS stations are actively used for the research and monitoring of geodynamic processes. Today, with the use of modern scientific programs and IGS products, it is possible to determine GNSS station coordinates and velocities at the level of a few millimeters. However, the scientific community constantly faces the question of increasing the accuracy of coordinate definitions to obtain more reliable data in the study of geodynamic phenomena. One of the main sources of errors is systematic measurement errors. To date, the procedure for their removal is still incomplete and imperfect. Also, during the processing of long-term GNSS measurements, it was found that the coordinate time series, after the removal of trend effects, are also characterized by seasonal variations, mainly of annual and semi-annual periods. We estimated the daily coordinate time series of 10 permanent GNSS stations in the central-eastern part of Europe from 2001 to 2019 and calculated the seasonal variation coefficients for these stations. The average value of the coefficients for the annual cycle for the N, E, and H components is −0.7, −0.2, and −0.7 mm, and for the semi-annual cycle the average value is 0.3, 0.4, and −0.5 mm. The obtained coefficients are less than 1 mm, which is why it can be argued that there is no seasonal component in the coordinate time series or that it is so small that it is a problematic task to calculate it. This practical absence of a seasonal component in long-term time series of GNSS coordinates, in our opinion, is partly compensated by the use of modern models of mapping functions (such as VMF3) for zenith tropospheric delays instead of the empirical GMF. To test the obtained results, we calculated the coefficients of seasonal variations for the sub-network of GNSS stations included in the category of the best EPN stations—C0 and C1. The values of the coefficients for the stations of this network are also less than 1 mm, which confirms the previous statement about the absence of a seasonal component in the long-term time series of coordinates. We also checked the presence of seasonal changes in the time series using the well-known decomposition procedure, which showed that the seasonal component is not observed because the content does not exceed 10% for additive decomposition and 20% for multiplicative decomposition. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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19 pages, 8883 KiB

Open AccessArticle

Method of Development of a New Regional Ionosphere Model (RIM) to Improve Static Single-Frequency Precise Point Positioning (SF-PPP) for Egypt Using Bernese GNSS Software

by Ashraf Abdallah, Tarek Agag and Volker Schwieger

Remote Sens. 2023, 15(12), 3147; https://doi.org/10.3390/rs15123147 - 16 Jun 2023

Cited by 1 | Viewed by 1429

Abstract

Due to the lack of coverage of IGS in Africa, especially over North Africa, and the construction revolution of infrastructure in Egypt, a geodetic CORS stations network was established in 2012. These CORS stations are operated by the Egyptian Surveying Authority (Egy. SA) and cover the whole of Egypt. The paper presents a fully developed regional ionosphere model (RIM) depending on the Egyptian CORS stations. The new model and the PPP solution were obtained using Bernese GNSS V. 5.2 software. An observation data series of eight days (DOY 201–208)/2019 was used in this study. Eighteen stations were used to develop the RIM model for each day; fifteen stations were used to validate the new RIM model. A static SF-PPP solution was obtained using the CODE-GIM and RIM models. Comparing the outcomes to the reference network solution, based on the recently developed RIM model, the solution showed a mean error of 0.06 m in the East direction, 0.13 m in the North direction, and 0.21 m in the height direction. In the East, North, and height directions, this solution improves the SF-PPP result achieved by the Global Ionosphere Maps (CODE-GIM) model by 60%, 68%, and 77%, respectively. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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16 pages, 2485 KiB

Open AccessArticle

Assessment of the Steering Precision of a UAV along the Flight Profiles Using a GNSS RTK Receiver

by Oktawia Lewicka, Mariusz Specht and Cezary Specht

Remote Sens. 2022, 14(23), 6127; https://doi.org/10.3390/rs14236127 - 02 Dec 2022

Cited by 13 | Viewed by 1721

Abstract

Photogrammetric surveys are increasingly being carried out using Unmanned Aerial Vehicles (UAV). Steering drones along the flight profiles is one of the main factors that determines the quality of the compiled photogrammetric products. The aim of this article is to present a methodology for performing and processing measurements, which are used in order to determine the accuracy of steering any drone along flight profiles. The study used a drone equipped with a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) receiver. The measurements were performed on two routes which comprised parallel profiles distant from each other by 10 m and 20 m. The study was conducted under favourable meteorological conditions (windless and sunny weather) at three speeds (10 km/h, 20 km/h and 30 km/h). The cross track error (XTE), which is the distance between a UAV’s position and the flight profile, calculated transversely to the course, was adopted as the accuracy measure of steering a UAV along the flight profiles. Based on the results obtained, it must be concluded that the values of XTE measures for two representative routes are very similar and are not determined by the flight speed. The XTE68 measure (p = 0.68) ranged from 0.39 m to 1.00 m, while the XTE95 measure (p = 0.95) ranged from 0.60 m to 1.22 m. Moreover, analyses demonstrated that the statistical distribution of the XTE measure was most similar to the gamma and Weibull (3P) distributions. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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21 pages, 6290 KiB

Open AccessArticle

On the Accuracy of Cadastral Marks: Statistical Analyses to Assess the Congruence among GNSS-Based Positioning and Official Maps

by Gino Dardanelli and Antonino Maltese

Remote Sens. 2022, 14(16), 4086; https://doi.org/10.3390/rs14164086 - 21 Aug 2022

Cited by 4 | Viewed by 1697

Abstract

Cadastral marks constitute a dense source of information for topographical surveys required to update cadastral maps. Historically, in Italy, cadastral marks have been the cartographic network for the implementation of mapping updates. Different sources of cadastral marks can be used by cadastral surveyors. In recent years, the cadastre is moving toward a digital world, and with the advancement of surveying technology, GNSS CORS technology has emerged in the positioning of cadastral marks. An analysis of congruence among cadastral marks using GNSS CORS and official maps is missing. Thus, this work aims to analyze the positional accuracy of some cadastral marks, located in Palermo, Italy, with regard to the official maps produced by the cadastral bureau, the local cartography, and Google Earth maps. A survey of 60 cadastral marks was carried out by conventional GNSS NRTK procedures, with the lateral offset method due to their materialization (mostly building edges), which is not always directly detectable. The cadastral marks’ positioning was obtained from different maps: cadastral maps and related monographic files, numerical technical maps, and Google Earth maps, to check their coordinate congruence. A statistical approach was performed to check whether the distribution frequencies of the coordinate’s differences belonged to the bivariate normal distribution for the planimetric coordinates and the univariate normal distribution for the altimetric component. The results show that the hypothesis of a normal distribution is confirmed in most of the pairs, and specifically, most of the analyses indicate that the highest congruencies seem to characterize the coordinates determined by using the GNSS and with those that can be deduced by the numerical technical maps. The results obtained experimentally show centimetric accuracies obtained by the GNSS NRTK survey, in both the planimetric and altimetric components, while the accuracies obtained from the georeferencing of the cadastral maps show differences in the order of 0.4–0.8 m. Meanwhile, the differences resulting from comparing the technical cartography produced by the local authority and Google Earth maps show greater criticalities, with a metric order of magnitude. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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Review

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23 pages, 5838 KiB

Open AccessReview

A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy)

by Claudia Pipitone, Antonino Maltese, Mauro Lo Brutto and Gino Dardanelli

Remote Sens. 2023, 15(22), 5343; https://doi.org/10.3390/rs15225343 - 13 Nov 2023

Viewed by 1536

Abstract

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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23 pages, 2191 KiB

Open AccessReview

Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms

by Oktawia Lewicka, Mariusz Specht, Andrzej Stateczny, Cezary Specht, Gino Dardanelli, David Brčić, Bartosz Szostak, Armin Halicki, Marcin Stateczny and Szymon Widźgowski

Remote Sens. 2022, 14(16), 4075; https://doi.org/10.3390/rs14164075 - 20 Aug 2022

Cited by 15 | Viewed by 2626

Abstract

Changes in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). As part of this model, three technology components will be created: a hydroacoustic and optoelectronic data integration component proposed by Dąbrowski et al., a radiometric depth determination component based on optoelectronic data using the Support Vector Regression (SVR) method, and a coastline extraction component proposed by Xu et al. Thanks to them, it will be possible to cover the entire area with measurements in the coastal zone, in particular between the shallow waterbody coastline and the min. isobath recorded by the echo sounder (the area is lacking actual measurement data). Multisensor data fusion obtained using Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), Light Detection And Ranging (LiDAR), Real Time Kinematic (RTK), UAV, and USV will allow to meet the requirements provided for the International Hydrographic Organization (IHO) Special Order (horizontal position error ≤ 2 m (p = 0.95), vertical position error ≤ 0.25 m (p = 0.95)). To this end, bathymetric and photogrammetric measurements shall be carried out under appropriate conditions. The water transparency in the tested waterbody should be at least 2 m. Hydrographic surveys shall be performed in windless weather and the water level is 0 in the Douglas sea scale (no waves or sea currents). However, the mission with the use of an UAV should take place in appropriate meteorological conditions, i.e., no precipitation, windless weather (wind speed not exceeding 6–7 m/s), sunny day. Full article

(This article belongs to the Special Issue GNSS CORS Application)

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