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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 41919

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Special Issue Editors

Dr. Jean-Paul Boy

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EOST/IPGS (UMR 7516 CNRS – Université de Strasbourg), 5 Rue René Descartes, 67084 Strasbourg, CEDEX, France
Interests: geodesy; gravimetry; time-variable gravity; GNSS; loading modeling

Prof. Dr. Umberto Riccardi

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Dipartimento di Scienze della Terra, dell'Ambiente e delle Risorse (DiSTAR) Università "Federico II" di Napoli, 80126 Naples, Italy
Interests: geodesy; time-lapse gravimetry; Earth tides; GNSS; ground deformation monitoring; GNSS tropospheric delay; space geodesy
Special Issues, Collections and Topics in MDPI journals

Dr. Umberto Tammaro

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Istituto Nazionale di Geofisica e Vulcanologia, Sezione OV, 80125 Napoli, Italy
Interests: GNSS; ground deformation monitoring and geodetic techniques; modeling and numerical analysis of transport phenomena; GNSS meteorology for meteorological studies

Special Issue Information

Dear Colleagues,

The development of global navigation satellite systems (GNSS) has revolutionized not only geodesy but also geosciences. Nowadays, GNSS is widely used for various forms of geodynamics research, such as plate tectonics, earthquake mechanics, volcano monitoring, surface loading, and glacial isostatic adjustment. GNSS is an ideal tool for these studies because it can remotely and continuously provide 3D surface positions with millimetric precision at a relatively inexpensive cost. Currently, GNSS observations are widely used for the retrieval of precipitable water vapor (PWV) for the benefit of weather forecasters and numerical weather prediction. The contributions extend from application to the whole atmosphere, through the radio-occultation technique, down to the scale of the retrieval of soil moisture through GNSS reflectometry.

This Special Issue welcomes articles presenting innovative research or case studies dealing with application of GNSS and integration with other space and terrestrial geodetic techniques, which may include (but are not limited to) the following topics:

Plate tectonics and seismic cycle;
Volcano, earthquake, and rockslide monitoring and forecasting;
Loading phenomena due to past and present mass variations in the Earth’s ice sheets (GIA), continental water balance, and the associated sea level changes;
GNSS meteorology, ionosphere sounding, radio occultation, and reflectometry.

Dr. Jean-Paul Boy
Prof. Dr. Umberto Riccardi
Dr. Umberto Tammaro
Guest Editors

Manuscript Submission Information

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Keywords

GNSS
Plate tectonics
Loading deformation
Environmental changes
Atmosphere sounding

Published Papers (13 papers)

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23 pages, 4826 KiB

Open AccessArticle

Analysis of GNSS Displacements in Europe and Their Comparison with Hydrological Loading Models

by Alexandre Michel, Alvaro Santamaría-Gómez, Jean-Paul Boy, Félix Perosanz and Sylvain Loyer

Remote Sens. 2021, 13(22), 4523; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13224523 - 10 Nov 2021

Cited by 15 | Viewed by 2387

Abstract

Thanks to the increasing number of permanent GNSS stations in Europe and their long records, we computed position solutions for more than 1000 stations over the last two decades using the REPRO3 orbit and clock products from the IGS CNES-CLS (GRGS) Analysis Center. The velocities, which are mainly due to tectonics and glacial isostatic adjustment (GIA), and the annual solar cycle have been estimated using weighted least squares. The interannual variations have been accounted for in the stochastic model or in the deterministic model. We demonstrated that the velocity and annual cycle, in addition to their uncertainties, depend on the estimation method we used and that the estimation of GPS draconitic oscillations minimises biases in the estimation of annual solar cycle displacements. The annual solar cycle extracted from GPS has been compared with that from loading estimates of several hydrological models. If the annual amplitudes between GPS and hydrological models match, the phases of the loading models were typically in advance of about 1 month compared to GPS. Predictions of displacements modelled from GRACE observations did not show this phase shift. We also found important discrepancies at the interannual frequency band between GNSS, loading estimates derived from GRACE, and hydrological models using principal component analysis (PCA) decomposition. These discrepancies revealed that GNSS position variations in the interannual band cannot be systematically interpreted as a geophysical signal and should instead be interpreted in terms of autocorrelated noise. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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27 pages, 16812 KiB

Open AccessArticle

Studying a Subsiding Urbanized Area from a Multidisciplinary Perspective: The Inner Sector of the Sarno Plain (Southern Apennines, Italy)

by Ettore Valente, Vincenzo Allocca, Umberto Riccardi, Giovanni Camanni and Diego Di Martire

Remote Sens. 2021, 13(16), 3323; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13163323 - 22 Aug 2021

Cited by 3 | Viewed by 2524

Abstract

Defining the origin of ground deformation, which can be a very challenging task, may be approached through several investigative techniques. Ground deformation can originate in response to both natural (e.g., tectonics) and anthropic (e.g., groundwater pumping) contributions. These may either act simultaneously or be somewhat correlated in space and time. For example, the location of structurally controlled basins may be the locus of enhanced human-induced subsidence. In this paper, we investigate the natural and anthropic contributions to ground deformation in the urbanized area of the inner Sarno plain, in the Southern Apennines. We used a multidisciplinary approach based on the collection and analysis of a combination of geomorphological, stratigraphical, structural, hydrogeological, GPS, and DInSAR datasets. Geomorphological, stratigraphical, and structural data suggested the occurrence of a graben-like depocenter, the Sarno basin, bounded by faults with evidence of activity in the last 39 ka. Geodetic data indicated that the Sarno basin also experienced ground deformation (mostly subsidence) in the last 30 years, with a possible anthropogenic contribution due to groundwater pumping. Hydrogeological data suggested that a significant portion of the subsidence detected by geodetic data can be ascribed to groundwater pumping from the alluvial plain aquifer, rather than to a re-activation of faults in the last 30 years. Our interpretation suggested that a positive feedback exists between fault activity and the location of area affected by human-induced subsidence. In fact, fault activity caused the accumulation of poorly consolidated deposits within the Sarno basin, which enhanced groundwater-induced subsidence. The multidisciplinary approach used here was proven to be successful within the study area and could therefore be an effective tool for investigating ground deformation in other urbanized areas worldwide. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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29 pages, 22700 KiB

Open AccessArticle

Improved Hydrological Loading Models in South America: Analysis of GPS Displacements Using M-SSA

by Joëlle Nicolas, Jérôme Verdun, Jean-Paul Boy, Louis Bonhomme, Ayoub Asri, Adélie Corbeau, Antoine Berthier, Frédéric Durand and Peter Clarke

Remote Sens. 2021, 13(9), 1605; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13091605 - 21 Apr 2021

Cited by 9 | Viewed by 2138

Abstract

Environmental loading, in particular from continental water storage changes, induces geodetic station displacements up to several centimeters for the vertical components. We investigate surface deformation due to loading processes in South America using a set of 247 permanent GPS (Global Positioning System) stations for the 2003–2016 period and compare them to loading estimates from global circulation models. Unfortunately, some of the hydrological components, and in particular surface waters, may be missing in hydrological models. This is especially an issue in South America where almost half of the seasonal water storage variations are due to surface water changes, e.g., rivers and floodplains. We derive river storage variations by rerouting runoffs of global hydrology models, allowing a better agreement with the mass variations observed from GRACE (Gravity Recovery and Climate Experiment) mission. We extract coherent seasonal GPS displacements using Multichannel Singular Spectrum Analysis (M-SSA) and show that modeling the river storage induced loading effects significantly improve the agreement between observed vertical and horizontal displacements and loading models. Such an agreement has been markedly achieved in the Amazon basin. Whilst the initial models only explained half of the amplitude of GPS, the new ones compensate for these gaps and remain consistent with GRACE. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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23 pages, 44057 KiB

Open AccessArticle

Interannual Variability of GPS Heights and Environmental Parameters over Europe and the Mediterranean Area

by Letizia Elia, Susanna Zerbini and Fabio Raicich

Remote Sens. 2021, 13(8), 1554; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13081554 - 16 Apr 2021

Cited by 2 | Viewed by 2259

Abstract

Vertical deformations of the Earth’s surface result from a host of geophysical and geological processes. Identification and assessment of the induced signals is key to addressing outstanding scientific questions, such as those related to the role played by the changing climate on height variations. This study, focused on the European and Mediterranean area, analyzed the GPS height time series of 114 well-distributed stations with the aim of identifying spatially coherent signals likely related to variations of environmental parameters, such as atmospheric surface pressure (SP) and terrestrial water storage (TWS). Linear trends and seasonality were removed from all the time series before applying the principal component analysis (PCA) to identify the main patterns of the space/time interannual variability. Coherent height variations on timescales of about 5 and 10 years were identified by the first and second mode, respectively. They were explained by invoking loading of the crust. Single-value decomposition (SVD) was used to study the coupled interannual space/time variability between the variable pairs GPS height–SP and GPS height–TWS. A decadal timescale was identified that related height and TWS variations. Features common to the height series and to those of a few climate indices—namely, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI)—were also investigated. We found significant correlations only with the MEI. The first height PCA mode of variability, showing a nearly 5-year fluctuation, was anticorrelated (−0.23) with MEI. The second mode, characterized by a decadal fluctuation, was well correlated (+0.58) with MEI; the spatial distribution of the correlation revealed, for Europe and the Mediterranean area, height decrease till 2015, followed by increase, while Scandinavian and Baltic countries showed the opposite behavior. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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22 pages, 10786 KiB

Open AccessArticle

Feasibility Analysis of GNSS-Reflectometry for Monitoring Coastal Hazards

by Su-Kyung Kim, Eunju Lee, Jihye Park and Sungwon Shin

Remote Sens. 2021, 13(5), 976; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13050976 - 04 Mar 2021

Cited by 8 | Viewed by 2723

Abstract

Coastal hazards, such as a tsunamis and storm surges, are a critical threat to coastal communities that lead to significant loss of lives and properties. To mitigate their impact, event-driven water level changes should be properly monitored. A tide gauge is one of the conventional water level measurement sensors. Still, alternative measurement systems can be needed to compensate for the role of tide gauge for contingency (e.g., broken and absence, etc.). Global Navigation Satellite System (GNSS) is an emerging water level measurement sensor that processes multipath signals reflected by the water surface that is referred to as GNSS-Reflectometry (GNSS-R). In this study, we adopted the GNSS-R technique to monitor tsunamis and storm surges by analyzing event-driven water level changes. To detect the extreme change of water level, enhanced GNSS-R data processing methods were applied which included the utilization of multi-band GNSS signals, determination of optimal processing window, and Kalman filtering for height rate determination. The impact of coastal hazards on water level retrievals was assessed by computing the confidence level of retrieval (CLR) that was computed based on probability of dominant peak representing the roughness of the water surface. The proposed approach was validated by two tsunami events, induced by 2012 Haida Gwaii earthquake and 2015 Chile earthquake, and two storm surge events, induced by 2017 Hurricane Harvey and occurred in Alaska in 2019. The proposed method successfully retrieved the water levels during the storm surge in both cases with the high correlation coefficients with the nearby tide gauge, 0.944, 0.933, 0.987, and 0.957, respectively. In addition, CLRs of four events are distinctive to the type of coastal events. It is confirmed that the tsunami causes the CLR deduction, while for the storm surges, GNSS-R keep high CLR during the event. These results are possibly used as an indicator of each event in terms of storm surge level and tsunami arrival time. This study shows that the proposed approach of GNSS-R based water level retrieval is feasible to monitor coastal hazards that are tsunamis and storm surges, and it can be a promising tool for investigating the coastal hazards to mitigate their impact and for a better decision making. Full article

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15 pages, 3580 KiB

Open AccessArticle

Seasonal Variation of GPS-Derived the Principal Ocean Tidal Constituents’ Loading Displacement Parameters Based on Moving Harmonic Analysis in Hong Kong

by Maosheng Zhou, Xin Liu, Jiajia Yuan, Xin Jin, Yupeng Niu, Jinyun Guo and Hao Gao

Remote Sens. 2021, 13(2), 279; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13020279 - 14 Jan 2021

Cited by 10 | Viewed by 2007

Abstract

The classical harmonic analysis (CHA) method only can be used to obtain the harmonic constants (amplitude and phase) of ocean tide loading displacement (OTLD). In fact, there are significant seasonal variations in the harmonic constants of OTLD. A moving harmonic analysis (MHA) method is proposed, which can effectively capture the seasonal variation of OTLD parameters. Based on 5 years of kinematic coordinate time series in direction U of six Global Positioning System (GPS) stations in Hong Kong, the MHA method is used to explore the seasonal variation of the OTLD parameters of the 6 principal tidal constituents (M2, S2, N2, K1, O1, Q1). The influence of mass loading on the seasonal variation of OTLD parameters is analyzed. The results show that there are obviously seasonal variations in OTLD parameters of the 6 principal tidal constituents in Hong Kong. The OTLD’s amplitude’s changes of the 6 principal tidal constituents are around 4–25.1% and the oscillation ranges of OTLD’s phase parameters vary from 8.8° to 20.4°. Among the seasonal variations of OTLD parameters, the annual signal, the semi-annual signal, and the ter-annual signal are the most significant. By analyzing the influence of atmospheric loading on the seasonal variation of OTLD parameters, it is found that atmospheric loading has certain contribution to the seasonal variation of OTLD parameters. Hydrological loading and non-tidal ocean loading have little influence on the seasonal variation of OTLD parameters. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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21 pages, 8960 KiB

Open AccessArticle

Recent Crustal Deformation Based on Interpolation of GNSS Velocity in Continental China

by Weiwei Bian, Jicang Wu and Weiwei Wu

Remote Sens. 2020, 12(22), 3753; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12223753 - 14 Nov 2020

Cited by 7 | Viewed by 2414

Abstract

We used the interpolation method of two-dimensional vector velocity field data based on Green’s function to conduct coupled interpolation with a Poisson’s ratio of 0.5 for 1966 horizontal velocity field data from 1999 to 2017 and obtained the uniform velocity field and strain rate field with a grid of 1°. The main results are as follows: the eastern Himalayan structure as the center, the eastern Lhasa block, the eastern Qiangtang block, the Sichuan-Yunnan block, and the Burma block form a strong deformation rate zone of continuous deformation in the fan-shaped region, which has been a strong deformation rate zone for earthquakes of magnitude 7 or higher in continental China since 1963. Besides, the eastward movement of crustal material in the Tibetan Plateau is blocked by the stable South China block. Therefore, the direction of crustal material movement is deflected, which gradually forms a clockwise rotation motion system centered on the eastern Himalayan structure. Finally, our research shows that the influencing factors of strong earthquakes include velocity change, non-uniform strain distribution, accumulation of larger strain, and the difference of the second strain rate invariant. Strong earthquakes are closely related to the difference in energy accumulation in space. Full article

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19 pages, 3767 KiB

Open AccessEditor’s ChoiceArticle

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

by Stefano Tavani, Antonio Pignalosa, Amerigo Corradetti, Marco Mercuri, Luca Smeraglia, Umberto Riccardi, Thomas Seers, Terry Pavlis and Andrea Billi

Remote Sens. 2020, 12(21), 3616; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12213616 - 04 Nov 2020

Cited by 25 | Viewed by 5710

Abstract

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. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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24 pages, 9040 KiB

Open AccessArticle

GNSS-TS-NRS: An Open-Source MATLAB-Based GNSS Time Series Noise Reduction Software

by Xiaoxing He, Kegen Yu, Jean-Philippe Montillet, Changliang Xiong, Tieding Lu, Shijian Zhou, Xiaping Ma, Hongchao Cui and Feng Ming

Remote Sens. 2020, 12(21), 3532; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12213532 - 28 Oct 2020

Cited by 22 | Viewed by 4989

Abstract

The global navigation satellite system (GNSS) has seen tremendous advances in measurement precision and accuracy, and it allows researchers to perform geodynamics and geophysics studies through the analysis of GNSS time series. Moreover, GNSS time series not only contain geophysical signals, but also unmodeled errors and other nuisance parameters, which affect the performance in the estimation of site coordinates and related parameters. As the number of globally distributed GNSS reference stations increases, GNSS time series analysis software should be developed with more flexible format support, better human–machine interaction, and with powerful noise reduction analysis. To meet this requirement, a new software named GNSS time series noise reduction software (GNSS-TS-NRS) was written in MATLAB and was developed. GNSS-TS-NRS allows users to perform noise reduction analysis and spatial filtering on common mode errors and to visualize GNSS position time series. The functions’ related theoretical background of GNSS-TS-NRS were introduced. Firstly, we showed the theoretical background algorithms of the noise reduction analysis (empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD)). We also developed three improved algorithms based on EMD for noise reduction, and the results of the test example showed our proposed methods with better effect. Secondly, the spatial filtering model supported five algorithms on a separate common model error: The stacking filter method, weighted stacking filter method, correlation weighted superposition filtering method, distance weighted filtering method, and principal component analysis, as well as with batch processing. Finally, the developed software also enabled other functions, including outlier detection, correlation coefficient calculation, spectrum analysis, and distribution estimation. The main goal of the manuscript is to share the software with the scientific community to introduce new users to the GNSS time series noise reduction and application. Full article

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21 pages, 5458 KiB

Open AccessArticle

Strain Pattern and Kinematics of the Canary Islands from GNSS Time Series Analysis

by Jose Arnoso, Umberto Riccardi, Maite Benavent, Umberto Tammaro, Fuensanta G. Montesinos, Isabel Blanco-Montenegro and Emilio Vélez

Remote Sens. 2020, 12(20), 3297; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12203297 - 10 Oct 2020

Cited by 12 | Viewed by 3748

Abstract

Following the 2004 seismic unrest at Tenerife and the 2011–2012 submarine eruption at El Hierro, the number of Global Navigation Satellite System (GNSS) observation sites in the Canary Islands (Spain) has increased, offering scientists a useful tool with which to infer the kinematics and present-day surface deformation of the Canary sector of the Atlantic Ocean. We take advantage of the common-mode component filtering technique to improve the signal-to-noise ratio of the velocities retrieved from the daily solutions of 18 permanent GNSS stations distributed in the Canaries. The analysis of GNSS time series spanning the period 2011–2017 enabled us to characterize major regions of deformation along the archipelago through the mapping of the 2D infinitesimal strain field. By applying the triangular segmentation approach to GNSS velocities, we unveil a variable kinematic behaviour within the islands. The retrieved extension pattern shows areas of maximum deformation west of Tenerife, Gran Canaria and Fuerteventura. For the submarine main seismogenic fault between Tenerife and Gran Canaria, we simulated the horizontal deformation and strain due to one of the strongest (m_bLg 5.2) earthquakes of the region. The seismic areas between islands, mainly offshore Tenerife and Gran Canaria, seem mainly influenced by the regional tectonic stress, not the local volcanic activity. In addition, the analysis of the maximum shear strain confirms that the regional stress field influences the E–W and NE–SW tectonic lineaments, which, in accordance with the extensional and compressional tectonic regimes identified, might favour episodes of volcanism in the Canary Islands. Full article

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15 pages, 2090 KiB

Open AccessArticle

Reconstruction of Wet Refractivity Field Using an Improved Parameterized Tropospheric Tomographic Technique

by Biyan Chen, Wujiao Dai, Pengfei Xia, Minsi Ao and Jingshu Tan

Remote Sens. 2020, 12(18), 3034; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12183034 - 17 Sep 2020

Cited by 7 | Viewed by 2147

Abstract

In most previous studies of tropospheric tomography, water vapor is assumed to have a homogeneous distribution within each voxel. The parameterization of voxels can mitigate the negative effects of the improper assumption to the tomographic solution. An improved parameterized algorithm is proposed for determining the water vapor distribution by Global Navigation Satellite System (GNSS) tomography. Within a voxel, a generic point is determined via horizontal inverse distance weighted (IDW) interpolation and vertical exponential interpolation from the wet refractivities at the eight surrounding voxel nodes. The parameters involved in exponential and IDW interpolation are dynamically estimated for each tomography by using the refractivity field of the last process. By considering the quasi-exponential behavior of the wet refractivity profile, an optimal algorithm is proposed to discretize the vertical layers of the tomographic model. The improved parameterization algorithm is validated with the observational data collected over a 1-month period from 124 Global Positioning System (GPS) stations of Hunan Province, China. Assessments by GPS, radiosonde, and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis 5 (ERA5) data, demonstrate that the improved model outperforms the traditional nonparametric model and the parameterized model using trilinear interpolation. In the assessment by GPS data, the improved model performs better than the traditional model and the trilinear parameterized model by 54% and 10%, respectively. Such improvements are 31% and 10% in the validation by radiosonde profiles. In comparison with the ERA5 reanalysis, the improved model yields a minimum overall root mean square (RMS) error of 8.94 mm/km, while those of the traditional and trilinear parametrized models are 10.79 and 9.73 mm/km, respectively. The RMS errors vertically decrease from ~20 mm/km at the bottom to ~5 mm/km at the top layer. Full article

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14 pages, 1849 KiB

Open AccessTechnical Note

Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations

by Artem M. Padokhin, Anna A. Mylnikova, Yury V. Yasyukevich, Yury V. Morozov, Gregory A. Kurbatov and Artem M. Vesnin

Remote Sens. 2021, 13(19), 3973; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13193973 - 04 Oct 2021

Cited by 6 | Viewed by 2344

Abstract

Global navigation satellite system signals are known to be an efficient tool to monitor the Earth ionosphere. We suggest Galileo E5 AltBOC phase and pseudorange observables—a single-frequency combination—to estimate the ionospheric total electron content (TEC). We performed a one-month campaign in September 2020 to compare the noise level for different TEC estimations based on single-frequency and dual-frequency data. Unlike GPS, GLONASS, or Galileo E5a and E5b single-frequency TEC estimations (involving signals with binary and quadrature phase-shift keying, such as BPSK and QPSK, or binary offset carrier (BOC) modulation), an extra wideband Galileo E5 AltBOC signal provided the smallest noise level, comparable to that of dual-frequency GPS. For elevation higher than 60 degrees, the 100 s root-mean-square (RMS) of TEC, an estimated TEC noise proxy, was as follows for different signals: ~0.05 TECU for Galileo E5 AltBOC, 0.09 TECU for GPS L5, ~0.1TECU for Galileo E5a/E5b BPSK, and 0.85 TECU for Galileo E1 CBOC. Dual-frequency phase combinations provided RMS values of 0.03 TECU for Galileo E1/E5, 0.03 and 0.07 TECU for GPS L1/L2 and L1/L5. At low elevations, E5 AltBOC provided at least twice less single-frequency TEC noise as compared with data obtained from E5a or E5b. The short dataset of our study could limit the obtained estimates; however, we expect that the AltBOC single-frequency TEC will still surpass the BPSK analogue in noise parameters when the solar cycle evolves and geomagnetic activity increases. Therefore, AltBOC signals could advance geoscience. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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18 pages, 7353 KiB

Open AccessTechnical Note

The Ground Deformation History of the Neapolitan Volcanic Area (Campi Flegrei Caldera, Somma–Vesuvius Volcano, and Ischia Island) from 20 Years of Continuous GPS Observations (2000–2019)

by Prospero De Martino, Mario Dolce, Giuseppe Brandi, Giovanni Scarpato and Umberto Tammaro

Remote Sens. 2021, 13(14), 2725; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13142725 - 11 Jul 2021

Cited by 32 | Viewed by 4439

Abstract

The Neapolitan volcanic area includes three active and high-risk volcanoes: Campi Flegrei caldera, Somma–Vesuvius, and Ischia island. The Campi Flegrei volcanic area is a typical example of a resurgent caldera, characterized by intense uplift periods followed by subsidence phases (bradyseism). After about 21 years of subsidence following the 1982–1984 unrest, a new inflation period started in 2005 and, with increasing rates over time, is ongoing. The overall uplift from 2005 to December 2019 is about 65 cm. This paper provides the history of the recent Campi Flegrei caldera unrest and an overview of the ground deformation patterns of the Somma–Vesuvius and Ischia volcanoes from continuous GPS observations. In the 2000–2019 time span, the GPS time series allowed the continuous and accurate tracking of ground and seafloor deformation of the whole volcanic area. With the aim of improving the research on volcano dynamics and hazard assessment, the full dataset of the GPS time series from the Neapolitan volcanic area from January 2000 to December 2019 is presented and made available to the scientific community. Full article

(This article belongs to the Special Issue GNSS for Geosciences)

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