Difference between revisions of "JSG T.32"

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<big>'''JSG 0.19: Time series analysis in geodesy'''</big>
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<big>'''JSG T.32: High-rate GNSS for geoscience and mobility'''</big>
  
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Chair: ''Wieslaw Kosek (Poland)''<br>
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Chair: ''Mattia Crespi (Italy)''<br>
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Affiliation:''Comm. 3 and GGOS''
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Affiliation:''Commissions 1, 3 and 4, GGOS''
  
 
__TOC__
 
__TOC__
  
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===Terms of Reference===
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===Introduction===
  
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Observations of the space geodesy techniques and on the Earth's surface deliver a global picture of the Earth dynamics represented in the form of time series which describe 1) changes of the Earth surface geometry, 2) the fluctuations in the Earth orientation, and 3) the variations of the Earth’s gravitational field. The Earth's surface geometry, rotation and gravity field are the three components of the Global Geodetic Observing System (GGOS) which integrates them into one unique physical and mathematical model. However, temporal variations of these three components represent the total, integral effect of all global mass exchange between all elements of the Earth’s system including the Earth's interior and fluid layers:  atmosphere, ocean and land hydrology.
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Global Navigation Satellite Systems (GNSS) have become for a long time an indispensable tool to get accurate and reliable information about positioning and timing; in addition, GNSS are able to provide information related to physical properties of media passed through by GNSS signals. Therefore, GNSS play a central role both in geodesy and geomatics and in several branches of geophysics, representing a cornerstone for the observation and monitoring of our planet.
  
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Different time series analysis methods have been applied to analyze all these geodetic time series for better understanding of the relations between all elements of the Earth’s system as well as their geophysical causes. The interactions between different components of the Earth’s system are very complex so the nature of considered signals in the geodetic time series is mostly wideband, irregular and non-stationary. Thus, it is recommended to apply wavelet based spectra-temporal analysis methods to analyze these geodetic time series as well as to explain their relations to geophysical processes in different frequency bands using time-frequency semblance and coherence methods. These spectra-temporal analysis methods and time-frequency semblance and coherence may be further developed to display reliably the features of the temporal or spatial variability of signals existing in various geodetic data, as well as in other source data sources.
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So, it is not surprising that, from the very beginning of the GNSS era, the goal was pursued to widen as much as possible the range in space (from local to global) and time (from short to long term) of the observed phenomena, in order to cover the largest possible field of applications, both in science and in engineering. Two additional primary goals were, obviously, to get this information with the highest accuracy and in the shortest time.  
  
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Geodetic time series include for example horizontal and vertical deformations of site positions determined from observations of space geodetic techniques. These site positions change due to e.g. plate tectonics, postglacial rebound, atmospheric, hydrology and ocean loading and earthquakes. However they are used to build the global international terrestrial reference frame (ITRF) which must be stable reference for all other geodetic observations including e.g. satellite orbit parameters and Earth's orientation parameters which consist of precession, nutation, polar motion and UT1-UTC that are necessary for transformation between the terrestrial and celestial reference frames. Geodetic time series include also temporal variations of Earth's gravity field where 1 arc-deg spherical harmonics correspond to the Earth’s centre of mass variations (long term mean of them determines the ITRF origin) and 2 degree spherical harmonics correspond to Earth rotation changes. Time series analysis methods can be also applied to analyze data on the Earth's surface including maps of the gravity field, sea level, ice covers, ionospheric total electron content and tropospheric delay as well as temporal variations of such surface data. The main problems to deal with include the estimation of deterministic (including trend and periodic variations) and stochastic (non-periodic variations and random changes) components of the geodetic time series as well as the application of digital filters for extracting specific components with a chosen frequency bandwidth.
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The advances in technology and the deployment of new constellations, after GPS (in the next few years the European Galileo, the Chinese Beidou and the Japanese QZSS will be completed) remarkably contributed to transform this three-goals dream in reality, but still remain significant challenges when very fast phenomena have to be observed, mainly if real-time results are looked for.
  
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The multiple methods of time series analysis may be encouraged to be applied to the preprocessing of raw data from various geodetic measurements in order to promote the quality level of enhancement of signals existing in these data. The topic on the improvement of the edge effects in time series analysis may also be considered, since they may affect the reliability of long-range tendency (trends) estimated from data series as well as the real-time data processing and prediction.
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Actually, for almost 15 years, starting from the noble birth in seismology, and the very first experiences in structural monitoring, high-rate GNSS has demonstrated its usefulness and power in providing precise positioning information in fast time-varying environments. At the beginning, high-rate observations were mostly limited at 1 Hz, but the technology development provided GNSS equipment (in some cases even at low-cost) able to collect measurements at much higher rates, up to 100 Hz, therefore opening new possibilities, and meanwhile new challenges and problems.
  
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For coping with small geodetic samples one can apply simulation-based methods and if the data are sparse, Monte-Carlo simulation or bootstrap technique may be useful. Understanding the nature of geodetic time series is very important from the point of view of appropriate spectral analysis as well as application of filtering and prediction methods.
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So, it is necessary to think about how to optimally process this potential huge heap of data, in order to supply information of high value for a large (and increasing) variety of applications, some of them listed hereafter without the claim to be exhaustive: better understanding of the geophysical/geodynamical processes mechanics; monitoring of ground shaking and displacement during earthquakes, also for contribution to tsunami early warning; tracking the fast variations of the ionosphere; real-time controlling landslides and the safety of structures; providing detailed trajectories and kinematic parameters (not only position, but also velocity and acceleration) of high dynamic platforms such as airborne sensors, high-speed terrestrial vehicles and even athlete and sport vehicles monitoring.
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Further, due to the contemporary technological development of other sensors (hereafter referred as ancillary sensors) related to positioning and kinematics able to collect high-rate data (among which MEMS accelerometers and gyros play a central role, also for their low-cost), the feasibility of a unique device for high-rate observations embedding GNSS receiver and MEMS sensors is real, and it opens, again, new opportunities and problems, first of all related to sensors integration.
 +
In this respect, Android based mass-market devices (smartphones and tablets) are nowadays able to provide 1 Hz raw GNSS measurements (with a growing number of models able to provide multi-constellation and multi-frequency code and phase observations) in addition to the above-mentioned ancillary sensors measurements.
 +
 
 +
All in all, it is clear that high-rate GNSS (and ancillary sensors) observations represent a great resource for future investigations in Earth sciences and applications in engineering, meanwhile stimulating a due attention from the methodological point of view in order to exploit their full potential and extract the best information.  This is the why it is worth to open a focus on high-rate (and, if possible, real-time) GNSS within ICCT.
  
 
===Objectives===
 
===Objectives===
  
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* Study of the nature of geodetic time series to choose optimum time series analysis methods for filtering, spectral analysis, time frequency analysis and prediction.
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* To realize the inventories of:
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* Study of Earth's geometry, rotation and gravity field variations and their geophysical causes in different frequency bands.
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** the available and applied methodologies for high-rate GNSS, in order to highlight their pros and cons and the open problems
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* Evaluation of appropriate covariance matrices for the time series by applying the law of error propagation to the original measurements, including weighting schemes, regularization, etc.
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** the present and wished applications of high-rate GNSS for science and engineering, with a special concern to the estimated quantities (geodetic, kinematic, physical), in order to focus on related problems (still open and possibly new) and draw future challenges
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* Determination of the statistical significance levels of the results obtained by different time series analysis methods and algorithms applied to geodetic time series.
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** the technology (hw, both for GNSS and ancillary sensors, and sw, possibly FOSS), pointing out what is ready and what is coming, with a special concern for the supplied observations and for their functional and stochastic modelling with the by-product of establishing a standardized terminology.
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* Development and comparison of different time series analysis methods in order to point out their advantages and disadvantages.
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* To address known (mostly cross-linked) problems related to high-rate GNSS as (not an exhaustive list): revision and refinement of functional and stochastic models; evaluation and impact of observations time-correlation; impact of multipath and constellation change; outlier detection and removal; issues about GNSS constellations interoperability; ancillary sensors evaluation, cross-calibration and integration.
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* Recommendations of different time series analysis methods for solving problems concerning specific geodetic time series.
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* To address new problems and future challenges which arise from inventories.
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* To investigate about the interaction with present real-time global (IGS-RT, EUREF-IP, etc.) and regional/local positioning services: how can these services support high-rate GNSS observations and, on reverse, how can they benefit of high-rate GNSS observations
  
 
===Program of activities===
 
===Program of activities===
  
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* Launching of a website about time series analysis in geodesy providing list of papers from different disciplines as well as unification of terminology applied in time series analysis.
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* To launch a questionnaire for the above mentioned inventory of methodologies, applications and technologies.
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* Working meetings at the international symposia and presentation of research results at the appropriate sessions.
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* To open a web page with information concerning high-rate GNSS and its wide applications in science and engineering, with special emphasis on exchange of ideas, raw relevant datasets, provision and updating bibliographic list of references of research results and relevant publications from different disciplines.
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* To launch the proposal for two (one science and the other engineering oriented) state-of-the-art review papers in high-rate GNSS co-authored by JSG members.
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* To promote sessions and presentation of research results at international symposia both related to Earth science (IAG/IUGG, EGU, AGU, EUREF, IGS), engineering (workshops and congresses in structural, geotechnical, mechanical, transport and automotive engineering), and life sciences (sports and health care).
  
 
===Membership===
 
===Membership===
  
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'' '''Wieslaw Kosek (Poland), chair''' <br /> Michael Schmidt (Germany) <br /> Jan Vondrák (Czech Republic) <br /> Waldemar Popinski (Poland) <br /> Tomasz Niedzielski (Poland) <br /> Johannes Boehm (Austria) <br /> Dawei Zheng (China) <br /> Yonghong Zhou (China) <br /> Mahmut O. Karslioglu (Turkey) <br /> Orhan Akyilmaz (Turkey) <br /> Laura Fernandez (Argentina) <br /> Richard Gross (USA) <br /> Olivier de Viron (France) <br /> Sergei Petrov (Russia) <br /> Michel Van Camp (Belgium) <br /> Hans Neuner (Germany) <br /> Xavier Collilieux (France) <br />''
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'' '''Mattia Crespi (Italy), chair ''' <br /> Elisa Benedetti (United Kingdom) <br /> Mara Branzanti (Switzerland) <br /> Liang Chen (China) <br /> Gabriele Colosimo (Switzerland) <br /> Elisabetta D’Anastasio (New Zealand) <br /> Roberto Devoti (Italy) <br /> Rui Fernandes (Portugal) <br /> Marco Fortunato (Italy) <br /> Athanassios Ganas (Greece) <br /> Pan Li (Germany) <br /> Alain Geiger (Switzerland) <br /> Jianghui Geng (China) <br /> Dara Goldberg (USA) <br /> Kathleen Hodgkinson (USA) <br /> Shuanggen Jin (China) <br /> Iwona Kudlacik (Poland) <br /> Jan Kaplon (Poland) <br /> Augusto Mazzoni (Italy) <br /> Joao Francisco Galera Monico (Brazil) <br /> Héctor Mora Páez (Colombia) <br /> Michela Ravanelli (Italy) <br /> Giorgio Savastano (Luxembourg) <br /> Sebastian Riquelme (Chile) <br /> Peiliang Xu (Japan) <br />''

Latest revision as of 12:33, 10 June 2020

JSG T.32: High-rate GNSS for geoscience and mobility

Chair: Mattia Crespi (Italy)
Affiliation:Commissions 1, 3 and 4, GGOS

Introduction

Global Navigation Satellite Systems (GNSS) have become for a long time an indispensable tool to get accurate and reliable information about positioning and timing; in addition, GNSS are able to provide information related to physical properties of media passed through by GNSS signals. Therefore, GNSS play a central role both in geodesy and geomatics and in several branches of geophysics, representing a cornerstone for the observation and monitoring of our planet.

So, it is not surprising that, from the very beginning of the GNSS era, the goal was pursued to widen as much as possible the range in space (from local to global) and time (from short to long term) of the observed phenomena, in order to cover the largest possible field of applications, both in science and in engineering. Two additional primary goals were, obviously, to get this information with the highest accuracy and in the shortest time.

The advances in technology and the deployment of new constellations, after GPS (in the next few years the European Galileo, the Chinese Beidou and the Japanese QZSS will be completed) remarkably contributed to transform this three-goals dream in reality, but still remain significant challenges when very fast phenomena have to be observed, mainly if real-time results are looked for.

Actually, for almost 15 years, starting from the noble birth in seismology, and the very first experiences in structural monitoring, high-rate GNSS has demonstrated its usefulness and power in providing precise positioning information in fast time-varying environments. At the beginning, high-rate observations were mostly limited at 1 Hz, but the technology development provided GNSS equipment (in some cases even at low-cost) able to collect measurements at much higher rates, up to 100 Hz, therefore opening new possibilities, and meanwhile new challenges and problems.

So, it is necessary to think about how to optimally process this potential huge heap of data, in order to supply information of high value for a large (and increasing) variety of applications, some of them listed hereafter without the claim to be exhaustive: better understanding of the geophysical/geodynamical processes mechanics; monitoring of ground shaking and displacement during earthquakes, also for contribution to tsunami early warning; tracking the fast variations of the ionosphere; real-time controlling landslides and the safety of structures; providing detailed trajectories and kinematic parameters (not only position, but also velocity and acceleration) of high dynamic platforms such as airborne sensors, high-speed terrestrial vehicles and even athlete and sport vehicles monitoring.

Further, due to the contemporary technological development of other sensors (hereafter referred as ancillary sensors) related to positioning and kinematics able to collect high-rate data (among which MEMS accelerometers and gyros play a central role, also for their low-cost), the feasibility of a unique device for high-rate observations embedding GNSS receiver and MEMS sensors is real, and it opens, again, new opportunities and problems, first of all related to sensors integration. In this respect, Android based mass-market devices (smartphones and tablets) are nowadays able to provide 1 Hz raw GNSS measurements (with a growing number of models able to provide multi-constellation and multi-frequency code and phase observations) in addition to the above-mentioned ancillary sensors measurements.

All in all, it is clear that high-rate GNSS (and ancillary sensors) observations represent a great resource for future investigations in Earth sciences and applications in engineering, meanwhile stimulating a due attention from the methodological point of view in order to exploit their full potential and extract the best information. This is the why it is worth to open a focus on high-rate (and, if possible, real-time) GNSS within ICCT.

Objectives

  • To realize the inventories of:
    • the available and applied methodologies for high-rate GNSS, in order to highlight their pros and cons and the open problems
    • the present and wished applications of high-rate GNSS for science and engineering, with a special concern to the estimated quantities (geodetic, kinematic, physical), in order to focus on related problems (still open and possibly new) and draw future challenges
    • the technology (hw, both for GNSS and ancillary sensors, and sw, possibly FOSS), pointing out what is ready and what is coming, with a special concern for the supplied observations and for their functional and stochastic modelling with the by-product of establishing a standardized terminology.
  • To address known (mostly cross-linked) problems related to high-rate GNSS as (not an exhaustive list): revision and refinement of functional and stochastic models; evaluation and impact of observations time-correlation; impact of multipath and constellation change; outlier detection and removal; issues about GNSS constellations interoperability; ancillary sensors evaluation, cross-calibration and integration.
  • To address new problems and future challenges which arise from inventories.
  • To investigate about the interaction with present real-time global (IGS-RT, EUREF-IP, etc.) and regional/local positioning services: how can these services support high-rate GNSS observations and, on reverse, how can they benefit of high-rate GNSS observations

Program of activities

  • To launch a questionnaire for the above mentioned inventory of methodologies, applications and technologies.
  • To open a web page with information concerning high-rate GNSS and its wide applications in science and engineering, with special emphasis on exchange of ideas, raw relevant datasets, provision and updating bibliographic list of references of research results and relevant publications from different disciplines.
  • To launch the proposal for two (one science and the other engineering oriented) state-of-the-art review papers in high-rate GNSS co-authored by JSG members.
  • To promote sessions and presentation of research results at international symposia both related to Earth science (IAG/IUGG, EGU, AGU, EUREF, IGS), engineering (workshops and congresses in structural, geotechnical, mechanical, transport and automotive engineering), and life sciences (sports and health care).

Membership

Mattia Crespi (Italy), chair
Elisa Benedetti (United Kingdom)
Mara Branzanti (Switzerland)
Liang Chen (China)
Gabriele Colosimo (Switzerland)
Elisabetta D’Anastasio (New Zealand)
Roberto Devoti (Italy)
Rui Fernandes (Portugal)
Marco Fortunato (Italy)
Athanassios Ganas (Greece)
Pan Li (Germany)
Alain Geiger (Switzerland)
Jianghui Geng (China)
Dara Goldberg (USA)
Kathleen Hodgkinson (USA)
Shuanggen Jin (China)
Iwona Kudlacik (Poland)
Jan Kaplon (Poland)
Augusto Mazzoni (Italy)
Joao Francisco Galera Monico (Brazil)
Héctor Mora Páez (Colombia)
Michela Ravanelli (Italy)
Giorgio Savastano (Luxembourg)
Sebastian Riquelme (Chile)
Peiliang Xu (Japan)

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