slide analysis of gps position time series renag network (france)

HN KH&CN 14THE 14TH CONFERENCE ON SCIENCE AND TECHNOLOGY Section: Geodesy engineering - Mapping ANALYSIS OF GPS POSITION TIME SERIES RENAG NETWORK FRANCE Trần Đình Trọng, Bùi Ngọc Sơn, V

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ANALYSIS OF GPS POSITION TIME SERIES

RENAG NETWORK (FRANCE)

Trần Đình Trọng (trandinhtrong@nuce.edu.vn )

Bùi Ngọc Sơn

Vũ Đình Chiều

Dept of Geodesy, National university of civil engineering (NUCE)

THE 14TH CONFERENCE ON SCIENCE AND TECHNOLOGY

Ho Chi Minh City University of Technology SSection: Geodesy engineering - Mapping

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THE 14TH CONFERENCE ON SCIENCE AND TECHNOLOGY Section: Geodesy engineering - Mapping

ANALYSIS OF GPS POSITION TIME SERIES RENAG NETWORK (FRANCE) Trần Đình Trọng, Bùi Ngọc Sơn, Vũ Đình Chiều

PLAN:

Introduction RENAG Network Analysis of RENAG GPS time series Conclusion

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GEONET (Yuki Hatanaka et al 2003)

Réseau GPS de Taiwan (Kuan‐Chuan Lin et al 2010)

EPOS

Introduction

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(Segall and Davis, 1997)

Seismic, post-seismic displacement determination

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Introduction Application of GPS time series in geophysics

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(Vergnolle et al., 2010)

Study the transient motion)

Introduction Application of GPS time series in geophysics

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PLAN:

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waves due to earthquakes,

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Period 1998.0 – 2010.8

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Xử lý chuỗi vị trí của mạng lưới GPS liên tục RENAG – Pháp Trần Đình Trọng, Bùi Ngọc Sơn, Vũ Đình Chiều

Analysis of RENAG GPS time series

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Permanent/campaign GPS data Free solutions (GAMIT, BERNESE, ) Transform free solutions to ITRF: Time series

Remove outliers Correct offsets

Long term velocity within ITRF

Detect/estimate co-seismic displacement

Detect/estimate transients:

Post-seismic, Slow Slip Events

Evaluate seasonnal variations

Tectonic/kinematic model

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Permanent/campaign GPS data Free solutions (GAMIT, BERNESE, ) Transform free solutions to ITRF: Time series

Remove outliers Correct offsets

Long term velocity within ITRF

Detect/estimate co-seismic displacement

Detect/estimate transients:

Post-seismic, Slow Slip Events

Evaluate seasonnal variations

Tectonic/kinematic model

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Make GPS position daily time series

WGS84 – ITRF transfortmation:

Helmert transformation:

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- The stations available to estimate the transformation vary over time

- The presence of outliers (outliers) / offsets (jumps) in the positions

Analysis of RENAG GPS time series Make GPS position daily time series

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Solutions:

- The stations available in IGS &

RENAG

- Use Dikin estimator [2] to detect

& eliminate outliers:

[p|v|] = min

- Estimate 7 parameters of Helmert

transformation by least square

using clean data:

[pvv] = min

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GPS time series

wrms histogram

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Due to a lack of data, a hardware problem, a problem in computational strategy,

Analysis of RENAG GPS time series Problems in time series

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Due to change of models (atmosphere), strategy analysis, antenna; phenomena

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Seasonal variation: annual & semi-annual term

Due to cyclical changes as changes in groundwater level, seasonal temperature

(summer, winter),…

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Time series analysis

Detection of outliers : Based on the variations of rms calculated

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- Velocity change or post-seismic relaxations

`

- linear trend

- Saisonnal terms

- Jump, co-seismic deplacement

0036 (projet ANR TO-EOS, GEONET, source: E Klein)

Determination of parameters movement in time series

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Analysis of RENAG GPS time series Time series analysis

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Histograms of repeatability from the final treatment

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Somes typical time series analysed

BARK

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Một vài chuỗi điển hình được xử lý:

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Velocity field in ITRF2008 from RENAG: 6mm/yr +/- 0.4mm/yr

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THANKS FOR YOUR

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