GNSS Reflectometry, an Innovative Remote Sensing Tool for the Mekong Delta - PowerPoint PPT Presentation

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GNSS Reflectometry, an Innovative Remote Sensing Tool for the Mekong Delta

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  1. GNSS Reflectometry, an Innovative Remote Sensing Tool for the Mekong Delta J. Beckheinrich1, S. Schön2, G. Beyerle1, M. Semmling1, H. Apel1, J. Wickert1 GFZ, German Research Center for Geosciences, Potsdam, Germany Leibniz University Hannover, Institute of Geodesy, Hannover, Germany Space Reflecto 2013 Brest, France

  2. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  3. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  4. WP within the WISDOM Project: • Severe changes could be observed in the Mekong Delta: • extreme flood events • important to monitor coastal area with dense population • Test the possibility of using low elevation GNSS-Reflectometry for flood monitoring of the Mekong Delta • Develop and implement algorithms to process GPS signals into water levels

  5. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  6. Experimental setup: Gauge 6 km 150 m Measurement location Slide 6

  7. Experimental setup: • Two time series with two different antenna heights above the reflecting surface: • Terrace with ~10 m • Roof with ~20 m Slide 7

  8. Experimental setup: • Two antennas (Antcom): • RHCP oriented to the zenith (direct signal) • LHCP tilted to the reflecting surface (reflected signal) Direct signal L1/L2 GPS RHCP RHCP/ LHCP L1/L2 GPS Reflected signal Slide 8

  9. Experimental setup: a: GORS b: Control unit c: Laptop d: External Hard Disk Slide 9

  10. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  11. Data Analysis:

  12. Data Analysis: Incoherent Observations Coherent Observations Hotel River Terrace (~10 m) Roof (~20 m)

  13. Data Analysis:

  14. Data Analysis: Receiver Reflection track River

  15. Data Analysis: Empirical Mode Decomposition (EMD) Method: • 1998 Huang [1] • 2008 and 2013 Hirrle [2] Motivation: • Fourier Transform assume stationarity and linearity • Wavelet Transform assume linearity • EMD is a fully data-driven signal analysis • No need of an a priori base

  16. Data Analysis: • Intrinsic Mode Functions (IMF) Input signal IMF Trend

  17. Data Analysis: Input Signal

  18. Data Analysis: Maxima and minima

  19. Data Analysis: Cubic spline interpolation

  20. Data Analysis: Mean

  21. Data Analysis: Resulting Signal

  22. Data Analysis: • Intrinsic Mode Functions (IMF) Input signal IMF Trend

  23. Data Analysis: Trend

  24. Data Analysis: Horizontal Reflector h = 13 m Vertical Reflector h = 1 m

  25. Data Analysis: IMF 2 vs Vertical Reflection IMF 1 vs Horizontal Reflection Completness

  26. Data Analysis: PRN 12, Vietnam, Can Tho City, 28th February 2012 Frequency

  27. Data Analysis: PRN 12, Vietnam, Can Tho City, 28th February 2012 Frequency

  28. First results: EMD Observations

  29. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  30. Latest Results: EMD Beckheinrich J. et al, GNSS Reflectometry: Innovative Flood Monitoring at the Mekong Delta, submitted JSTARS august 2013

  31. Latest Results: Vietnam, Can Tho City, 29th February 2012 With EMD: std (1σ) = 0.05 m Without EMD: std (1σ) = 0.12 m

  32. Latest Results: Vietnam, Can Tho City, 29thFebruary 2012

  33. WP within the WISDOM project Experimental Setup Data Analysis Latest Results Conclusion and Outlook

  34. Conclusion and Outlook: • Although the measurement were made under challenging conditions we could reach a correlation of 0.84 with the data recorded from a gauge instrument • GNSS-R could contribute to monitor water level changes of the Mekong Delta • Improvement of stochastic and functional model • Determination of sigma reflected signals (Experiment) • Include Phase Wind up effect • Amplitude • Better understanding of the EMD parameters and there impact on the IMF decomposition Slide 34

  35. References: [1] Huang N.E. et al., The Empirical Mode Decomposition and the Hilbert Spectrum for non linear and non-stationary time series analysis, Proc. R. Soc. London A, (1998), pp. 903-995 [2] Hirrle A. Et al., Estimation of Multipath Parameters using Hilbert Huang Transform, ION GNSS, Nashville, Tennessee, USA, 2012 [3] Beckheinrich J. et al., GNSS Reflectometry: Innovative Flood Monitoring at the Mekong Delta, submitted at JSTARS, August 2013

  36. Thank you for your attention jamila.beckheinrich@gfz-potsdam.de Slide 36

  37. First Fresnel zone, 10 m height antenna

  38. First Fresnel zone, 20 m antenna height