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On the potential of TanDEM-X for the retrieval of agricultural crop parameters

On the potential of TanDEM-X for the retrieval of agricultural crop parameters by single-pass PolInSAR. Juan M. Lopez-Sanchez and J. David Ballester-Berman Signals, Systems and Telecommunications Group University of Alicante, Spain. Motivation.

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On the potential of TanDEM-X for the retrieval of agricultural crop parameters

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  1. On the potential of TanDEM-X for the retrieval of agricultural crop parameters by single-pass PolInSAR Juan M. Lopez-Sanchez and J. David Ballester-Berman Signals, Systems and Telecommunications Group University of Alicante, Spain

  2. Motivation • Final application: information for helping farming practices • Requirement: Timely and local information about crop phenology, condition, and other indicators • TanDEM-X: proof-of-concept • High spatial resolution (1-3 m) • Short revist time (11 days) • Single-pass interferometry • Parameters of interest to be retrieved with single-pass PolInSAR: • Vegetation height: correlated to phenology in many crops (especially during the vegetative phase) • Structural parameters related to phenology and crop condition: • Extinction • Vertical profiles (using PCT) • Other physical features (target decomposition): randomness, orientation of leaves and branches, water content, etc.

  3. Methodology • A number of direct models have been developed in the last years: • General: Homogeneous volume over ground • Model: Analytical expression of the complex interferometric coherence, as a function of polarization channel 2 Oriented Random Alternate-tx (monostatic) 1 Single-tx (bistatic) VOLUME Direct Double-bounce GROUND Both

  4. Methodology RVoG: alternate-tx, and single-tx with direct ground RVoG: single-tx with double-bounce from ground • Examples • All coherences are aligned • Line depends on scene • and interferometer

  5. Methodology • Examples OVoG: single-tx with double-bounce from ground OVoG: alternate-tx, and single-tx with direct ground Coherences are no longer aligned

  6. Methodology OVoG with both ground contributions • Examples RVoG with both ground contributions Alternate-tx Single-tx Alternate-tx Single-tx

  7. Methodology • Baseline requirements • If too small: no decorrelation, hence all coherences in a small cluster (i.e. insensitive) • If too large: extreme volume decorrelation, hence low coherence and presence of phase noise • Important: kz * hv (or kv = kz*hv/2) • Ideal case: kv = 1 [Cloude 2009] • Typical example for crops: hv = 1 m • With the mentioned criterion: kz = 2, i.e. hamb = 3.14 m • TanDEM-X: Bn ~ 3 km (bistatic) or 1.5 km (alternate-tx) • Normal mode: Bn ~ 250-300 m, kz ~ 0.2-0.4 • Some sensitivity is expected…

  8. Available data set: Wallerfing (Germany) • Date: April 12, 2011 (no ground truth, but scarce agriculture is expected) • Mode: Bistatic • Polarizations: HH VV • Incidence angle (scene center): 32.66 degrees • Height of ambiguity: 133.4 m • Perpendicular baseline: 76.56 m • InSAR sensitivity: • Vertical wavenumber kz = 0.0471 • For agricultural crops with hv = 1 m, kv = 0.0236 << 1

  9. Wallerfing: RGB composite HH-VV VV HH

  10. Wallerfing: coherence maps HH+VV HH HH-VV VV

  11. Wallerfing (sample): RGB composite Sample extracted from the image HH-VV VV HH

  12. Wallerfing (sample): coherence maps HH+VV HH HH-VV VV

  13. Wallerfing (sample): backscatter HH VV

  14. Wallerfing (sample): SNR effect • Low backscattering levels are expected from agriculture fields • Data sample: bare fields or with scarce vegetation: below -10 dB • NESZ in these TSX/TDX images (from annotated info): - 21 to -24 dB • Decorrelation due to SNR:

  15. Wallerfing (sample): SNR effect • If NESZ = -22 dB is assumed, decorrelation due to SNR can be estimated from backscattering levels: Example: Typical values for HH and VV over rice fields with TSX

  16. Wallerfing (sample): SNR effect • Application to these data: HH, and similar for VV Estimated from SNR Measured

  17. Wallerfing (sample): SNR effect • Application to these data: HH+VV Estimated from SNR Measured

  18. Wallerfing (sample): SNR effect • Application to these data: HH-VV Estimated from SNR Measured

  19. Wallerfing (sample): coherence set Set of 6 coherences: HH, VV HH+VV, HH-VV Optimum (1st and 2nd)

  20. Wallerfing (sample): interf. phases HH+VV HH HH-VV VV

  21. Wallerfing (sample): diff. interf. phases Phase HH – Phase VV Phase HH+VV – Phase HH-VV Height HH – Height VV Height HH+VV – Height HH-VV

  22. Wallerfing (sample): PolSAR Average alpha Entropy alpha1

  23. Planned acquisitions • Generic: various types of crops • Barrax (Albacete), SE Spain • Types: wheat, barley, maize, etc. • Farming practices information and optical images available • Measurements of LAI, vegetation height, phenology, soil moisture • Roseworthy farm (Adelaide), S Australia • Types: wheat, barley, legumes, peas, beans, canola. • Measurements of vegetation height, phenology, etc. • Thematic: • Rice fields in Sevilla, SW Spain • Weekly measurements of phenology, height, condition changes • Extra data: sowing & harvest date, plantation density, yield

  24. Expected results • Better results are expected for the planned acquisitions (Jun-Aug 2011): • Baselines: 240 – 300 m • Many acquisitions in alternate bistatic mode • Regarding the application: Expected limitations: • Noise • Reduced swath: small spatial coverage • Potential solution: combination of passes (asc, desc, etc.)

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