Time Series Analysis of Hybrid Polarimetric RISAT-1 Data for Soil Moisture Estimation G. G. Ponnurangam1,2, T. Jagdhuber1, I. Hajnsek1 and Y.S.

Transcription

1 Time Serie Analyi of Hybrid Polarimetric RISAT- Data for Soil Moiture Etimation G. G. Ponnurangam,, T. Jagdhuber, I. Hajnek and Y.S. Rao Microwave and Radar Intitute, German Aeropace Center (DLR), Weling, Germany Centre of Studie in Reource Engineering, Indian Intitute of Technology Bombay, India

2 Hybrid Polarimetry Advantage of hybrid PolSAR: Swath width, PRF, data rate, ytem deign. L-band ALOS-(JAXA), C-band RCM (CSA) and L-/S-band NI-SAR (NASA-ISRO). π/4 Mode: π/ Mode: Receive V π/4 Tranmit: (HH+VV) π/4 Receive H C Receive V Receive V Tranmit: (HH jjvv) H RISAT- (π/-rctlr) Right or Left Circular Tranmit (RCT or LCT) H Linear Receive (LR)

3 3 ndia RISAT- C-band SAR Senor Firt pace-borne SAR ytem with hybrid polarimetric mode. Launched by ISRO on April 6 th, from India. Sytem parameter Frequency Antenna type and ize Orbit Altitude PRF Polarization Detail 5.35 GHz Patch array antenna (dimenion:6mxm) 536 km 3 Hz 35 Hz Single, dual, circular and quad (no phae) Incidence angle.5 to 55. Reolution Swath width Repeat cycle -m (HRS), 3-6m(FRS), 5m(MRS) and 5m (CRS) xkm (HRS), 5x5Km (FRS), 5Km (MRS) and 3KM (CRS) 5 day (MRS mode) & day (CRS mode) SAR Look and Beam Direction Left Looking Right Looking (Oppoite to International terminology)

4 4 Wallerfing Tet Site RiSAT- Time Serie Data Acquiition Red Box : Area of Interet Date of Acquiition Satellite Pa Mode of Acquiition Polarization AOI 9 / 4 / 4 Decending Right Circular FRS- Hybrid RH/RV / 5 / 4 Decending Right Circular FRS- 7 / 6 / 4 Acending Right Circular FRS- 8 / 7 / 4 Decending Right Circular FRS- 4 / 8 / 4 Decending Right Circular FRS- 8/ 9 / 4 Decending Right Circular FRS- Hybrid RH/RV 48. Hybrid RH/RV 7. Hybrid RH/RV 35. Hybrid RH/RV 4. Hybrid RH/RV 39. 6/ / 4 Decending Right Circular FRS- Hybrid RH/RV 35. Fine Reolution Stripmap (FRS) - reolution :.3 x 3.3 m (Rg x Az) Triangular Meteo (TRI) Big Bare(BB) (AMS)

5 5 Time Serie of Ground Data Collection

6 6 Time Serie of Ground Data Collection

7 Hybrid Polarimetric Decompoition PolSAR i enitive to the geometrical propertie (ize, hape, orientation, denity) and the dielectric propertie (permittivity, alinity) of catterer. Hybrid (circular polarization) PolSAR interaction with target i different from fully PolSAR (linear polarization). Decompoition into elementary cattering mechanim: Hybrid decompoition theory. 7

8 8 Hybrid Wave Polarimetry RCTLR hybrid PolSAR (RISAT-) meaure a projection of complex cattering matrix: E E RH RV S S The Jone Vector of a monochromatic electro-magnetic wave: Wave Coherency Matrix: Stoke Repreentation: Real Repreentation g HH VH S S HV VV j S S HH VH js js HV VV RH RV iδ x ERH ae x RH J iδ y E RV ae y RV T RH RH J J RH RV RV RV RH g + g g + jg3 g jg3 g g [ ] [ ] J RV [ J ] g RH + RV g g g RH RV g Re RH RV g3 g3 Im RH RV g ( ) ( ) Complex Repreentation Total Power H or V polarized Power RH RV 45 /35 linear polarized Power Circularly polarized Power

9 m-α Hybrid Decompoition (9th of April,4) Stoke Parameter (g, g, g, g3) baed m-α hybrid decompoition theorem, f odd g. m. m-α decompoition TRI (Cloude et al. ) + co α Blue f even g. m. co α Red f diffue g. ( m) Green g + g g AMS + g + g 3 where m and α atan g g 3 BB Decompoition parameter: g Total Power m Degree of Polarization (-m) Degree of De-Polarization α Scattering Mechanim 9

10 Model-baed Hybrid Polarimetric Decompoition Cloude model-baed hybrid polarimetric decompoition of the Stoke vector: polarized (oil urface) + random volume (vegetation) cattering component g g g g 3 Data Decompoition parameter: m StoV m Surface-to-Volume Ratio Degree of Polarization m g + g g v + g 3 m v g (/ ) g m + in α coφ in α inφ co α Volume + Surface m ( m) min ε d m ( α α ) ( ig ) Soil Surface Scattering Mechanim g + g α atan 45 < α < 45 g 3 ϕ arg g + Inverion of urface cattering component via α Comparion of α m from IEM with the decompoed α d from data for different ε. Inverion of ε uing minimization

11 [ J ] Derivation of Hybrid α for IEM RH RH RV RHRV RV Model IEM hybrid polarimetric wave coherency matrix in term of linear polarization: j HH HH VV HHVV For IEM Model with reflection Imymmetry: HHHV HHHV + HVVV VV + HH HV + HV VV Im VVHV Allain High Frequency aumption: HV (k and kl cancel out!) j VV + j HV HV j HV HV RCTLR hybrid polarimetric wave coherency matrix for IEM Model (No roughne-induced depolarization): [ J ] RH RH RV RHRV j HH RV HH VV j HHVV VV Allain, S(3). Charactériation d un ol nu àpartir de donnée SAR polarimétrique Etude multifréquentielle et multi-réolution. PhD Thei, Univerity of Renne, France

12 [ J ] Derivation of Hybrid α for IEM Model x wave coherency matrix in term of Stoke vector: RH RHRV HH j HHVV g + g g + jg3 g jg3 g g RH RV RV j HH VV VV 4 unknown are olved with 4 equation: g HH + VV, g HH VV, g Im HHVV, g3 Re HHVV atan 45 < < 45 g + g Hybrid α α α g 3 For IEM High Frequency IEM f HF α [ ] [ ] ( ) ( ) Hybrid α for IEM High frequency (X- and C-band): atan [ ( )].5 f f + Im( f f ) hh ( ε, θ ), VV f ( ε, θ ) HH f Re [ ] hh vv ( f f ) vv hh vv 45 < α < 45

13 3 Hybrid α for IEM Model and Data Senitivity Analyi of α -model Hybrid α for RISAT- Data Wallerfing, April Hybrid α [ ] [ ] Dielectric Contant Senitivity of α decreae with riing ε and increae with θ inc. All urface catterer and agriculture field are between and 45. Model-baed hybrid polarimetric decompoition oil inverion over both, bare and vegetated oil.

14 4 Methodology of Hybrid Polarimetric Soil Moiture Inverion RISAT- Data Radiometric calibration RISAT- Hybrid-Pol SLC Hybrid-Pol IEM Model Hybrid-Pol channel in term of linear polarization Create [J] wave coherency matrix Speckle filtering Box-Car 9x9 window ize Stoke parameter Calculation Hybrid polarimetric decompoition α d min ε d m ( α α ) Create [J] wave coherency matrix Aumption: Reflection ymmetry + HF Stoke parameter calculation Hybrid polarimetric decompoition α m Dobon converion model Dielectric contant (ε ) Soil moiture

15 5 Inverion Reult within the Wallerfing Area Mv (%) (With out Mak) Image Smooth : 5x5 April 4 Beginning of growing Seaon [vol.%] [vol.%] Conformity Coefficient CCg 3 /g [-] (Bare oil dominate) Surface Scattering Volume Scattering Dihedral Scattering

16 Time Serie of m-α Decompoition RGB Image April 9, 4 θ35 Augut 4, 4 May 5, 4 θ48 September 8, 4 June 7, 4 July 8, 4 θ7 θ35 October 6, 4 R : g. m. co α G : g. ( m) B : g. m. θ4 θ39 + co α θ35 Ditinct variation of cattering cenario over agricultural growing eaon 6

17 Time Serie of Decompoed Hybrid α April 9, 4 θ35 May 5, 4 θ48 June 7, 4 July 8, 4 θ7 θ Potentially Invertible 9 (θ-dependent) -9 θ4 θ39 θ35 NonInvertible [-] 7

18 Time Serie Soil Moiture Inverion Reult for IEM May April θ35 θ Inverion Rate (%) September θ4 8 θ48 Augut [vol.%] June 6 5 July July IEM:θ7 Inverion Rate October θ35 Big Bare Meteo Triangular 4 3 θ35 -AprSmooth: 5-May 7-Jun Image 5x5 8-Jul 4-Aug 8-Sep October Day of Year (4) 8

19 9 IEM-Validation with in itu for Bare oil FDR Theta Probe Rough Bare Field RMSE5.74 (9 th of April, 4) Smooth Bare Field RMSE5.85 RMSE3. RMSE5.69 BB AMS RMSE6.94 Sampling Box Validity Criterion 3 5% 3 TRI

20 IEM: Validation of Time Serie RMSE:5.56 Winter wheat Inverion April θ35. Bare oil Wheat Height: -cm Plant moiture: ---- RMSE:.9 Winter wheat May θ48. Height: 4-5cm Plant moiture: 8% RMSE:4. Winter wheat June θ7. Height: 4-5cm Plant moiture: 8-9% RMSE:7. Winter wheat July θ35. Height: 4-6cm Plant moiture: -8%

21 IEM: Validation of Time Serie RMSE:7.4 Winter wheat Inverion Augut θ4. Height: 4-3cm Plant moiture: ---- RMSE:.86 Winter wheat September θ39. Height: 4-5cm Plant moiture: 8% RMSE:3.69 Winter wheat October θ35. Bare Soil (trong roughne) Intermediate Crop Height: cm Plant moiture: -----

22 Concluion Development of a hybrid model-baed decompoition and Inverion algorithm for oil moiture (under vegetation cover) at C-band. Application of the hybrid polarimetric oil moiture retrieval algorithm on time erie data (including bare and vegetation covered oil) uing the IEM (no depolarization term) + Random Volume Model: Inverion Rate: -3% (crop), 3-75% (bare oil). Firt oil moiture inverion from RISAT- data uing a phyically-baed decompoition and inverion model. Validation: For all crop and all date, an overall RMS error i from 9.3 to vol.% for the IEM Model including the entire vegetation growing eaon and all the variation in vegetation phenology and oil condition. Bare oil moiture inverion uing IEM : 3. to 5.7 vol.% with 3-75% inverion rate. Outlook: Incluion of variable vegetation volume in the retrieval cenario: IEM + Variable Volume. Checking the applicability of other urface cattering model : X-Bragg

23 Thank You Very Much for Your Attention!