Synergy of L-band and optical data for soil moisture monitoring O. Merlin, J. Walker and R. Panciera 3 rd NAFE workshop 17-18 sept. 2007.

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Presentation transcript:

Synergy of L-band and optical data for soil moisture monitoring O. Merlin, J. Walker and R. Panciera 3 rd NAFE workshop sept. 2007

Objective Use synergy optical/passive microwave for improving 1. Accuracy (passive microwave scale) OR 2. Spatial resolution (downscaling) of L-band derived soil moisture retrievals

Data Regional area of NAFE’06 1km resolution PLMR data: TB 1km resolution MODIS (Terra/Aqua) data: Tsurf, NDVI

Illustration Impact of SM and vegetation on TB and Tsurf Carlson et al., 1995

Illustration Impact of SM on TB and Tsurf 75K 25K 4K 7K

Illustration Impact of vegetation on TB and Tsurf 65K 15K 2K 5K

TBSMRetrieval algo LAI Illustration Impact of vegetation on TB: multi-spectral retrieval Sensitivity of Tsurf to SM: downscaling TB/SM Tsurf Downscaling algo SM Synergy L-band/optical

1. SM retrieval RT model: - TAU-OMEGA formalism Mo et al., soil roughness (H,Q) Wang and Choudhury, Teff = f(Tsurf,T2) Wigneron et al., TAU = bVWC Jackson and Schmugge, 1991 Inverse model: Minimize (TBobs - TBsim) 2 SMRetrieval algo Tsurf MODIS TB PLMR LAI MODIS Teff = f(Tsurf,T2) VWC = 0.5 LAI

1. SM retrieval Application to NAFE’06 regional area (Yanco) Assumptions: veg para, roughness uniform Standing water = Bare soil with SM 100% v/v Retrieval algo TBHAngle SM TsurfLAI

1. SM retrieval Comparison with ground measurements at the PLMR scale Model parameters: Sand = 30% Clay = 30% b = 0.15 OMEGA = 0.05 T2 = 20degC H = 0.1 RMSE = 3.2% v/v Bias ~ 10 % v/v 70% of pixels30% of pixels

km 0 818> Preliminary SM product SM (% v/v)

2. SM downscaling Downscaling algo MODIS SM MODIS SM NDVI Tsurf Test a downscaling technique of ~40km SMOS like data from MODIS data

2. SM downscaling Approach: SEF (soil evaporative fraction) as a proxy of surface soil moisture MODIS SEF derived from triangle method Ta Tmax NDVI Tsurf NDVImin NDVImax Tsoil

2. SM downscaling A downscaling relationship

2. SM downscaling Modified downscaling relationship One difficulty: the non-linearity of SEF to SM Generated SM (% v/v) EF (% v/v) SEF

2. SM downscaling Modified downscaling relationship SEF model Komatsu, 2003

2. SM downscaling Correlation between MODIS SEF and PLMR SM SM sensitivity of Tsurf ~ SM sensivity of TB /10

2. SM downscaling Limitations and applicability: Dry-end conditions (Tmax) Uncertainty in SEF is high: need to aggregate to lower resolution Could account for heterogeneity of soil

Conclusions Illustrated two applications of the synergy between optical and passive microwave data Preliminary SM product with accuracy ~4% v/v for 70% of the validation area (fitted with roughness H) An example of downscaling technique of SMOS type data from 1km MODIS type data Some questions: - stripes on PLMR TB images - bias in retrieved SM over 30% validation pixels (not explained by any parameter) -…