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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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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
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Data Regional area of NAFE’06 1km resolution PLMR data: TB 1km resolution MODIS (Terra/Aqua) data: Tsurf, NDVI
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Illustration Impact of SM and vegetation on TB and Tsurf Carlson et al., 1995
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Illustration Impact of SM on TB and Tsurf 75K 25K 4K 7K
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Illustration Impact of vegetation on TB and Tsurf 65K 15K 2K 5K
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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
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1. SM retrieval RT model: - TAU-OMEGA formalism Mo et al., 1982 - soil roughness (H,Q) Wang and Choudhury, 1981 - Teff = f(Tsurf,T2) Wigneron et al., 2001 - 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
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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
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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
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322 320 318317313 311309308307306 304 40km 0 818>402533 Preliminary SM product SM (% v/v)
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2. SM downscaling Downscaling algo MODIS SM MODIS SM NDVI Tsurf Test a downscaling technique of ~40km SMOS like data from MODIS data
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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
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2. SM downscaling A downscaling relationship
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2. SM downscaling Modified downscaling relationship One difficulty: the non-linearity of SEF to SM Generated SM (% v/v) EF (% v/v) SEF
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2. SM downscaling Modified downscaling relationship SEF model Komatsu, 2003
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2. SM downscaling Correlation between MODIS SEF and PLMR SM SM sensitivity of Tsurf ~ SM sensivity of TB /10
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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
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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) -…
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