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Airborne Passive microwave response to soil moisture: A case study for the Rur catchment Sayeh Hasan (1), Carsten Montzka (1), Heye Bogena (1), Chris Rüdiger.

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Presentation on theme: "Airborne Passive microwave response to soil moisture: A case study for the Rur catchment Sayeh Hasan (1), Carsten Montzka (1), Heye Bogena (1), Chris Rüdiger."— Presentation transcript:

1 Airborne Passive microwave response to soil moisture: A case study for the Rur catchment Sayeh Hasan (1), Carsten Montzka (1), Heye Bogena (1), Chris Rüdiger (2) and Harry Vereecken (1) (1) Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG 3), Jülich, Germany (2) Monash University, Department of Civil Engineering, Australia Airborne passive microwave remote sensing in L band provides a feasible option for high resolution mapping of near surface soil moisture that allows both large spatial coverage and resolution. A series of multi- resolution flights was conducted over the Rur Catchment, a TERENO observatory, in the west of Germany. Brightness temperature observed by Polarimetric L-band multibeam radiometer (PLMR) was mapped 3 times at different altitude in descending order (1200m 1000m and 700m). Soil moisture is estimated using the inversion of L-band Microwave Emission of the Biosphere (L-MEB) model, which simulates the L-band microwave emissions produced by the soil–vegetation layer. Fig 2: Enviscope Partenavia PA68 D-GERY aircraft Fig 1: Polarimetric L-band multibeam radiometer Counts Tb raw Tb cal,geo,filt Tb cal,geo,filt,T Tb cal,geo,filt,T,angle Tb cal,geo Tb cal Calibration: Cold target sky (4K), warm target box, linear regression Filtering: RFI detection, role > 2.5° Temperature correction: internal T drift Angle Normalization : 38° beam Geocorrection : DEM, aircraft movements Conversion: Prosensing conversion tools Plots of Tb cal,geo,filt,T,angle Convert to raster, shp, kml format Data Processing Chain Measurements are taken across long temporal scales(several hours) The geometry of PLMR results in 3 different viewing angles (±8°, ±22°, ±38°). PLMR data have to be standardized to a certain temperature and also to a chosen angle Brightness Temperature Fig 3:Data processing chain of PLMR data Fig 4: a)Brightness temperature map for Rur catchment and the zoom leveled are for altitudes b) 700m, c)1000m, d)1200m at Selhausen test site Introduction DFG/Transregio32 Fig 5: a)Soil moisture map for Rur catchment and the zoom leveled are for altitudes b) 700m, c)1000m, d)1200m at Selhausen test site Soil moisture retreived by L-MEB (a) (d) (c) (b) (d) (c) (a) L-MEB Reference J. P. Wigneron, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, P. Richaume, P. Ferrazzoli, P. de Rosnay, R. Gurney, J. C. Calvet, J. P. Grant, M. Guglielmetti, B. Hornbuckle, C. Matzler, T. Pellarin, and M. Schwank, "L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields," Remote Sensing of Environment, vol. 107, pp. 639- 655, Apr 30 2007. T. J. Jackson, "Multiple Resolution Analysis of L-Band Brightness Temperature for Soil Moisture," IEEE Transactions on Geoscience and Remote Sensing, vol. 39,No.1, pp. 151-164, January 2001. Conclusion The consistency between patterns of TB at different resolutions is notable. These patterns are well defined in the 250m resolution and still observed in the 400m resolution although generalized and smoothed. Field experiments are a valuable database for the validation of L-band sensors on aircraft or satellites. The observed soil moisture was not significantly different from the In-situ values. Radio Frequency Interference (RFI) effect is less at lower altitudes. Fig 6:LAI map generated from Rapideye satellite Outlook


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