- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 1 M. Brogioni 1, S. Pettinato 1, E. Santi 1, S. Paloscia 1, P. Pampaloni 1,

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Presentation transcript:

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 1 M. Brogioni 1, S. Pettinato 1, E. Santi 1, S. Paloscia 1, P. Pampaloni 1, E. Palchetti 1, J. Shi 2,3, C. Xiong 1,2, 1 Institute of Applied Physics - IFAC-CNR, Firenze, Italy 2 Institute for Remote Sensing Applications, Beijing, China 3 University of California, Santa Barbara (CA), USA The Potential of Cosmo-Skymed SAR Images in Mapping Snow Cover and Snow Water Equivalent

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Outline  Motivations  The ASI Cosmo-Skymed mission and data  Model investigations  Experimental Results  Retrieval of Snow cover and Snow Water Equivalent 2

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Introduction 3  Several experiments have documented the ability of C- band SAR in mapping the extent of wet snow. But the high transmissivity of dry snow cover at this frequency makes difficult to detect it.  The study aims at evaluating the potential of X-band COSMO-Skymed SAR in generating snow cover maps and estimating snow water equivalent

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada The ASI/Cosmo-Skymed mission 4 4 medium-size satellites, equipped with an X-band SAR HH, VV, HV, VH pol sun-synchronous orbit at ~620km height Full constellation revisit time : 12 h - 1 Spotlight mode, for metric resolutions over small images - 2 Stripmap modes, for metric resolutions over tenth of km images; one mode is polarimetric with images acquired in two polarizations - 2 ScanSAR for medium to coarse (100 m) resolution over large swath

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Example of COSMO-Skymed data CSK 2, Himage, HH,  = 26.5° Temporal variation of backscattering on alpine regions CSK® © ASI

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model Investigation: Snow backscattering model  Snow as a single layer of identical scatterers  Flat air-snow interface  Rough snow –soil interface DMRT-QCA (Tsang et al., 2007) Multiple scattering effects Mie Scattering Stickyness Snow volume scattering 6 Surface scattering AIEM (Chen et al., 2004)

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 7 The surface scattering: The AIEM model The normalized scattering coefficient is composed of three terms: Kirchhoff, cross and the complementary one.

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Volume scattering: The DMRT/QCA Model (Tsang et al. 2007) 8

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model Simulations (DMRT – QCA model) 9 Data chosen to account for the different type of snow cover on the Alps Frequency (GHz)5.3, 9.6, 17.2 PolarizationVV, HH, HV Incidence angle (deg) Density (Kg/m 3 ) Grain radius (mm) Snow depth (cm) Soilsmooth

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model Simulations Extinction and Penetration depth 10 Radius Density

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Sensitivity of backscattering to grain radius 11

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model Simulations: Sensitivity to SWE Crystal radius: 0.1 mm – Incidence angle: 35° 12 Backscattering (dB) 5.3 GHz SWE Total scattering Snow contribution Soil contribution 9.6 GHz SWE Density SWE 17.2 GHz Backscattering (dB)

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 17.2 GHz SWE (mm) Backscattering (dB) GHz Backscattering (dB) SWE (mm) Total scattering Snow contribution Soil contribution 5.3 GHz SWE (mm) Backscattering (dB) Model Simulations: Sensitivity to SWE Crystal radius: 0.3 mm – Incidence angle: 35°

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 14 Total scattering Snow contribution Soil contribution 17.2 GHz SWE (mm) Backscattering (dB) 5.3 GHz SWE (mm) Backscattering (dB) Model Simulations: Sensitivity to SWE Crystal radius: 0.5 mm – Incidence angle: 35° 9.6 GHz SWE (mm) Backscattering (dB)

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model Simulations Sensitivity to SWE GHz 9.6 GHz 17.2 GHz Backscattering

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Experimental sensitivity to Snow Depth:Temporal trends 16 Wet snow  SWE Depth Hoar

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 17 Generation of snow cover maps and Retrieval of SWE

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Principle of the algorithm 18 DEM + air temperature Optic SAR clear sky snow cover wet snow clouds ? dry snow SWE snow cover + SWE wet snow dry/wet snow clear cloudy Ref. Image Threshold ANN for high SWE values

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Validation of SWE Algorithm with experimental X-band data 19 DateSensorSensor modePolarization 08/03/2009CSK2STR_HIMAGEHH 27/05/2009CSK2STR_HIMAGEHH 14/07/2009CSK2STR_HIMAGEHH 22/01/2010CSK2STR_HIMAGEHH 26/03/2010CSK2STR_PINGPONGVV/VH 29/03/2010CSK1STR_PINGPONGVV/VH 02/09/2010CSK1STR_PINGPONGVV/VH

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada First verification of SWE Algorithm with exper. data 20 22/01/201008/03/200927/05/2009 SWE (200 Kg/m 3 ) SWE (300 Kg/m 3 ) SWE NN SWE (200 Kg/m 3 ) SWE (300 Kg/m 3 ) SWE NN SWE (200 Kg/m 3 ) SWE (300 Kg/m 3 ) SWE NN Monti Ornella masked194291wet snow Col dei Baldi wet snow Pradazzo no data - Ravales280420masked488732masked260390masked Cherz no data - 26/03/201029/03/2010 SWE (200 Kg/m 3 ) SWE (300 Kg/m 3 ) SWE NN SWE (200 Kg/m 3 ) SWE (300 Kg/m 3 ) SWE NN Monti Ornella Col dei Baldi masked Cima Pradazzo masked198297masked Ravales Cherz masked230345masked Single polarization Dual polarization (co & cross )

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Example of Snow Cover Area 21 January 22, 2010 March 29, 2011 SWE 40 Km

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Summary and conclusions 22  The sensitivity of ASI/Cosmo-Skymed X-band SAR to snow cover and SWE has been investigated by using experimental results and model simulations.  An algorithm to generate snow cover maps by combining optical and SAR data has been developed and validated  It has been found that X-band data can contribute to the retrieval of SWE for snow depth higher than about cm and relative high crystal size.  More investigations and data validations are needed to demonstrate the full potential of Cosmo-Skymed SAR in snow detection Aknowledgment This work has been funded by the Italian Space Agency (ASI) under the COSMO-Skymed project 1720

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 23

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model simulations Sensitivity of X band backscattering to snow density 24 Snow depth : 1 m - Grain radius : 0.5 mm

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 25

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Model investigations : Snow-pack scattering 26 Density Depth Size/shape of crystals Liquid water contet Height St Dev Correlation length Autocorrelation function

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada Test of SWE Algorithm with simulated data input values randomly varied: 5000 for training for test Snow depth = cm Density = kg/m 3 Grain radius = 0.1 – 1.0 mm Incidence angle = 20°-70° Single polarization (RMSE=~ 32 mm) Dual polarization (RMSE=~ 25 mm)

- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada MODIS snow cover Generation of dry/wet snow cover maps 04/05/2009 SAR wet snow SAR + MODIS 04/05/ km 28