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WE4.T04.3_THE POTENTIAL OF COSMO-SKYMED SAR IMAGES IN MAPPING SNOW COVER AND SNOW WATER EQUIVALENT_2011.July 24.pptx
 

WE4.T04.3_THE POTENTIAL OF COSMO-SKYMED SAR IMAGES IN MAPPING SNOW COVER AND SNOW WATER EQUIVALENT_2011.July 24.pptx

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    WE4.T04.3_THE POTENTIAL OF COSMO-SKYMED SAR IMAGES IN MAPPING SNOW COVER AND SNOW WATER EQUIVALENT_2011.July 24.pptx WE4.T04.3_THE POTENTIAL OF COSMO-SKYMED SAR IMAGES IN MAPPING SNOW COVER AND SNOW WATER EQUIVALENT_2011.July 24.pptx Presentation Transcript

    • - Microwave Remote Sensing Group The Potential of Cosmo-Skymed SAR Images in Mapping Snow Cover and Snow Water Equivalent M. Brogioni1, S. Pettinato1, E. Santi1, S. Paloscia1, P. Pampaloni1, E. Palchetti1, J. Shi2,3, C. Xiong1,2, 1Institute of Applied Physics - IFAC-CNR, Firenze, Italy 2Institute for Remote Sensing Applications, Beijing, China 3University of California, Santa Barbara (CA), USA 1 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Outline Motivations The ASI Cosmo-Skymed mission and data Model investigations Experimental Results Retrieval of Snow cover and Snow Water Equivalent 2 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group IntroductionSeveral experiments have documented the ability of C-band SAR in mapping the extent of wet snow. But thehigh transmissivity of dry snow cover at this frequencymakes difficult to detect it.The study aims at evaluating the potential of X-bandCOSMO-Skymed SAR in generating snow cover mapsand estimating snow water equivalent 3 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group The ASI/Cosmo-Skymed mission 4 medium-size satellites, equipped with an X-band SAR HH, VV, HV, VH pol sun-synchronous orbit at ~620km heightFull constellationrevisit 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 4 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Example of COSMO-Skymed dataTemporal variation of backscattering on alpine regionsCSK® © ASI CSK 2, Himage, HH, = 26.5° IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Investigation: Snow backscattering model AIR  Snow as a single layer of identical z=0 S scatterers SNOW z=-d  Flat air-snow interfaceGROUND  Rough snow –soil interface Multiple scattering effects Snow volume scattering DMRT-QCA Mie Scattering (Tsang et al., 2007) Stickyness Surface scattering AIEM (Chen et al., 2004) 6 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group The surface scattering: The AIEM model o k kc c qp (S ) qp (S ) qp (S ) qp (S ) The normalized scattering coefficient is composed of three terms: Kirchhoff, cross and the complementary one. 7 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Volume scattering: The DMRT/QCA Model (Tsang et al. 2007) 2 2 d I , ,z cos ke I , , z d sin d P , ; , I , , z dz 0 0 2 2 d sin d P , ; , I , , z 0 0 2 I1 s P11 0 0 0 I1i P11 f11 q P33 P44 2 I 2s 0 P22 0 0 I 2i P22 f 22 q P43 P34 *U12 s 0 0 P33 P34 U12i P33 Re f11 f 22 q *V12 s 0 0 P43 P44 V12 i P34 Im f11 f 22 q N max i 1 2n 1 ( M ) ( M )f11 Tn X n n cos Tn( N ) X n N ) ( n cos 1 R k Kr n 1 n n 1 N max i 1 2n 1 ( M ) ( M )f 22 Tn X n n cos Tn( N ) X n N ) ( n cos 1 R k Kr n 1 n n 1 8 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations (DMRT – QCA model) Frequency (GHz) 5.3, 9.6, 17.2 Polarization VV, HH, HV Incidence angle (deg) 20 - 50 Density (Kg/m3) 200 - 500 Grain radius (mm) 0.1 - 1.5 Snow depth (cm) 20 - 300 Soil smoothData chosen to account for the different type of snow cover on the Alps 9 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations Extinction and Penetration depth Density Crystal Frequency Penetration depth (1/ke) radius Band (m) (mm) 250 Kg/m3 350 Kg/m3 Radius C 66.8 81.9 0.5 X 9.5 17.5 Ku 1.2 2.5 C 18.8 39.3 0.9 X 2.3 5.31 Ku 0.33 0.67 C 7.4 17.8 1.3 X 0.99 2.16 Ku 0.15 0.29 10 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing GroupSensitivity of backscattering to grain radius 11 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations: Sensitivity to SWE Crystal radius: 0.1 mm – Incidence angle: 35° SWE SWEBackscattering (dB) Density 150-400 5.3 GHz 9.6 GHzTotal scattering SWESnow contribution Backscattering (dB) Soil contribution 12 17.2 GHz IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations: Sensitivity to SWE Crystal radius: 0.3 mm – Incidence angle: 35° SWE (mm) SWE (mm)Backscattering (dB) Backscattering (dB) 5.3 GHz 9.6 GHz Total scattering SWE (mm) Snow contribution Backscattering (dB) Soil contribution 13 17.2 GHz IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations: Sensitivity to SWE Crystal radius: 0.5 mm – Incidence angle: 35° SWE (mm) SWE (mm)Backscattering (dB) Backscattering (dB) 5.3 GHz 9.6 GHz Total scattering SWE (mm) Snow contribution Backscattering (dB) Soil contribution 17.2 GHz 14 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model Simulations 5.3 GHz 9.6 GHz 17.2 GHz Sensitivity to SWEBackscattering 15 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing GroupExperimental sensitivity to Snow Depth:Temporal trends Wet snow SWE 16 Depth Hoar IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Generation of snow cover maps and Retrieval of SWE 17 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Principle of the algorithm clear sky dry/wet snow snow coverOptic clouds ? snow cover + SWE wet snow SAR clear cloudy wet snow Threshold dry snow ANN SWE Ref. Image DEM + air temperature for high SWE values 18 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing GroupValidation of SWE Algorithm with experimental X-band data Date Sensor Sensor mode Polarization 08/03/2009 CSK2 STR_HIMAGE HH 27/05/2009 CSK2 STR_HIMAGE HH 14/07/2009 CSK2 STR_HIMAGE HH 22/01/2010 CSK2 STR_HIMAGE HH 26/03/2010 CSK2 STR_PINGPONG VV/VH 29/03/2010 CSK1 STR_PINGPONG VV/VH 02/09/2010 CSK1 STR_PINGPONG VV/VH 19 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group First verification of SWE Algorithm with exper. data 22/01/2010 08/03/2009 27/05/2009 SWE SWE SWE SWE SWE SWE (200 (300 SWE NN (200 (300 SWE NN (200 (300 SWE NN Kg/m3) Kg/m3) Kg/m3) Kg/m3) Kg/m3) Kg/m3) Single Monti Ornella 272 408 270 500 750 masked 194 291 wet snow polarization Col dei Baldi 268 402 350 574 861 544 90 135 wet snow Pradazzo 192 288 280 306 459 400 no data no data - Ravales 280 420 masked 488 732 masked 260 390 masked Cherz 200 300 290 240 360 270 no data no data - 26/03/2010 29/03/2010 SWE SWE SWE SWE (200 Kg/m3) (300 Kg/m3) SWE NN (200 Kg/m3) (300 Kg/m3) SWE NNDual polarization Monti Ornella 304 456 380 332 498 438 (co & cross ) Col dei Baldi 296 444 390 294 441 masked Cima Pradazzo 204 306 masked 198 297 masked Ravales 304 456 378 332 498 480 Cherz 270 405 masked 230 345 masked 20 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Example of Snow Cover Area 40 Km SWEJanuary 22, 2010 March 29, 2011 21 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Summary and conclusions 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 40-50 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 22 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group 23 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model simulations Sensitivity of X band backscattering to snow density Snow depth : 1 m - Grain radius : 0.5 mm 24 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group 25 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Model investigations : Snow-pack scattering ^ Z •Density  AIR •Depth z=0 •Size/shape of z=-d 1 crystals z=-d 2 • Liquid water SNOW contet z=-d N-2 z=-d N-1 •Height St Dev • Correlation length z=-d N • AutocorrelationGROUND function 26 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Test of SWE Algorithm with simulated data10000 input values randomly varied:5000 for training - 5000 for testSnow depth =10 - 150 cmDensity = 200-300 kg/m3Grain radius = 0.1 – 1.0 mmIncidence angle = 20 -70 Single polarization (RMSE=~ 32 mm) 600 y = 0.9495x + 11.107 R2 = 0.9342 500 400 SWE calcolato (mm) 300 200 100 0 0 100 200 300 400 500 600 SWE m isurato (m m ) Dual polarization (RMSE=~ 25 mm) 27 IGARSS 2011, July 23-29, Vancouver, Canada
    • - Microwave Remote Sensing Group Generation of dry/wet snow cover maps04/05/2009 100 km SAR SAR + MODIS MODIS wet snow 04/05/2009 snow cover 28 IGARSS 2011, July 23-29, Vancouver, Canada