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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/2041

Title: Snow wetness estimation in Himalayan snow covered regions using ENVISAT-ASAR data - art. no. 641008
Authors: SINGH, G
KUMAR, V
MOHITE, K
VENKATRAMAN, G
RAO, YS
SNEHMANI
Keywords: synthetic-aperture radar
sir-c/x-sar
backscattering
density
ghz
Issue Date: 2006
Publisher: SPIE-INT SOC OPTICAL ENGINEERING
Citation: Microwave Remote Sensing of the Atmosphere and Environment V,6410,41008-41008
Abstract: The snow wetness in the Himalayan snow covered region is an important parameter, for the snow melt runoff modeling and forecasting. The main objective of the study is to estimate snow wetness in parts of Himalayan snow covered regions. Snow surface backscattering can expressed as function of permittivity of snow. Reflectivity at the air snow interface increases greatly with wetness and volume scattering decreases abruptly. ENIVISAT-ASAR dual polarization (HH&VV) data have been used to investigate permittivity and snow wetness in sub Himalayan region. Raw data have been processed for backscattering coefficient (BSC) image generation for HH and VV polarization. BSC image is geo-referenced and topographically corrected using high precision digital elevation model (DEM). The BSC images are despeckled using adaptive filter technique. For this study Physical optics Model (POM) for surface scattering based inversion model has been used. Physical Optics Model based inversion model gives the permittivity which can be further related for estimating snow wetness. A comparison was done between inversion model estimated snow wetness and field values of snow wetness in the study region. Comparison with field measurement showed that the correlation coefficient for snow wetness estimated from ASAR data was 0.8 at 95% confidence interval. The snow wetness ranges from 0-15% by volume.
URI: http://dx.doi.org/10.1117/12.693690
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15316
http://hdl.handle.net/100/2041
ISBN: 978-0-8194-6517-7
ISSN: 0277-786X
Appears in Collections:Proceedings papers

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