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Application of MSMR brightness temperature for retrieval of land surface parameters

Parag S. Narvekar
Parag S. Narvekar
Center of Studies in Resources Engineering (CSRE), Indian Institute of Technology (IIT) Bombay, Powai Mumbai 400 076
Email: parag_narvekar@yahoo.com



Introduction
Multi Scanning Microwave Radiometer (MSMR) provides data for Brightness Temperature (TB) at four different frequencies 6.6 GHz, 10.65 GHz, 18 GHz and 21 GHz, at Vertical and Horizontal Polarizations. From the previous studies there are various models provided for estimating soil moisture, vegetation water content, surface roughness, etc. Due to the complexity of equations used, it is a tedious task to obtain these parameters with better accuracy. In the present work, 50 by 50 Km area at Bikaner Rajasthan, India is considered and the TB data of MSMR of IRS P4, SMMR of Nimbus 7 and theoretical calculations are compared. Plots of TB v/s frequency shows an unexpected fall in TB values at 18 GHz frequency of IRS P4 indicating some problem at 18 GHz of IRS P4. thus the measurements at 6.6 GHz, 10.65 GHz and 21 GHz are considered. Referring to data from "Benchmarks of India" [1], the TB is calculated for range of soil moisture, vegetation water content, surface roughness values etc., for 50 by 50 Km area of Bikaner. These results are compared with TB data of Nimbus 7 and IRS P4 satellites for the retrieval of land surface parameters with better accuracy.

Theory
Brightness Temperature as a function of soil moisture, vegetation water content, and surface roughness is given as [2]

Where
TBp is the polarization at vertical or horizontal brightness temperature.
Rsp is rough surface reflectivity.
tc is the vegetation opacity.
wp is the single scattering albedo.

Relation for Rsp and tc are same as given in [3].


where Rr is the rough surface reflectivity at look angle q, and h is


Rp is the refractivity of smooth surface and is given by






Thus for the ranges of soil moisture, vegetation water content and if required surface roughness, for the area under study, the simulations can be made and the results can be compared with satellite data sets for estimation of Land surface parameters.

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