Application of MSMR brightness temperature for retrieval of land surface parameters

Application of MSMR brightness temperature for retrieval of land surface parameters

Results and Discussion
On comparison the plots of TB v/s frequency of IRS P4, Nimbus 7 and Theoretical calculations it is seen that there is a decrease in the value of TB for IRS P4 at 18 GHz.

Figure 1: shows plots for TB at horizontal polarizations with frequency for (A) Theoretical calculations, (B) for Nimbus 7 and (C) for IRS P4.
Plot (C) shows after 10.65 GHz the value of TB decreases for 18 GHz and then again increases for 21 GHz. While in other two cases (A) and (B), value of 18 GHz is more than the 10.65 GHz. Thus calculation are done at other three frequencies i.e. 6.6 GHz, 10.65 GHz and 21 GHz for the month of September.

The graphs of TB v/s Days are plotted for Nimbus 7 for 1978, IRS P4 for 2001 and Theoretical calculations are made for the values from Benchmark soil of India [1].

Figure 2: plots shows the variation of brightness temperature. Curve at higher TB is for vertical polarization and one with lower TB is for horizontal polarizations at 6.6 GHz frequency for Nimbus 7(a), IRS P4(b) and Theoretical calculations ( c).
These plots are compared to see the variations of TB throughout the year for the Area of interest. Theoretical curve is drown taking average of TB over a month. It is seen that around month of may there is a decrease in the TB because of soil moisture present and due to the effect of vegetation water content. In the similar way the simulations are made for all the ranges temperatures, soil moisture, and vegetation water content. These simulations can be compared with the actual values of TB from satellite so that to get perfect match with satellite data.

Conclusion
The results obtained using above technique closer resemblance with the actual ground values of surface parameters. Thus using satellite data it is possible to get idea of the nature of the surface and vegetation presence, which can be used effectively weather forecasting, hydrologists, agriculturist, etc. It has been seen that, microwave polarization difference gives more accurate estimation of vegetation water content and soil moisture. Thus it has been tried to use this difference in inversion technique to get better results in future.

References

Benchmarks Soil of India, national bureau of soil survey and land used planning. (University of Agricultural Science, Bangalore India.
Eni G. Njoku, Retrieval of Land Surface Parameters Using Passive Microwave Measurments at 6 - 18 GHz. IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, NO. 1, January 1999.
Myron C.Dobson, et.al, Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Model, Member IEEE.

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