2009-06-15
Application of Neural Network with Error Correlation and Time Evolution for Retrieval of Soil Moisture and Other Vegetation Variables
By
Progress In Electromagnetics Research B, Vol. 15, 245-465, 2009
Abstract
Present paper utilizes the time evolution for estimating the soil moisture and vegetation parameter with Radar remote sensing data. For this purpose, vegetation ladyfinger has been taken as a test field and experimental observations have been taken by bistatic scatterometer at X-band in the regular interval of 10 days for both like polarization (i.e., Horizontal-Horizontal, HH-; Vertical-Vertical, VV-) and at different incidence angles. At this interval, all the vegetation parameters and scattering coefficient have been recorded and computed. Three similar types of field of size 5 x 5 m have been especially prepared for this purpose. The observed data is critically analyzed to understand the effect of incidence angle and polarization effect on scattering coefficient of the ladyfinger. It is observed that VV-polarization gives better result than HH-polarization and incidence angle 55ο is the best suited to observe composite effect of vegetation ladyfinger biomass (Bm) and vegetation covered soil moisture at X-band. This analysis is further used for retrieval of soil moisture and biomass of ladyfinger using Neural Network. The important aspect of the retrieval algorithm is that it includes the time evolution. The retrieval results for soil moisture and Bm are in good agreement with the actual values of the soil moisture and biomass.
Citation
Dharmendra Singh, Vandita Srivastava, Basant Pandey, and Devesh Bhimsaria, "Application of Neural Network with Error Correlation and Time Evolution for Retrieval of Soil Moisture and Other Vegetation Variables," Progress In Electromagnetics Research B, Vol. 15, 245-465, 2009.
doi:10.2528/PIERB09043003
References

1. Bracaglia, M., P. Ferrazzoli, and L. Guerriero, "A fully polarimetric multiple scattering model for crops," Remote Sensing Environ., Vol. 54, 170-179, 1995.
doi:10.1016/0034-4257(95)00151-4        Google Scholar

2. Del Frate, F., P. Ferrazzoli, L. Guerriero, T. Strozzi, U. Wegmuller, G. Cookmartin, and S. Quegan, "Wheat cycle monitoring using radar data and a neural network trained by a model," IEEE Transaction on Geoscience and Remote Sensing, Vol. 42, 35-44, 2004.
doi:10.1109/TGRS.2003.817200        Google Scholar

3. Del Frate, F., P. Ferrazzoli, and G. Schiavon, "Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks," Remote Sensing Environ., Vol. 84, 174-183, 2003.
doi:10.1016/S0034-4257(02)00105-0        Google Scholar

4. Ferrazzoli, P., S. Palsocia, P. Pampaloni, G. Schiavon, S. Sigismondi, and D. Solimini, "The potential of multifrequency polarimetric SAR in assessing agricultral and arboreous biomass," IEEE Transaction on Geoscience and Remote Sensing, Vol. 35, No. 1, 5-17, 1997.
doi:10.1109/36.551929        Google Scholar

5. Franceschetti, G., A. Iodice, S. Maddaluno, and D. Riccio, "A fractal based theoretical framework for retrieval of surface parameters from electromagnetic bakscattering data," IEEE Transaction on Geoscience and Remote Sensing, Vol. 38, No. 2, 641-650, 2000.
doi:10.1109/36.841994        Google Scholar

6. Henderson, F. M. and A. J. Lewis, Manual of Remote Sensing, Vol. 2, John Wiley & Sons, Inc, 1998.

7. Huang, E. X. and A. K. Fung, "Electromagnetic wave scattering from vegetation with ODD pinnate compound leaves," Journal of Electromagnetic Waves and Applications, Vol. 19, No. 2, 231-244, 2005.
doi:10.1163/1569393054497339        Google Scholar

8. Karam, M. A., A. K. Fung, R. H. Lang, and N. S. Chauhan, "A Microwave scattering model for layered vegetation," IEEE Transaction on Geoscience and Remote Sensing, Vol. 30, No. 4, 767-784, July 1992.
doi:10.1109/36.158872        Google Scholar

9. Kim, S. B., B. W. Kim, Y. K. Kong, and Y. S. Kim, "Radar backscattering measurements of rice crop using X-band scalterometer," IEEE Transaction on Geoscience and Remote Sensing, Vol. 38, No. 3, 2000.        Google Scholar

10. Kurosu, T., S. Uratsuka, H. Maeno, and T. Kozu, "Texture statistics for classification of land use with multitemporal. JERS-1, SAR single-look imagery," IEEE Transaction on Geoscience and Remote Sensing, Vol. 37, No. 1, 1999.
doi:10.1109/36.739157        Google Scholar

11. Le Toan, T., F. Ribbes, L. F. Wang, N. F. Floury, K. H. Ding, J. A. Kong, M. Fujita, and T. Kurosu, "Rice croping mapping and monitoring using ERS-1 data based on experiment and modeling results," IEEE Transaction on Geoscience and Remote Sensing, 41-56, 1997.
doi:10.1109/36.551933        Google Scholar

12. Pulliainen, J. T., P. J. Mikhela, M. T. Hallikainen, and J.-P. Ikonen, "Seasonal dynamics of C-band Backscatter of boreal forests with applications to biomass and soil moisture estimation," IEEE Transaction on Geoscience and Remote Sensing, Vol. 34, 758-770, 1996.
doi:10.1109/36.499781        Google Scholar

13. Saatchi, S. S. and M. Moghaddam, "Estimation of crown and stem water content and biomass of boreal forest using polarimetric SAR imagery," IEEE Transaction on Geoscience and Remote Sensing, Vol. 38, No. 2, 2000.
doi:10.1109/36.841999        Google Scholar

14. Singh, D. and V. Dubey, "Microwave bistatic polarization measurements for retrieval of soil moisture with incidence angle approach," Journal of Geophysics and Engineering, Vol. 4, 75-82, Published by Institute of Physics, IoP, U. K., 2007.        Google Scholar

15. Singh, D., "Scatterometer performance with polarization discrimination ratio approach to retrieve crop soybean parameter at X-band," International Journal of Remote Sensing, Vol. 27, No. 19, 4101-4115, 2006.
doi:10.1080/01431160600735988        Google Scholar

16. Singh, D. and S. K. Sharan, "Microwave response to broad leaf vegetation (spinach) and vegetation covered soil for remote sensing," Journal of Indian Society of Remote Sensing, Vol. 28, 2001.        Google Scholar

17. Toure, A., K. P. B. Thomson, G. Edwards, R. J. Brown, and B. G. Brisco, "Adaptation of the MIMICS backscattering model to the agriculturalcontext-wheat and canola at L and C bands," IEEE Transaction on Geoscience and Remote Sensing, 1994.        Google Scholar

18. Ulaby, F. T., R. K. Moore, and A. K. Fung, "Microwave remote sensing (active and passive),", Vol. 1-3, Addision-Wesely Publishing Company, Reading, MA, 1982.        Google Scholar