Application of Neural Network with Er- Ror Correlation and Time Evolution for Re- Trieval of Soil Moisture and Other Vegeta- Tion Variables

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 polarizations (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 × 5m 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 55◦ is the best suited to observe composite effect of vegetation ladyfinger biomass (Bm) and vegetation covered soil moisture at Xband. This analysis is further used for retrieval of soil moisture and Corresponding author: D. Singh ([email protected]).