Abstract:
Soil moisture is a key variable in hydrological process, as the availability of moisture content in soil controls the mechanism between the land surface and atmospheric processes. Accurate soil moisture estimation is decisive in weather forecast, drought monitoring, hydrological modeling, agriculture management and policy making. The objective of the study was to estimate soil moisture using remote sensed data (Fourier Transform Infra-Red spectroscopy& optical) and validation of the results with field measured soil moisture data. The ground measurements were carried out at 0-15cm depth. Combination of Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were used to derive Temperature Vegetation Dryness Index (TVDI) for assessment of surface soil moisture. Correlation and regression analysis was carried out to relate the TVDI with in-situ measured soil moisture. The spatial pattern of TVDI shows that generally low moisture distribution over study area. A significant (p < 0.05) negative correlation of r=0.79 was found between TVDI and in-situ soil moisture. The TVDI was also found satisfactory in temporal variation of surface moisture. The triangular method (TVDI) provides reliable estimate of moisture condition and hence can be used to assess the moisture conditions. Furthermore, the estimation of soil moisture using the triangular method (TVDI) was possible at medium spatial resolutions because the relationship of soil moisture with LST and NDVI provide significant number of representative pixels for developing a triangular scatter plot.
