Soil moisture is a key capricious in hydrological process, the accessibility of moisture content in soil reins the mechanism amid the land surface and atmospheric progression. Precise soil moisture determination is influential in the weather forecast, drought monitoring, hydrological modeling, agriculture management and policy making. The aims of the study were to estimate soil moisture through remotely sensed data (FTIR & optical) and establishment of the results with field measured soil moisture data. The ground measurements were carried out in 0–15 cm depth. Permutation of normalized difference vegetation index (NDVI) and land surface temperature (LST) were taken to derive temperature vegetation dryness index (TVDI) for assessment of surface soil moisture. Correlation and regression analysis was conceded to narrate the TVDI with in situ calculated 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 adequate in temporal variation of surface soil moisture. The triangle method (TVDI) confers consistent appraisal of moisture situation and consequently can be used to evaluate the wet conditions. Furthermore, the appraisal of soil moisture using the triangular method (TVDI) was possible at medium spatial resolutions because the relationship of soil moisture with LST and NDVI lends an eloquent number of representative pixels for developing a triangular scatter plot.