Soil moisture content assessment based on Landsat 8 red, near-infrared, and thermal channels

Soil moisture content (SMC) plays an important role in different environmental. In this study, four different soil moisture indices, namely, SOMID, SOMID-FS, SOMID-FT, and CSOMID-FT, were introduced. In this work, the following parameters were used to estimate SMC at a depth of 5 cm: (a) the distance of pixels from the origin in the scatter-plot of near-infrared (NIR) and red bands (SNIR-R), (b) the fraction of soil cover in each pixel, and (c) the land surface temperature. It was concluded that the CSOMID-FT was the most accurate index for estimation of SMC (RMSE = 0.045, R = 0.92). This index divides the SNIR-R into three separate regions based on the pixels' normalized difference vegetation index (NDVI) values and assigns a specific regression equation to each region. The results showed that as the NDVI values increase, the accuracy of the proposed indices decreases. Furthermore, the SOMID-FT and CSOMID-FT were used to estimate SMC at five different depths of 5, 10, 20, 50, and 100 cm. It was concluded that the satellite-estimated SMC was highly correlated with the field-measured data at 5-cm soil depth. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)