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

Mohammad Reza Mobasheri; Meisam Amani

doi:10.1117/1.JRS.10.026011

26 April 2016 Soil moisture content assessment based on Landsat 8 red, near-infrared, and thermal channels

Mohammad Reza Mobasheri, Meisam Amani

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 2, 026011 (April 2016). https://doi.org/10.1117/1.JRS.10.026011

Abstract

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.

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Mohammad Reza Mobasheri and Meisam Amani "Soil moisture content assessment based on Landsat 8 red, near-infrared, and thermal channels," Journal of Applied Remote Sensing 10(2), 026011 (26 April 2016). https://doi.org/10.1117/1.JRS.10.026011

Published: 26 April 2016

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