Spatiotemporal monitoring of surface soil moisture using optical remote sensing data: a case study in a semi-arid area

Abstract

Surface soil moisture content (SSMC) monitoring constitutes an important parameter to estimate crop water requirements, especially in arid and semi-arid areas. Remote sensing became a useful tool for estimating SSMC. Two approaches were applied for monitoring the SSMC during the 2013/14 cropping season in the irrigated perimeter of Tadla (Morocco) using multispectral bands of Landsat-8 OLI images. The first approach examined the potential of visible and short-wave infrared drought index (VSDI), normalized multi-band drought index (NMDI) and short-wave infrared water stress index (SIWSI), to retrieve SSMC. The second approach attempted to develop a new SSMC model based on evaluation of the correlations between multispectral bands and measured SSMC using a stepwise multiple regression analysis. Results showed that the established model is highly correlated with the measured SSMC at all crop growth stages with R2 of 0.87, 0.85 and 0.89, for bare soil, partially covered and entirely covered by vegetation, respectively.