Estimation of the soil moisture and its influencing factors using an integration approach of sentinel-2 and GLDAS data: A case study of Bagdad city, Iraq

Remote sensing techniques have shown that soil moisture can be estimated using several satellite images, each with its own set of advantages and limitations. This study aims to apply the integration approach of Sentinel-2 and the Global Land Data Assimilation System (GLDAS) to estimate the surface soil moisture and its influencing factors in Baghdad City, central Iraq. The GLDAS/Noah model with 0.25° resolution and monthly temporal resolution was used to generate a soil moisture map for the first 10 cm of the land surface for the study area. The results showed that the estimated soil moisture values ranged between 11% and 29%, where the high percentage was in the center of the study area and gradually decreased in all directions around the study area. Six important factors, namely depth of groundwater, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), topography, soil texture and land use/land cover were compared with the estimated soil moisture to show which is the more influential. The result show that there is a good relationship between the depth of groundwater and calculated soil moisture where the depth of the groundwater was low, ranging between 11–13 m, in areas where the soil moisture is high, ranging from 27–29%.