An assessment of remotely sensed surface and root zone soil moisture through active and passive sensors in northeast Asia

Abstract

Active and passive microwave remote sensing techniques provide an effective way to observe soil moisture contents. We validated Advanced Scatterometer (ASCAT) and Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor products using estimations from nine different stations located in the Korean peninsula, in northeast Asia from May 1 to September 30, 2010. The results of the surface soil moisture (SSM) products showed a reasonable agreement with the average correlation coefficient (R) values of 0.39, 0.42, and 0.53 for the National Snow and Ice Data Centre (NSIDC), Vrije Universiteit Amsterdam - National Aeronautics and Space Administration (VUA-NASA) AMSR-E, and ASCAT SSM datasets, respectively. The root zone soil moisture (RZSM) products, derived using the NSIDC soil water index (SWI), the United States Department of Agriculture (USDA) AMSR-E, and the ASCAT SWI datasets showed relatively high R values of 0.47, 0.72, and 0.75, respectively, with in situ soil moisture at a depth of 20cm. In particular, AMSR-E USDA RZSM data show best agreements with in-situ data at 20cm, among the four depths (10, 20, 30, and 50cm). In this study, the ASCAT SSM and SWI were rescaled based on the porosity and the effective saturation according to soil texture. Renormalized soil moisture products using three renormalization methods: the linear regression correction (REG), average-standard deviation (μ-σ), and cumulative distribution function (CDF) provided an improvement in biases and RMSEs, with SSM (SWI) RMSEs of 0.04 (0.02), 0.05 (0.03), and 0.05 (0.03)m3/m3 for REG, μ-σ, and CDF matching, respectively. A Taylor diagram was used to assess the accuracy of four satellite soil moisture products with in situ data on a plot. Based on these results, ASCAT soil moisture products were potentially proven to be more appropriate than AMSR-E products in northeast Asia. Remotely sensed soil moisture datasets from passive (AMSR-E) and active (ASCAT) sensors are beneficial to operational hydrological investigations and water management activities.