An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data
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RESEARCH ARTICLE
An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data Liangliang Tao1,2 • Jing Li1,2 • Xi Chen1,2 • Qingkong Cai3 • Yunfei Zhang1,2
Received: 23 November 2015 / Accepted: 8 September 2016 Ó Indian Society of Remote Sensing 2016
Abstract This study investigated an appropriate method for soil moisture retrieval from radar images and coincident ground measurements acquired over bare soil and sparsely vegetated regions. The adopted approach based on a single scattering integral equation method (IEM) was developed to establish the relationship between backscatter coefficient and surface soil parameters including volumetric soil moisture content and surface roughness. The performance of IEM in 0–7.6 cm is better than that in 0–20 cm. Moreover, IEM can simulate correctly the backscatter coefficients only for the root mean square (RMS) height s \ 1.5 cm at C-band and s \ 2.5 cm at L-band by using an exponential correlation function and for s [ 1.5 cm at C-band and s [ 2.5 cm at L-band by using Gaussian function. However, due to the difficulties involved in the parameterization of soil surface roughness, the estimated accuracy is not satisfactory for the inversion of IEM. This paper used a combined roughness parameter and Fresnel reflection coefficient to develop an empirical model. Simulations were performed to support experimental results and to highlight soil moisture content and surface roughness effects in different polarizations. Results showed that a good agreement was found between the IEM simulations and the SAR measurements over a wide range of soil
& Jing Li [email protected] 1
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2
Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China
3
Institute of Civil Engineering, Henan Institute of Engineering, Zhengzhou 451191, China
moisture and surface roughness characteristics. The model had a significant operational advantage in soil moisture retrieval. The correlation coefficients were 77.03 % at L-band and 81.45 % at C-band with the RMSEs of 0.515 and 0.4996 dB, respectively. Additionally, this work offered insight into the required application accuracy of soil moisture retrieval at a large area of arid regions. Keywords Soil moisture SAR IEM Autocorrelation function Backscatter coefficient Surface roughness
Introduction Synthetic aperture radar (SAR) is a promising option for monitoring surface parameters and has important applications in agricultural studies, in particular for soil moisture estimation (Engman and Chauhan 1995; Wang et al. 1997). The radar signal is correlated with radar parameters and has a close relationship with soil surface roughness and soil moisture content (Rakotoarivony et al. 1996; Zribi and Dechambre 2003; Holah et al. 2005). In the past four decades, many surface scattering models were widely applied to retrieve the value of soil moisture using SAR data. Empirical
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