A simplified physically-based algorithm for surface soil moisture retrieval using AMSR-E data

doi:10.1007/s11707-014-0412-4

Front. Earth Sci.

2014, Vol. 8

Issue (3) : 427-438 https://doi.org/10.1007/s11707-014-0412-4

RESEARCH ARTICLE

A simplified physically-based algorithm for surface soil moisture retrieval using AMSR-E data

Jiangyuan ZENG^1,²,Zhen LI¹,Quan CHEN^1,^*(

),Haiyun BI^1,²

1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2. University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

A simplified physically-based algorithm for surface soil moisture inversion from satellite microwave radiometer data is presented. The algorithm is based on a radiative transfer model, and the assumption that the optical depth of the vegetation is polarization independent. The algorithm combines the effects of vegetation and roughness into a single parameter. Then the microwave polarization difference index (MPDI) is used to eliminate the effects of surface temperature, and to obtain soil moisture, through a nonlinear iterative procedure. To verify the present algorithm, the 6.9 GHz dual-polarized brightness temperature data from the Advanced Microwave Scanning Radiometer (AMSR-E) were used. Then the soil moisture values retrieved by the present algorithm were validated by in-situ data from 20 sites in the Tibetan Plateau, and compared with both the NASA AMSR-E soil moisture products, and Soil Moisture and Ocean Salinity (SMOS) soil moisture products. The results show that the soil moisture retrieved by the present algorithm agrees better with ground measurements than the two satellite products. The advantage of the algorithm is that it doesn’t require field observations of soil moisture, surface roughness, or canopy biophysical data as calibration parameters, and needs only single-frequency brightness temperature observations during the whole retrieval process.

Keywords passive microwave remote sensing soil moisture inversion AMSR-E SMOS

Corresponding Author(s): Quan CHEN

Issue Date: 04 July 2014

Cite this article:

Jiangyuan ZENG,Zhen LI,Quan CHEN, et al. A simplified physically-based algorithm for surface soil moisture retrieval using AMSR-E data[J]. Front. Earth Sci., 2014, 8(3): 427-438.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-014-0412-4
https://academic.hep.com.cn/fesci/EN/Y2014/V8/I3/427

Fig.1 The flow chart of the proposed algorithm for surface soil moisture retrieval.

Fig.2 Location of the 20 sites of the Maqu soil moisture monitoring network. CST and NST represent the names of these sites.

Fig.3 Temporal variations of averaged NDVI at the Maqu network region during the entire period.

Fig.4 Temporal variations of averaged soil moisture and soil temperature at 5 cm at the Maqu network region during the entire period.

Fig.5 Time series comparison of soil moisture retrieved by the present inversion algorithm and two satellite soil moisture products (NASA AMSR-E and SMOS) with in-situ average soil moisture at 5 cm. (a) 2008.7.1–2008.10.31; (b) 2009.4.1–2009.10.31; (c) 2010.4.1–2010.7.31.

Tab.1 Error statistics of Algorithm_SM, NASA_SM, and SMOS_SM, with respect to the In-situ_SM. STD (Standard deviation), Bias, MAE (Mean absolute error), RMSE (Root mean square error) are in m³·m^–3

Fig.6 Histogram of the distribution of mean absolute error between in-situ soil moisture, at 5 cm, and estimated soil moisture. (a) Algorithm_SM; (b) NASA_SM; (c) SMOS_SM; (d) all of three soil moisture retrievals.

Fig.7 Scatter plots comparison of soil moisture retrieved by the present inversion algorithm and two satellite soil moisture products (NASA AMSR-E and SMOS) with in-situ average soil moisture at 5 cm during the entire period.

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