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Soil moisture retrievals using L-band radiometry from variable angular ground-based and airborne observations.

Authors :
Zhao, Tianjie
Hu, Lu
Shi, Jiancheng
Lü, Haishen
Li, Shangnan
Fan, Dong
Wang, Pingkai
Geng, Deyuan
Kang, Chuen Siang
Zhang, Ziqian
Source :
Remote Sensing of Environment. Oct2020, Vol. 248, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

Surface soil moisture is a vital variable in the process of energy exchange between the land and atmosphere. Monitoring the surface soil moisture at the local and global scales has become feasible due to the development of microwave remote sensing. With the new development of potential satellite missions, it is important to evaluate existing soil moisture retrieval algorithms, which will greatly contribute to the improvement of current soil moisture products and the development of new methodologies. This paper compared the performance of four well-known soil moisture retrieval algorithms with L-band radiometry at fixed incidence angles, including the single channel algorithm at horizontal polarization (SCA-H), the single channel algorithm at vertical polarization (SCA-V), the dual channel algorithm (DCA), and the land parameter retrieval model (LPRM). The experimental data used for evaluation was from the Soil Moisture Experiment in the Luan River (SMELR), which consists of variable angular ground-based and airborne observations covering a wide range of incidence angles (22.5°–55°) at L-band. The microwave radiative transfer models are set to be consistent to guarantee that the four different algorithms are comparable. The results showed that the retrieval accuracy of the SCA-H and SCA-V is significantly affected by the input vegetation optical depth, and the calibration of vegetation parameters should be considered in the implementation of the SCA-H and SCA-V. The DCA does not rely on the auxiliary vegetation information and can also achieve good performance for both the soil moisture and vegetation optical depth. However, its retrieval requires a penalty on parameter constraints since the input brightness temperatures at horizontal and vertical polarization are correlated. The LPRM has a poor performance at incidence angles less than 30°, as it analytically utilizes the polarization difference in the brightness temperature, which is quite small at lower incidence angles. The accuracy of four soil moisture algorithms achieve their best performances at intermediate incidence angles of 40° to 45°, and is slightly degraded when the incident angles increased to larger than 50°, which is contributed to the increasing vegetation effects and depolarization that leads to an information loss. These findings provide quantitative evidence to help understand the differences in various current soil moisture algorithms and further promote the development of new methodologies for future soil moisture missions. • Evaluation of soil moisture retrieval algorithms for various vegetation types. • Vegetation parameters show angular dependence especially at vertical polarization. • Intermediate angles from 40 to 45 degree are optimal for soil moisture retrieval. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
248
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
145494846
Full Text :
https://doi.org/10.1016/j.rse.2020.111958