Soil Moisture Retrieval in Agricultural Fields Using Adaptive   Model-Based Polarimetric Decomposition of SAR Data

doi:10.1109/TGRS.2016.2542214

CORC > 北京大学 > 地球与空间科学学院

	Soil Moisture Retrieval in Agricultural Fields Using Adaptive Model-Based Polarimetric Decomposition of SAR Data
	He, Lian ; Panciera, Rocco ; Tanase, Mihai A. ; Walker, Jeffrey P. ; Qin, Qiming
刊名	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
	2016
关键词	Agricultural fields polarimetric decomposition synthetic aperture radar (SAR) polarimetry soil moisture L-BAND SAR SCATTERING MODEL SURFACE-ROUGHNESS MICROWAVE-SCATTERING RADAR OBSERVATIONS COHERENCY MATRIX WHEAT FIELDS TIME-SERIES VEGETATION BACKSCATTERING
DOI	10.1109/TGRS.2016.2542214
英文摘要	The aim of this paper was to estimate soil moisture in agricultural crop fields from fully polarimetric L-band synthetic aperture radar (SAR) data through the polarimetric decomposition of the SAR coherency matrix. A nonnegative-eigenvalue-decomposition scheme, together with an adaptive volumescattering model, is extended to an adaptive model-based decomposition (MBD) (Adaptive MBD) model for soil moisture retrieval. The Adaptive MBD can ensure nonnegative decomposed scattering components and allows two parameters (i.e., the mean orientation angle and a degree of randomness) to be determined to characterize the volume scattering. Its performance was tested using airborne SAR data and coincident ground measurements collected over agricultural fields in southeastern Australia and compared with previous MBD methods (i.e., the Freeman three-component decomposition using the extended Bragg model, the Yamaguchi three-component decomposition, and an iterative generalized hybrid decomposition). The results obtained with the newly proposed decomposition scheme agreed well with expectations based on observed plant structure and biomass levels. The new method was superior in tracking soil moisture dynamics with respect to previous decomposition methods in our study area, with root-mean-square error of soil moisture estimations being 0.10 and 0.14 m(3)/m(3), respectively, for surface and double-bounce components. However, large variability in the achieved soil moisture accuracy was observed, depending on the presence of row structures in the underlying soil surface.; National Natural Science Foundation of China [41230747, 41401375]; China Scholarship Council; Australian Research Council [DP0984586, LE0882509, FS100100040]; SCI(E); EI; ARTICLE; helian_2006@126.com; pancerarocco@gmail.com; mihai76@gmail.com; jeff.walker@monash.edu; qmqin@pku.edu.cn; 8; 4445-4460; 54
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/437075]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	He, Lian,Panciera, Rocco,Tanase, Mihai A.,et al. Soil Moisture Retrieval in Agricultural Fields Using Adaptive Model-Based Polarimetric Decomposition of SAR Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2016.
APA	He, Lian,Panciera, Rocco,Tanase, Mihai A.,Walker, Jeffrey P.,&Qin, Qiming.(2016).Soil Moisture Retrieval in Agricultural Fields Using Adaptive Model-Based Polarimetric Decomposition of SAR Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING.
MLA	He, Lian,et al."Soil Moisture Retrieval in Agricultural Fields Using Adaptive Model-Based Polarimetric Decomposition of SAR Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2016).