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Characterization of the coherent scattering induced by ridging patterns in agriculture by the use of polarimetric SAR imagery.

Authors :
Zhao, Lingli
Yang, Jie
Li, Pingxiang
Huang, Xin
Shi, Lei
Zhang, Liangpei
Source :
International Journal of Remote Sensing. Jun2017, Vol. 38 Issue 12, p3502-3518. 17p.
Publication Year :
2017

Abstract

This article investigates the scattering characteristics of ridging patterns in agriculture by the use of C-band polarimetric synthetic aperture radar (PolSAR) images. The polarimetric signatures of periodic potato fields and row wheat in different directions are highlighted using a set of polarimetric parameters. Enhanced coherent scattering is observed when the alignment direction of the ridging patterns is perpendicular to the radar’s line of sight (LOS). The dominant backscattering mechanism of the ridging patterns is deduced by evaluating different polarimetric parameters. The increased copolarized backscattering coefficients and copolarized correlation coefficient, and the reduced entropy and polarimetric alpha angle, indicate a strong contribution of odd scattering to ridging patterns aligned perpendicular to the LOS. We also compare the dominant contributions to the backscattering of ridging patterns in different phenological stages. Although the canopy changes of potato and wheat with time are significant, the underlying periodic surface changes the dominant scattering mechanism of potato fields over all the phenological stages, and the wheat aligned parallel with the flight direction of radar still has relatively high coherent scattering in the different vegetation development stages. The variability analyses undertake in this study allow a more detailed documentation of the physical scattering process of the ridging patterns in agriculture, and will improve the applicability of synthetic aperture radar images in agriculture. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01431161
Volume :
38
Issue :
12
Database :
Academic Search Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
122101114
Full Text :
https://doi.org/10.1080/01431161.2017.1297545