Paper
15 November 2007 Improved model for dielectric behavior of moist saline soil
Huaze Gong, Yun Shao, Jinghui Liu, Qingrong Hu
Author Affiliations +
Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 67871T (2007) https://doi.org/10.1117/12.750386
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
This paper introduces a new amendment dielectric model in the microwave band concerning the principle of soil science which can also give the information about soil texture and variety of soluble salt ions, and points out some errors of original model at the same time. The new model is confirmed suitable for saline soil with different levels of moisture and salinity soil samples prepared in lab. Based on the research on the dielectric properties of saline and alkali soils, this paper also brings forward the feasibility of separating them. Contrasts to the classic dielectric models of soil, all the parameters of the improved model have their physical meanings, and the procedures avoid neglecting principle of soil science and optimization blindly. So the parameters can give us more information about moist saline soil. This study sums up dielectric properties of moist soil, and adds salt-affected factor. Thus we can describe dielectric behavior of moist saline soil more precisely. In further research it pays attention to the relationship between dielectric properties and backscattering coefficients or polarimetric information extracted from radar image.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huaze Gong, Yun Shao, Jinghui Liu, and Qingrong Hu "Improved model for dielectric behavior of moist saline soil", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67871T (15 November 2007); https://doi.org/10.1117/12.750386
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Cited by 5 scholarly publications.
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KEYWORDS
Soil science

Dielectrics

Ions

Data modeling

Sodium

Microwave radiation

Statistical modeling

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