DocumentCode
1266027
Title
A generalized power law spectrum and its applications to the backscattering of soil surfaces based on the integral equation model
Author
Li, Qin ; Shi, Jiancheng ; Chen, K.S.
Author_Institution
Inst. for Computational Earth Syst. Sci., California Univ., Santa Barbara, CA, USA
Volume
40
Issue
2
fYear
2002
fDate
2/1/2002 12:00:00 AM
Firstpage
271
Lastpage
280
Abstract
A generalized power law spectrum is proposed to describe the random rough surfaces in this paper. The parameters of the spectrum are related to the traditional physical parameters of root mean square (rms) height and correlation length. It can naturally reduce to the spectra of Gaussian and exponential correlation functions. The corresponding correlation functions are also derived. It can provide wider range of spectra to describe the random rough surfaces than other spectra. Based on the proposed spectrum, backscattering of soil surfaces is studied by using the integral equation model (IEM). The simulation results are compared with the experimental measurements of real soil surfaces at L, C, and X bands for the different roughness scales and moisture conditions. The reasonably good agreements between the measurements and the simulations are observed for all three-frequency bands and different incidence angles with the same sets of the physical roughness parameters
Keywords
backscatter; geophysical techniques; radar cross-sections; radar theory; remote sensing by radar; rough surfaces; soil; terrain mapping; C-band; L-band; SHF; UHF; X-band; backscattering; exponential correlation function; generalized power law spectrum; geophysical measurement technique; integral equation model; land surface; radar remote sensing; random rough surface; simulation; soil; terrain mapping; Backscatter; Integral equations; Moisture measurement; Probability distribution; Response surface methodology; Rough surfaces; Scanning probe microscopy; Soil measurements; Soil moisture; Surface roughness;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/36.992784
Filename
992784
Link To Document