DocumentCode
882727
Title
A semiempirical surface backscattering model for bare soil surfaces based on a generalized power law spectrum approach
Author
Loew, Alexander ; Mauser, Wolfram
Author_Institution
Dept. of Earth & Environ. Sci., Univ. of Munich, Germany
Volume
44
Issue
4
fYear
2006
fDate
4/1/2006 12:00:00 AM
Firstpage
1022
Lastpage
1035
Abstract
An adequate characterization of surface roughness is crucial to obtain reliable backscatter simulation results from existing analytical backscattering models. The surface roughness is typically characterized using root mean square height, autocorrelation length, and shape of the autocorrelation function. For the solution of inverse problems it is of interest to reduce the number of unknown surface parameters. Simplified backscattering models are required in this context. The paper introduces a new semiempirical backscattering model in C-band for rough dielectric surfaces which is based on the integral equation model. It is shown that a surface roughness description can be reduced using a single surface roughness parameter. To account for the high variability of autocorrelation function types, the proposed model is based on a generalized power law spectrum approach which mediates between Gaussian and exponential correlated surfaces. The approach is validated against analytical backscatter simulations and laboratory-measured microwave signatures, and the surface parameter retrieval capabilities of the suggested model are investigated.
Keywords
backscatter; data acquisition; inverse problems; microwave measurement; remote sensing; soil; surface roughness; C-band; Gaussian surfaces; autocorrelation function; autocorrelation length; bare soil surfaces; exponential correlated surfaces; generalized power law spectrum; integral equation; inverse problems; microwave remote sensing; microwave signatures; root mean square height; rough dielectric surfaces; surface backscattering model; surface parameter retrieval; surface roughness; Analytical models; Autocorrelation; Backscatter; Context modeling; Inverse problems; Root mean square; Rough surfaces; Shape; Soil; Surface roughness; Inverse problems; microwave remote sensing; rough surfaces; surface scattering;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2005.862501
Filename
1610837
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