[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7780/kjrs.2008.24.5.427

Radar Remote Sensing of Soil Moisture and Surface Roughness for Vegetated Surfaces

Oh, Yi-Sok (Department of Electronic and Electrical Engineering, Hongik University)

Publication Information

Korean Journal of Remote Sensing / v.24, no.5, 2008 , pp. 427-436 More about this Journal

Abstract

This paper presents radar remote sensing of soil moisture and surface roughness for vegetated surfaces. A precise volume scattering model for a vegetated surface is derived based on the first-order radiative transfer technique. At first, the scattering mechanisms of the scattering model are analyzed for various conditions of the vegetation canopies. Then, the scattering model is simplified step by step for developing an appropriate inversion algorithm. For verifying the scattering model and the inversion algorithm, the polarimetric backscattering coefficients at 1.85 GHz, as well as the ground truth data, of a tall-grass field are measured for various soil moisture conditions. The genetic algorithm is employed in the inversion algorithm for retrieving soil moisture and surface roughness from the radar measurements. It is found that the scattering model agrees quite well with the measurements. It is also found that the retrieved soil moisture and surface roughness parameters agree well with the field-measured ground truth data.

Keywords

Scattering model; inversion algorithm; soil moisture; surface roughness; vegetated surfaces; genetic algorithm;

Citations & Related Records

Reference

1	De Roo, R. D., Y. Du, F. T. Ulaby, and M. C. Dobson, 2001. A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion, IEEE Trans. Geosci. Remote Sensing, 39(4): 864-872 DOI ScienceOn
2	Oh, Y., K. Sarabandi, and F. T. Ulaby, 2002. Semiempirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces, IEEE Trans. Geosci. Remote Sensing, 40(6): 1348-1355 DOI ScienceOn
3	Oh, Y. and J. Y. Hong, 2007. Re-examination of analytical models for microwave scattering from deciduous leaves, IET Microwaves, Antennas, Propag., 1(3): 617-623 DOI ScienceOn
4	Oh, Y., 2004. Quantitative retrieval of soil moisture content and surface roughness from multi polarized radar observations of bare soil surfaces, IEEE Trans. Geosci. Remote Sensing, 42(3): 596-601 DOI ScienceOn
5	Bindlish R. and A. P. Barros, 2001. Parameterization of vegetation backscatter in radar-based, soil moisture estimation, Remote Sensing of Environment, 76: 130-137 DOI ScienceOn
6	Ulaby, F. T. and C. Elachi, 1990. Radar Polarimetry for Geoscience Applications, Artech House
7	Oh, Y., 2006. Robust inversion technique for retrieving soil moisture from multi-polarized backscatter of a bare surface, IEE Electronics Letters, 42(2): 414-415 DOI ScienceOn
8	Ulaby, F. T., M. K. Moore, and A. K. Fung, 1982. Microwave Remote Sensing, Active and Passive, vol. 2, Artech House. Norwood, MA, USA
9	Hallikainen, T., F. T. Ulaby, M. C. Dobson, M. A. El-Rayes, and L. Wu, 1985. Microwave dielectric behavior of wet soil, Part-I: Empirical models and experimental observation, IEEE Trans. Geosci. Remote Sensing, 23: 25-34 DOI ScienceOn
10	Tsang, L., J. A. Kong, and R. T. Shin, 1985. Theory of Microwave Remote Sensing, 1st ed., John Wiley and Sons
11	Sikdar, M., S. Macintosh, I. Cumming, and B. Brisco, 2005. Incorporating a vegetation index into a soil moisture retrieval model: Results from Conair-580 SAR data, IGARSS 2005, Seoul, Korea, Digest, pp. 383-386