Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval
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Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema


The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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[1] F. Mattia, and T. Le Toan, "Backscattering properties of multi-scale rough surfaces". Journal of Electromagnetic Waves and Applications, 13: 493-528, 1999.
[2] F. Mattia, and T. Le Toan, " An analytical, numerical, and experimental study of backscattering from multi-scale soil surfaces." Radio Science, Volume 36, Number 1 : 119-135, 2001.
[3] L.E. Church,. "Fractal surface finish." Applied Optics, vol.27, n.8, 1998.
[4] M. Davidson, T. Le Toan, F. Mattia, G. Satalino, T. Manninen, and M. Borgeaud,. "On the characterisation of agricultural soil roughness for radar sensing studies." IEEE Trans. Geosc.Rem.Sens., 38: 630-640, 2000.
[5] C.A. Guerin, M. Holschneider, and M. Saillard, "Electromagnetic scattering from multi-scale rough surfaces." Waves Random Media, 7: 331-349, 1997.
[6] I. Daubechies, "Ten lectures on Wavelet". CBMS-NFS Lecture Notes, NR.61, SIAM, 1992.
[7] S.G. Mallat, "Theory of multi-resolution signal decomposition: The Wavelet representation", IEEE Trans.Pattern analysis and machine intelligence, vol II., 7, 1989.
[8] L. Bennaceur, Z. Belhadj, and M. R. Boussema. "A study of radar backscattering multi-scale bi dimensional surface", The 2002 IEEE International Geoscience and Remote Sensing Symposium and the 24 th Canadian Symposium on Remote Sensing, Toronto, Canada, June 2002.
[9] A.K. Fung, Z. Li, and K.S. Chen, "Backscattering from a randomly rough dielectric surface". IEEE Trans.Geosc.Rem.Sensing, 30 : 356-363, 1992.
[10] A.K. Fung, Microwave scattering and emission models and their applications Artech House, 1994.
[11] R. M. Axline, and A.K. Fung, "Numerical computation from a perfectly conducting random surface", IEEE, Trans.Antennas Propagat., 26 : 488- 582, 1978.
[12] T. K. Chan, Y. Kuga, A. Ishimaru, and C.T.C. Le, "Experimental studies of bistatic scattering from two-dimensional conducting random rough surfaces". IEEE Trans.On Geosc. And Remote sensing, Vol. 34, No.3, 1996.
[13] R.T Shin, Theory of Microwave Remote Sensing, John Wiley, New York, 1985.
[14] B.B., Mandelbrot, and J.W. Van Ness,1968. "Fractional Brownian motions, fractal noises and applications". Siam Rev., 10.
[15] T., Feder, Fractals, Plenum Press, 1988.
[16] G.W.,Wornell, " Wavelet-based representation for the 1/f family of fractal process", Proc IEEE, vol. 81, October 1993.
[17] M., Dawson, A.K Fung. "A robust statistical based estimator for soil moisutre retrieval from radar measurments. "
[18] L. Bennaceur, R. Bennaceur, Z. Belhadj, and M. R. Boussema, A sensitivity analysis of radar backscattering coefficient to multi-scale roughness description and radar parameters using the small perturbation model. Proceedings of ICTTA 04, Damascus, Sirius, April 2004.