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It is well documented that soil backscattering in the microwave regime depends mostly on soil roughness and soil permittivity. Many agricultural applications require the retrieval of soil moisture at regional scales, in order to include soil moisture information into an ecoagricultural process model. One key step to derive soil moisture maps from soil backscattering maps at microwave regimes is to statistically quantify agricultural soil roughness. Up to date, only in situ measurements were able to success in this task. Three main techniques for soil roughness measurement are discussed in the literature: meshboard profilers, needle-like profilers and laser profilers. Meshboard profilers are graduated boards able to measure soil roughness using graduated lines. Needle-like profilers are arrays of small parallel cylinders mounted over a board in such a way that the vertical displacements of the needles (related to the vertical profile of the soil) can be measured. Laser profilers discussed in the literature are flighttime laser altimeters, that measure soil profile by converting beam delay into beam flight distance. All these methods present different disadvantages, all discussed in [1]. The major drawback common to these methods is their inherent restriction to measure only 1-D profiles. This restriction is related to the fact that the most widely used electromagnetic interaction models used to calculate the soil backscattering at microwave regime (SPM, PO, GO, IEM) suppose that soil roughness can be characterized by a 1-D soil profile. This leads to theoretical derivations based on one of two autocorrelation functions (exponential, gaussian), that requires as an input the soil RMS height (s) and the correlation length related to the autocorrelation function (l).Recent investigations suggest that for some agricultural soils profiles related to specific agricultural techniques, these hypotheses could not be valid [2]. Firstly, in very smooth soils related to siembra directa [3], the assumption of a single autocorrelation function able to describe the whole soil profile was found false [4]. Secondly, most agricultural soil presents a non symmetrical 2-D profile, related to preferential plough directions and water leakage [2]. So, it is not clear in which direction soil profile should me measured, and angular averaging leads to very imprecise parameter estimations, not related to intrinsic parameter variability but to an incorrect experimental design [5].One way to increase the theoretical knowledge about real soil backscattering, is to measure the bi-dimensional soil profile of agricultural soils. In order to do this, in this paper we present a profiler based on a laser scanning technique, that intrinsically measure the 2-D soil profile [5]. This profiler is constructed around a laser beam that is diffracted using a small glass rod, in order to obtain a clear laser line over the soil. A mechanical base is used to move the laser base transversally, in order to scan a 2- D soil profile. On every step of the laser base, a camera takes a picture of the soil illuminated by the laser line. Then, an image processing technique is used to extract soil profile from soil images. In its prototype version, the scanner is able to scan an area of 1m x 0.5 m, but since laser diffraction width is only determinated by the rod diameter, is easy to achieve scanning areas of the order of 1m x 1 m. In section II we describe the laser profiler device and the associated image processing techniques needed to derive profile information from photographic images. In section III we show some 2-D profiles measured on specific test sites, and show different methods to: (1) characterize the full bi-dimensional soil profile and (2) derive accurate estimates of 1-D profiles from 2-D profiles. In section III, we compare section II results with the results obtained from a 2 meter needle-like profile. Finally, in the conclusion we analyze how this new technique could be able to close the gap between theoretical models and real soil backscattering.[1] Davidson, M.W.J.; Thuy Le Toan; Mattia, F.; Satalino, C.; Manninen, T.; Borgeaud, M., "On the characterization of agricultural soil roughness for radar remote sensing studies," Geoscience and Remote Sensing, IEEE Transactions on , vol.38, no.2, pp.630-640, Mar 2000. [2] Yisok Oh; Young Chul Kay, "Condition for precise measurement of soil surface roughness," Geoscience and Remote Sensing, IEEE Transactions on , vol.36, no.2, pp.691-695, Mar 1998. [3] Cruse, R.M.; Cassel, D.K.; Stitt, R.E. y Averette, F.G., "Effect of particle surface roughness on mechanical impedance of coarsetextured soil materials . Soil Sci. Soc. Am. J. 45:1210-1214, 1981. [4] Davidson, M.; Le Toan, T.; Borgeaud, M.; Manninen, T., "Measuring the roughness characteristics of natural surfaces at pixel scales: moving from 1 metre to 25 metre profiles," Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS ´98. 1998 IEEE International , vol.3, no., pp.1200-1202 vol.3, 6-10 Jul 1998. [5] Mattia, F.; Davidson, M.W.J.; Le Toan, T.; D´Haese, C.M.F.; Verhoest, N.E.C.; Gatti, A.M.; Borgeaud, M., "A comparison between soil roughness statistics used in surface scattering models derived from mechanical and laser profilers," Geoscience and Remote Sensing, IEEE Transactions on , vol.41, no.7, pp. 1659-1671, July 2003.

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