The control of agricultural areas with the aid of remote sensing techniques and GPS technology yields better results with less cost and time when compared to standard soil measurements. In this study, it is aimed to extract multiple scattering coefficients from Radarsat-2 data in order to establish an association between remote sensing techniques and soil characteristics (soil moisture, dielectric coefficient, etc.). Different regions of the electromagnetic spectrum are being studied for the purpose of estimating soil moisture with remote sensing data. Because microwave sensors are sensitive to changes in soil moisture content, it is more appropriate to use these sensors in soil moisture estimation Therefore; synthetic aperture radar (SAR) sensor operating in the microwave range of the electromagnetic spectrum is capable of producing appropriate images with high resolution for agricultural purpose soil monitoring. Moreover, it is used for agricultural monitoring, plant growth, yield, mapping and estimation of soil moisture (Tehrani 2014) Among the different types of remote sensing sensors, SAR sensors (Radarsat-1, Envisat-Asar, Radarsat-2, and ERS-1/2) have a great potential in basin-scale soil moisture estimates (Moran ve ark. 2004). In addition, with polarimetric SAR, much better information can be obtained than with single band SAR. Furthermore, polarimetric SAR can provide more information with multiple polarizations (hh, hv, vh, vv) and penetrate into canopy where plant cover is dominant. For this reason, polarimetric SAR data gives a good result in estimating soil moisture on bare soil and vegetated areas. The experiments were carried out on agricultural sites in the Dicle University campus and calculation of scattering coefficients from the RadarSat-2 data consisted of several steps. At the first stage, a Radarsat-2 data was obtained from densely vegetated study area on April 8, 2015 and simultaneous local measurements were made on this area. In the second stage, various pre-processing steps (calibration, filtering, and terrain correction) have been employed to remove disorders from the Radarsat-2 data and the terrain correction process has been provided for fitting the terrain onto a real map coordinate system. At the other stage, the GPS coordinates of the points at which each ground moisture measurement was taken, were transferred to Rdarsat-2 data. In the last stage, a standard SAR backscattering technique was applied to the Radarsat-2 data of April 8, 2015 in order to calculate multiple scattering coefficients over the study areas dominated by dense vegetation cover. Then, four different backscattering parameters (σhh, σhv, σvh, σvv) were calculated from the parcels corresponding to each ground measurement point. Finally, these operations were repeated for 285 measurement points obtained on April 8, 2015 and a data matrix of 285x4 lengths was generated to evaluate the effect of vegetation cover. Furthermore, the statistical measurements of multi scattering coefficients were computed from this data matrix.