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In this study, processing of satellite images derived from T.M. sensor was used for soil studies and finally for producing soil units map. The region is part of Varamin plain and watershed catchment of Jajroud River. According to the nearest weather station information, average of yearly rainfall of study area is between 140 and 150 mm with average temperature of 18°C. Based on two different methods, soils of this region can be classified based on soil taxonomy method (i.e., two Aridisol and Entisol orders) and based on F.A.O. method (i.e., mainly as Fluvisol, Cambisol and some units as Calsisol, Gypsisol and Solonchak). Agreement ratio between soil maps derived from digital classification with the maximum likelihood method and ground truth map devolved from traditional methods and its kappa index were 82% and 75%, respectively. Analyzing the error matrix of this research showed that among 12 units derived from this study, differentiation of units 2 from 6 and 9 from 7 were poor (i.e., units 2, 6, 9 and 7 correspond to Haplocalcid, Haplocambid, Calcaric Fluvisol and Calcaric Cambisol, respectively). Meanwhile, the presence of high silt content in the texture of topsoil created high spectra reflection, which caused great similarity of the spectra with saline soils or other chemical substances. This resulted in some problems when analyzing dates and specially image classification.
This research suggests that in soil studies, beside selection of suitable spectral bands, images be used when land is bare. It should be noticed that images of the land with and without plant coverage can be used simultaneously, too. To reduce the above-mentioned interference, in stead of classifying based on the difference in spectra reflection, digital dates produced by other sensors, such as SPOT satellite (of France) or IRS satellite (of India) and also other classification methods based on phenomenon coordinate system should be studied.