A Case Study on Fuzzy Classification of Soil: Cheshmeh - Sefid, Kermanshah

Chenges in the soil characteristics is rather continuously. A method that takes this continuity into account would present a realistic pattern of soil distribution either in taxonomic or geographical space. The fuzzy set theory provides such an approach. In this study, the robustness of fuzzy clustering in soil pattern recognition was evaluated in a subcatchment of western Iran. The clustering carried out on the basis of minimization of an objective function in assigning membership values to each pedon in each fuzzy class. Fuzziness exponent values from 1.15 to 1.5 were used. The following validation of the resulted clusters (classes), optimal number of classes in whole, morphological and particle-size subsets were determined 8, 4, and 5 respectively. Plots of membership values across the landscape indicated class overlap and considerable contiguity. Considering low differentiation of these young soils and the high similarity among their properties, the method indicated a high capacity in recognizing different soil types over the study area. Furthermore, there was relationships between the soil fuzzy classes and landform. Thus, the method is capable in continuous classification, which could be so important in construction of continuous soil maps at low aggregation levels, e. g., pedon.