Evaluation of Soil Inference Model (SIE) in Soil Mapping with Emphasis on Using Expert Knowledge and Fuzzy Logic (Jolfa City-Golfaraj)

One of the problems with the traditional mapping of soils is the expert’s opinion, it time-consuming and timely preparation, and the updating of the maps. While digital soil mapping, using different soil-earth models leads to the simplification of the complexity of the soil system. The purpose of this study was to investigate Soil-Environment Inference (SIE) in soil mapping with an emphasis on using the expert knowledge and fuzzy logic. For this purpose, the digital layer of geology and peripheral layers were derived from a digital elevation model including elevation, slope, and curvature of the ground surface, and auxiliary index, which comprised the input data of the SIE model. Then, the fuzzy maps prepared for the five soil types and the final map of soil prediction were created by hardening. The results showed that the SIE model, which used environmental variables, had a high ability to isolate soil types with more detailed compositions of soils with different maternal materials. The comparison of the error matrix showed that the overall accuracy of the derived map of the SIE model was equal to 75%, and the matching of the digital mapping results with conventional mapping accounted for 74.71% of the results. The difference in the compliance rate could be attributed to the difference in the nature of the two methods.