application of fuzzy membership functions and isocluster analysis method for soli-landscape map (case study: damavand region, iran)

soil and land information is vital for land use planning and infrastructure development. maps of soils landscapes are powerful tools to guide sustainable planning and natural resource management. fuzzy set theory has been widely used in soil science for soil classification and mapping, land evaluation, fuzzy soil geostatistics, soil quality indices. in fuzzy logic-based approaches, soil spatial variation is expressed as spatial variation of membership in soil classes, which is then used to produce conventional soil-landscape map and to predict spatial variation of specific soil properties. the aim of this study is using fuzzy membership functions and isocluster analysis method for soli landscape maps with high accuracy. the following seven topographic variables (elevation, slope gradient, curvature, profile curvature, plani metric curvature, flow accumulation and topographic wetness index) were used in this study to characterize the environment conditions. the proposed methods were tested in damavand region in the northeastern of tehran. a set of membership functions were constructed to represent the descriptive knowledge on soil-landscape relationships, then for soil-landscape map isocluster analysis method was used. using this operator 5 soil-landscape units were determined as follows: 1-valley bottoms, 2-low land plain, 3-moderate hill slope, 4-steep hill slope, 5-mountain.the soil-landscape map achieved 74% of accuracy. 74% accuracy is acceptable for an initial soil mapping. this suggests that the membership functions constructed in this study do capture the major pattern of soil-landscape relationships over the region.