Using ordered weight averaging (OWA) aggregation for multi-criteria soil fertility evaluation by GIS (case study: southeast Iran)

The Multi-criteria Decision Analysis (MCDA) and the Geographical Information Systems (GIS) are used to provide more accurate decisions for decision makers in order to evaluate the effective factors of the natural science. One of the popular algorithms of the multi-criteria analysis is the Ordered Weighted Averaging (OWA). The OWA procedure depends on some parameters which can be specified by means of the fuzzy logic. The aim of this study is to take the advantage of incorporating the fuzzy logic into GIS-based soil fertility analysis by OWA in the west of Shiraz, Fars province, Iran. In fact, different soil fertility maps with different risk level are prepared in the present study. This study introduces a method for farmers in case of make balance between their budget and their farm soil parameters. A farmer can accept more risk it can use more areas for farming and also the amount of needed budget increases too. For determining the soil fertility maps, the OWA parameters such as potassium (K), phosphor (P), copper (Cu), iron (Fe), manganese (Mn), organic carbon (OC) and zinc (Zn) were used. After generating the interpolation maps with the Inverse Distance Weighted (IDW), the fuzzy maps were generated by the membership functions for each parameter. Finally, by utilizing OWA, six fertility maps with different risk levels (degrees of uncertainty) were made. The results show that by decreasing the risk (no trade-off), increasing the risk, more area within the study area was suitable in terms of the soil fertility. Therefore, using OWA can generate many maps with different risk levels. This leads to different managements based on different financial conditions of farmers.