Monte Carlo Reiterations to Decrease Uncertainty in Pair Wise Comparison of Desertification Indicators

Monte Carlo methods designed base on stochastic reiterations and can be useful in uncertainty conditions. The purpose of this research was investigation of uncertainty to rank desertification indicators. In order to decrease uncertainty have been applied Monte Carlo reiterations for each value of indicator، if rank of Xi is higher than rank of Xk constantly. Using multi dimension integrals the Monte Carlo program was run on JAVA environment. The results of simulation indicated that with increasing Monte Carlo reiterations the standard deviation of alternatives was decreasing. Also results showed that wind erosion، water erosion، land use alterations، biomass loss، canopy decreasing، grazing density and loss of rangelands quality were main indicators affecting desertification process.