The SDM membership function in the fuzzy spatial classification

In this paper the SDM membership (Sthephany-David-Mariana) function is presented as an alternative to overcome the difficulties caused by the direct approach in the Spatial Classification using fuzzy membership models or Fuzzy Spatial Classification. Further, it is realized one small modification at the Bayesian estimator of the fuzzy membership vectors, with the purpose of suppressing the misclassification that appears when the addition of the regression coefficients is negative. Two classifications are executed based on the theory of the fuzzy sets; one using the direct approach without modification and the other modifying the previous one through of SDM procedure. Later, comparisons are established between the results of both classifications, obtaining in the classification with the SDM procedure, classification vectors easier to interpret and almost unbiased.