The Spatial Analysis and Modeling Tool (SAMT) is a GIS-based analytical software for land use study. This paper demonstrates the capabilities of SAMT as applied i... Academic Article uri icon

abstract

  • The implementations of both the supervised and unsupervised fuzzy c-means classification algorithms require a priori selection of the fuzzy exponent parameter. This parameter is a weighting exponent and it determines the degree of fuzziness of the membership grades. The determination of an optimal value for this parameter in a fuzzy classification process is problematic and remains an open problem. This paper presents a new and efficient procedure for determining a local optimal value for the fuzzy exponent in the implementation of fuzzy classification technique. Numerical results using simulated image and real data sets are used to illustrate the simplicity and effectiveness of the proposed method.

publication date

  • January 1, 2006