Cloud classification from satellite data using a fuzzy sets algorithm: A polar example

Abstract

Abstract Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster centre. The FCM algorithm is applied to Advanced Very High Resolution Radiometer (AVHRR) data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification and an unsupervised maximum likelihood classifier.