A Comparative Study on Stepwise Cluster and Fuzzy Cluster in Cloud Classificat ion Techniques
In order to profoundly understand abilities of two classifiers—step wise cluster and fuzzy cluster in the cloud classification techniques, both EOS/ MODIS and GMS5 data set are used, spectral or textural features are drawn from samples randomly to identify various cloud/surface. The results show that the st epwise cluster gives higher accuracies than fuzzy classifier on the whole. With rega rds to discriminating diverse cloud/surfaces, fuzzy cluster demonstrates its hig her accuracies than stepwise cluster on the classes having similar characteristi cs such as stratus, cumulostratus and cumulus; while stepwise cluster has better capabilities of distinguishing cumulonimbus and surfaces. As far as misclassifi cation of cloud/surfaces, fuzzy cluster tends to show lower accuracies in more m isclassified classes.