Unsupervised classification of earth resources data.A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.
Document ID
19730032352
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Su, M. Y.
Jayroe, R. R., Jr.
Cummings, R. E. (NASA Marshall Space Flight Center Huntsville, Ala., United States)
Date Acquired
August 7, 2013
Publication Date
January 1, 1972
Subject Category
Computers
Meeting Information
Meeting: Conference on Earth Resources Observation and Information Analysis Systems