학술논문
A comparison of hierarchical and partitional clustering techniques for multispectral image classification
Document Type
Conference
Author
Source
IEEE International Geoscience and Remote Sensing Symposium Geoscience and remote sensing symposium Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International. 3:1624-1626 vol.3 2002
Subject
Language
Abstract
Unsupervised classification of remotely sensed data has traditionally been performed using partitional clustering procedures. This paper compares six classification results for a small Landsat 7 TM sub-image of Hainan Province in China. Of all clustering procedures, the hierarchical nearest neighbour linkage had the lowest classification accuracy, whereas the combinatorial K-means partitional procedure produced the best classification result.