Fuzzy clustering of a Landsat TM scene

Author

Beichel, Reinhard ; Bolter, Regine ; Pinz, Axel

Author_Institution

Dept. of Comput. Graphics & Vision, Graz Univ. of Technol., Austria

Volume

3

fYear

1999

fDate

1999

Firstpage

1597

Abstract

Emerging new sensors deliver an ever increasing amount of remote sensing data. Classification still plays a key role in the automatic evaluation of these data. In this paper the characteristics of unsupervised fuzzy classification methods are examined and the results obtained from a section of a Landsat TM scene from the surroundings of Vienna are compared with various supervised classification methods

Keywords

geophysical signal processing; geophysical techniques; image classification; image processing; multidimensional signal processing; remote sensing; terrain mapping; 350 to 2500 nm; Austria; IR; Landsat TM; Vienna; fuzzy clustering; geophysical measurement technique; image classification; image processing; infrared method; land surface; multispectral remote sensing; optical imaging; remote sensing; satellite remote sensing; terrain mapping; unsupervised fuzzy classification method; visible; Automation; Clustering algorithms; Computer graphics; Iterative algorithms; Layout; Partitioning algorithms; Remote sensing; Satellites; Shape; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International

Conference_Location

Hamburg

Print_ISBN

0-7803-5207-6

Type

conf

DOI

10.1109/IGARSS.1999.772031

Filename

772031