A non-parametric classification system for a partially unsupervised updating of land-cover maps

Author

Bruzzone, Lorenzo ; Cossu, Roberto

Author_Institution

DICA, Trento Univ., Italy

Volume

6

fYear

2001

fDate

2001

Firstpage

2587

Abstract

A partially unsupervised classification system for a regular updating of land-cover maps is proposed. The systems is composed of different partially unsupervised cascade classifiers integrated in the framework of a multiple classifier approach. The use of cascade classifiers allows one to exploit temporal correlation between multitemporal remote-sensing images to increase the accuracy and robustness of the partially unsupervised classification approach. Experimental results confirm the effectiveness of the proposed classification system

Keywords

geophysical signal processing; geophysical techniques; image classification; image sequences; terrain mapping; vegetation mapping; cascade classification; cascade classifier; change detection; geophysical measurement technique; image classification; image sequence; land cover map; land surface; multiple classifier; multitemporal remote sensing; nonparametric method; partially unsupervised updating; remote sensing; terrain mapping; Availability; Classification algorithms; Electronic mail; Geographic Information Systems; Image databases; Image sensors; Information systems; Production; Remote sensing; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.978097

Filename

978097