By Topic

Combining Tasseled Cap Transformation with Support Vector Machine to classify Landsat TM imagery data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Qingsheng Liu ; State Key Lab. of Resources & Environ. Inf. Syst., Chinese Acad. of Sci., Beijing, China ; Gaohuan Liu

A supervised classification method combining Tasseled Cap Transformation (TCT) and Support Vector Machine (SVM) for Landsat TM imagery data is proposed in this paper. The spectral dimensionality of the imagery data is firstly reduced by TCT into the Brightness Component (TCTB) and Greenness Component (TCTG) and Wetness Component (TCTW), then the transformed data is inputted into Support Vector Machine and classified into water, wetland, shrub and grass land, farmland and town or bare land. The present results show that compared to SVM classification of the original six bands of Landsat TM imagery data, the classification method of combining TCT with SVM has a high accuracy.

Published in:

Natural Computation (ICNC), 2010 Sixth International Conference on  (Volume:7 )

Date of Conference:

10-12 Aug. 2010