Cart (Loading....) | Create Account
Close category search window
 

Comparative Study of Three Feature Selection Methods for Regional Land Cover Classification Using MODIS 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

5 Author(s)

Selecting suitable features is very crucial for achieving successful classification of land cover types. This paper presents a comparative study of three typical feature selection methods for the task of regional land cover classification using MODIS data. Comparison results have shown that Branch and Bound is the best for land cover classification with MODIS data, while ReliefF and mRMR achieve nearly the same accuracies on the target application. The experimental results also show that it is necessary to conduct feature selection, which can reduce the computation cost largely, while the accuracy remains the same or even better.

Published in:

Image and Signal Processing, 2008. CISP '08. Congress on  (Volume:4 )

Date of Conference:

27-30 May 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.