By Topic

Senescent vegetation and crop residue mapping in agricultural lands using artificial neutral networks and hyperspectral remote sensing

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
$33 $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

4 Author(s)
A. Bannari ; Dept. of Geogr., Ottawa Univ., Ont., Canada ; M. Chevrier ; K. Staenz ; H. McNairn

This paper focuses on a comparative study between a semi empirical model, the Modified Soil Adjusted Crop Residue Index (MSACRI), and artificial neutral networks (ANN) for estimating crop residue cover on agricultural fields using hyperspectral imagery. The results indicate the ANN method is more accurate and more representative of the ground reference information than the MSACRI.

Published in:

Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International  (Volume:7 )

Date of Conference:

21-25 July 2003