By Topic

Automatic Mapping of Linearwoody Vegetation Features in Agricultural Landscapes

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

4 Author(s)
Aksoy, S. ; Dept. of Comput. Eng., Bilkent Univ., Ankara ; Akcay, G. ; Cinbis, G. ; Wassenaar, T.

Development of automatic methods for agricultural mapping and monitoring using remotely sensed imagery has been an important research problem. We describe algorithms that exploit the spectral, textural and object shape information using hierarchical feature extraction and decision making steps for automatic mapping of linear strips of woody vegetation in very high-resolution imagery. First, combinations of multispectral values and multi-scale Gabor and entropy texture features are used for training pixel level statistical classifiers for characterizing individual trees and tree groups with respect to their surroundings. Then, decisions based on object level texture features and morphological shape analysis provide the final detection of woody vegetation having a linear structure. Experiments on QuickBird imagery from different sites show that the proposed algorithms provide good localization of linear strips of woody vegetation in different landscapes.

Published in:

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International  (Volume:4 )

Date of Conference:

7-11 July 2008