Object-based classification of remotely sensed olive tree fields, using mathematical morphology

Vol. 6 No. 2

Year : 2011

Issue : Nov-Jan

Title  : Object-based classification of remotely sensed olive tree fields, using mathematical morphology 

Author Name  : Mounir Salhi 

Synopsis  : 

In this paper, we present an object-based approach for rural land cover classification from high-resolution multispectral image data that builds upon a pixel-based segmentation.A mathematical morphology algorithm is then implemented to build objects by a generalization technique to facilitate further object-based classification. The imagery used for this study was acquired by the IKONOS commercial remote sensing satellite and consists of four multi- spectral bands. The object-based classifier uses shape and spectral features to determine the final classification of a segmented image. Using these techniques, the object-based classifier is able to identify olive tree fields from farms and impervious surface..