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A comparison of object-oriented and pixel-based classification methods for mapping land cover in Northern Australia

Whiteside, T and Ahmad, W (2005). A comparison of object-oriented and pixel-based classification methods for mapping land cover in Northern Australia. In: Spacial Sciences Institute Biennial Conference, Melbourne, 13-17 September 2005.

Document type: Conference Paper
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Author Whiteside, T
Ahmad, W
Title A comparison of object-oriented and pixel-based classification methods for mapping land cover in Northern Australia
Conference Name Spacial Sciences Institute Biennial Conference
Conference Location Melbourne
Conference Dates 13-17 September 2005
Conference Publication Title Proceedings of SSC 2005 Spatial Intelligence, Innovation and Praxis
Publisher Spacial Sciences Institute
Publication Year 2005
ISBN 0-9581366-2-9   (check CDU catalogue open catalogue search in new window)
Field of Research 0909 - Geomatic Engineering
0406 - Physical Geography and Environmental Geoscience
HERDC Category E2 - Conference Publication - Full written paper, non refereed proceedings (internal)
Abstract The development of robust object-oriented classification methods suitable for medium to high resolution satellite imagery provides a valid alternative to ‘traditional’ pixel-based methods. This paper compares the results of an object-oriented classification to a supervised pixel-based classification for mapping land cover in the tropical north of the Northern Territory. The object-oriented approach involved the segmentation of image data into objects at multiple scale levels. Objects were assigned class rules using spectral signatures, shape and contextual relationships. The rules were then used as a basis for the fuzzy classification of the imagery. The supervised pixel-based classification involved the selection of training areas and a classification using maximum likelihood algorithm. Accuracy assessment of bothe classifications were undertaken. A comparison of the results shows better overall accuracy of the object-oriented classification over the pixel-based classification. This object-oriented method provided results with accepotable accuracy; indicating object-oriented analysis has great potential for extracting land cover information from satellite imagery captured over tropical Australia.
 
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Created: Fri, 12 Sep 2008, 08:35:25 CST by Administrator