An object-based classification approach for surface water detection
by G. Xiao, David Tien
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 9, No. 3/4, 2010

Abstract: Detection of water areas on the land surface via aerial imagery is crucial for assisting land management. As near-infrared (NIR) energy tends to be absorbed by water, this property of low-spectral reflection is usually utilised in analysing water resources on land. However, the spectral reflection of shallow water varies significantly. It is difficult to distinguish such areas from the background by traditional land cover classifications. To solve this problem, this paper proposes an object-based classification approach for automatically detecting water areas from aerial imagery with red, green, blue and NIR bands. To overcome the problem of inadequate class definition in conventional region-based classifications, the water areas are divided into a number of classes, and a decision tree approach to select the features required for each class. Experiments show that the proposed approach has good capability to distinguish shallow water areas from other objects in wetlands.

Online publication date: Thu, 04-Nov-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com