WASET
	%0 Journal Article
	%A Kaveh Shahi and  Helmi Z. M. Shafri and  Ebrahim Taherzadeh
	%D 2014
	%J International Journal of Environmental and Ecological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 94, 2014
	%T A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based On WorldView-2 Satellite Imagery
	%U https://publications.waset.org/pdf/9999443
	%V 94
	%X In remote sensing, shadow causes problems in many
applications such as change detection and classification. It is caused
by objects which are elevated, thus can directly affect the accuracy of
information. For these reasons, it is very important to detect shadows
particularly in urban high spatial resolution imagery which created a
significant problem. This paper focuses on automatic shadow
detection based on a new spectral index for multispectral imagery
known as Shadow Detection Index (SDI). The new spectral index
was tested on different areas of WorldView-2 images and the results
demonstrated that the new spectral index has a massive potential to
extract shadows with accuracy of 94% effectively and automatically.
Furthermore, the new shadow detection index improved road
extraction from 82% to 93%.

	%P 1774 - 1777