A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based On WorldView-2 Satellite Imagery

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%.





References:
[1] P. M. Dare, "Shadow analysis in high-resolution satellite imagery of
urban areas." Photogrammetric Eng. & Remote Sens.71, no. 2, 2005, pp.
169-177.
[2] A.K. Saha, M. K. Arora, E. Csaplovics, and R. P. Gupta. "Land cover
classification using IRS LISS III image and DEM in a rugged terrain: a
case study in Himalayas." Geocarto Int. 20, no. 2, 2005, pp. 33-40.
[3] V. Arévalo, J. González, and G. Ambrosio. "Detecting shadows in
QuickBird satellite images." In ISPRS Commission VII Mid-term
Symposium'Remote Sens: From Pixels to Processes. 2005.
[4] P. Sarabandi, F. Yamazaki, M. Matsuoka, and A. Kiremidjian. "Shadow
detection and radiometric restoration in satellite high resolution
images." Proc. IEEE of IGARSS-2004, September 2004, Anchorage,
Alaska, New York, CDROM 2004.
[5] Y. Chen, D. Wen, L. Jing, and P. Shi. "Shadow information recovery in
urban areas from very high resolution satellite imagery." Int. J. of
Remote Sens. 28, no. 15, 2007, pp.3249-3254.
[6] T. Gustav, M. Shimoni, and J. Ahlberg. "A shadow detection method for
remote sensing images using VHR hyperspectral and LIDAR data." In
IEEE Int. Geosci. and Remote Sens. Symposium (IGARSS), 2011, pp.
4423-4426.
[7] A. Lizy, and M. Sasikumar. "An efficient shadow detection method for
high resolution satellite images." (Published Conference Proceedings
style) IEEE In Computing Communication & Networking Technologies
(ICCCNT), 2012 Third International Conference on, 2012, pp. 1-5.
[8] K.R.M Adeline, M. Chen, X. Briottet, S. K. Pang, and N. Paparoditis.
"Shadow detection in very high spatial resolution aerial images: A
comparative study." ISPRS Journal of Photogrammetry and Remote
Sens. 80, 2013, pp. 21-38.
[9] V. Arévalo, J. González, and G. Ambrosio. "Shadow detection in colour
high‐resolution satellite images." Int. J. of Remote Sens 29, no. 7, 2008,
pp.1945-1963.
[10] L. Hégarat-Mascle, and C. André. "Use of Markov random fields for
automatic cloud/shadow detection on high resolution optical
images." ISPRS J. of Photogrammetry and Remote Sens. 64, no. 4, 2009,
pp.351-366.
[11] L. Wen, and F. Yamazaki. "Object-based shadow extraction and
correction of high-resolution optical satellite images." IEEE J. of Select.
Topics in Appl. Earth Observations and Remote Sens. no. 4, 2012,
pp.1296-1302.
[12] L. Jiahang, T. Fang, and D. Li. "Shadow detection in remotely sensed
images based on self-adaptive feature selection." Geoscience and
Remote Sensing, IEEE Trans. on 49, no. 12, 2011, pp.5092-5103.
[13] P. Andrea, I. Mikic, M.M. Trivedi, and R. Cucchiara. "Detecting moving
shadows: algorithms and evaluation." IEEE Trans. Pattern Anal.
Machine Intel. 25, no. 7, 2003, pp.918-923.
[14] X. Li, F. Qi, R. Jiang, Y. Hao, G. Wu, L. Xu, F. Qi, R. Jiang, Y. Hao,
and G. Wu. "Shadow detection and removal in real images: a
survey." (Unpublished work style) Computer Vision Lab, Dept. of
Computer Science and Engineering, Shanghai JiaoTong University,
Shanghai (2006).
[15] DigitalGlobe. White Paper: The Benefits of the 8 Spectral Bands of
WorldView–2. Longmont, CO: DigitalGlobe 2009.