Research Papers

Support vector machines classification for finding building patches from IKONOS imagery: the effect of additional bands

[+] Author Affiliations
Dilek Koc-San

Akdeniz University, Department of Space Sciences and Technologies, 07058 Antalya, Turkey

Mustafa Turker

Hacettepe University, Department of Geomatics Engineering, 06800 Ankara, Turkey

J. Appl. Remote Sens. 8(1), 083694 (Jan 10, 2014). doi:10.1117/1.JRS.8.083694
History: Received July 19, 2013; Revised November 19, 2013; Accepted December 16, 2013
Text Size: A A A

Abstract.  This study aims to find building patches from pan-sharpened IKONOS imagery using two-class support vector machines (SVM) classification. In addition to original bands of the image, the normalized digital surface model, normalized difference vegetation index, and several texture measures (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation) are also used in the classification. The study illustrates the performance of the binary SVM classification in building detection from IKONOS imagery. Moreover, the effect of additional bands in building detection is examined. The approach was tested in three test sites that are located in the Batikent district of Ankara, Turkey. The SVM classification provided quite accurate results with the building detection percentage (BDP) values in the range 81.27–96.26% and the quality percentage (QP) values in the range 41.01–74.83%. It was found that the usage of additional bands in SVM classification had a significant effect in building detection accuracy. When compared to results obtained using solely the original bands, the additional bands increased the accuracy up to 10.44% and 8.45% for BDP and QP, respectively.

Figures in this Article
© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Dilek Koc-San and Mustafa Turker
"Support vector machines classification for finding building patches from IKONOS imagery: the effect of additional bands", J. Appl. Remote Sens. 8(1), 083694 (Jan 10, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083694


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.