Urban construction area extraction using circular polarimetric correlation coefficient

Xiaoxia Lin, Wenguang Wang, Erfu Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution book


Urban construction area detection is of great significance for tracking, mission planning, training, loss estimation and urban planning. In this paper, we make full use of the polarization characteristics of SAR (synthetic aperture radar) data to detect urban construction area. First, circular polarization correlation coefficient characteristics, entropy characteristics based on the gray level co-occurrence matrix (GLCM), and the dihedral angle scattering characteristics using the Pauli decomposition are extracted to distinguish among urban area, forest area and other manmade targets. And then we adopt the three kinds of characteristic to form feature vector and complete urban area detection based on k-means clustering analysis. The experimental result has proved the efficiency of this method.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Imaging Systems and Techniques (IST)
Place of PublicationPiscataway, NJ.
Number of pages4
ISBN (Print)9781467357906
Publication statusPublished - 2013
Event2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013 - Beijing, United Kingdom
Duration: 22 Oct 201323 Oct 2013


Conference2013 IEEE International Conference on Imaging Systems and Techniques, IST 2013
Country/TerritoryUnited Kingdom


  • circular polarization correlation coefficient
  • dihedral angle scattering
  • GLCM
  • k-means clustering
  • urban area extraction

Cite this