Title :
Unsupervised Land Cover/Land Use Classification Using PolSAR Imagery Based on Scattering Similarity
Author :
Qiang Chen ; Gangyao Kuang ; Li, Jie ; Lichun Sui ; Diangang Li
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
This paper presents a new unsupervised land cover/land use classification scheme using polarimetric synthetic aperture radar (PolSAR) imagery based on polarimetric scattering similarity. Compared with the H/alpha classification scheme based on a dominant “average” scattering mechanism, the proposed scheme has such advantages as the following: (1) The major scattering mechanism represents a target scattering in the low-entropy case; (2) it also represents both the major and minor scattering mechanisms in the medium-entropy case; and (3) all the scattering mechanisms in the high-entropy case can be represented. The major and minor scattering mechanisms have been identified automatically based on the relative magnitude of multiple-scattering similarities. The canonical scattering corresponding to maximum scattering similarity is regarded as the major scattering mechanism. The result obtained using the National Aeronautics and Space Administration/Jet Propulsion Laboratory´s AIRSAR L-band PolSAR imagery reveals that the proposed scheme is more effective as compared to the existing models and promises to increase the accuracy of the classification and interpretation.
Keywords :
entropy; geophysical image processing; image classification; land use planning; radar polarimetry; synthetic aperture radar; terrain mapping; AIRSAR L-band PolSAR imagery; H classification scheme; National Aeronautics; alpha classification scheme; average scattering mechanism; canonical scattering; high-entropy case; image classification; image interpretation; jet propulsion laboratory; low-entropy case; major scattering mechanisms; maximum scattering similarity; medium-entropy case; minor scattering mechanisms; multiple-scattering similarities; polarimetric scattering similarity; polarimetric synthetic aperture radar imagery; space administration; target scattering; unsupervised land cover classification scheme; unsupervised land use classification scheme; Backscatter; Educational institutions; Entropy; Feature extraction; Radar polarimetry; Scattering; Synthetic aperture radar; Land cover/land use; radar polarimetry; scattering similarity; synthetic aperture radar (SAR); unsupervised classification;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2012.2205389