Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 281-285, 2014
https://doi.org/10.5194/isprsarchives-XL-2-W3-281-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
22 Oct 2014
A COMPARISON STUDY OF DIFFERENT KERNEL FUNCTIONS FOR SVM-BASED CLASSIFICATION OF MULTI-TEMPORAL POLARIMETRY SAR DATA
B. Yekkehkhany1, A. Safari1, S. Homayouni2, and M. Hasanlou1 1Dept. of Geomatics Engineering, College of Eng., University of Tehran, Tehran, Iran
2Dept. of Geography, University of Ottawa, Ottawa, Canada
Keywords: Full-polarimetric SAR data, multi-temporal data, SVM, kernel functions, cop classification Abstract. In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF).

The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

Conference paper (PDF, 2072 KB)


Citation: Yekkehkhany, B., Safari, A., Homayouni, S., and Hasanlou, M.: A COMPARISON STUDY OF DIFFERENT KERNEL FUNCTIONS FOR SVM-BASED CLASSIFICATION OF MULTI-TEMPORAL POLARIMETRY SAR DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 281-285, https://doi.org/10.5194/isprsarchives-XL-2-W3-281-2014, 2014.

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