A COMPARISON STUDY OF DIFFERENT KERNEL FUNCTIONS FOR SVM-BASED CLASSIFICATION OF MULTI-TEMPORAL POLARIMETRY SAR DATA
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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2014-10-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2-W3/281/2014/isprsarchives-XL-2-W3-281-2014.pdf |