期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：46
期号：2
页码：0659-0664
出版社：Journal of Theoretical and Applied
摘要：Classification is achieved by Markov random field filtering on the original data. The result is a series of segmented maps, which differ in the number of (unsupervised) classes. For a (compatible) supervised approach, only the first and last step have to be applied. Results are discussed for the agricultural areas Flevoland in The Netherlands (AirSAR data)and DEMMIN in Germany, using the NASA/JPL AirSAR system and the DLR ESAR system, respectively. The applications include the use of groundtruth for legend development, the check for ground truth completeness, and the construction of a bottom-up hierarchy of the characteristics that can be distinguished in the radar data. The latter gives important insights in physics of polarimetric radar backscattering mechanisms.
关键词：Unsupervised Classification; Agricultures; Data Segmentation; Full Polarimetric
