HYBRID AND DUAL LINEAR POLARIMETRIC RISAT-1 SAR DATA FOR CLASSIFICATION ASSESSMENT

被引：0
|
作者：
Kumar, Vineet [1 ]
Mandal, Dipankar [1 ]
Rao, Y. S. [1 ]
Meadows, Peter [2 ]
机构：
[1] Indian Inst Technol, CSRE, Bombay 400076, Maharashtra, India
[2] BAE Syst Appl Intelligence Labs, Chelmsford CM2 8HN, Essex, England
来源：
2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2017年
关键词：
Hybrid pol; RISAT-1; SVM;
D O I：
暂无
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
This paper compares the classification capability of data acquired in hybrid and dual linear polarization mode over the Chelmsford area, United Kingdom, from RISAT-1 C-band satellite. Support vector machine based supervised classification is used in the study and accuracy is assessed over the validation pixels. The hybrid-pol RH/RV combination shows better classification accuracy over linear pol HH/HV combination by 2.5 %. Overall classification accuracy is increased to 90% over the given area when Stokes parameter are added to the polarization combination.
引用
收藏
页码：1028 / 1031
页数：4
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