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

页码：1028 / 1031

页数：4

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