VARIABLE IMPORTANCE AND RANDOM FOREST CLASSIFICATION USING RADARSAT-2 POLSAR DATA

被引：3
|
作者：
Hariharan, Siddharth [1 ]
Tirodkar, Siddhesh [1 ]
De, Shaunak [1 ]
Bhattacharya, Avik [1 ]
机构：
[1] Indian Inst Technol, Ctr Studies Resources Engn, Powai 400076, India
来源：
2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年
关键词：
Random Forest Classification; Synthetic Aperture Radar; Polarimetry;
D O I：
10.1109/IGARSS.2014.6946649
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we have classified Polarimetric Synthetic Aperture Radar (PolSAR) data using the Random Forest (RF) classifier. The variables were ranked using the mean decrease in accuracy permutation method for each terrain class. RADARSAT-2 (RS-2) data acquired over Mumbai, India was used in this study. This technique is able to efficiently classify the dataset, as well as rank the parameters used in that classifier.
引用
收藏
页码：1210 / 1213
页数：4
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