Forest Mapping and Classification with Compact PolInSAR Data

作     者：Ningxiao Sun Yuejin Zhao Lin Sun Qiongzhi Wu 

作者机构：School of OptoelectronicsBeijing Institute of Technology School of Information and ElectronicsBeijing Institute of Technology 

出 版 物：《Journal of Beijing Institute of Technology》 (北京理工大学学报(英文版))

年 卷 期：2018年第27卷第3期

页      面：391-398页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：forest mapping unsupervised classification Wishart classifier optimal coherence set com-pact polarimetric-interferometric SAR(C-PolInSAR) 

摘      要：An unsupervised classification method was applied to compact polarimetric-interferometric SAR（C-PolInSAR）data to investigate its potential for forest mapping and *** classification requires an initial class as a training *** this paper,the compact polarimetric entropy H and the optimal coherence spectrumA were computed,and their capabilities for initial classification were *** on the Hand A,apartition method was proposed to subdivide the H-A plane,and initial classes were hence ***,unsupervised C-PolInSAR segmentation procedures based on H-A and the complex coherence matrix J;were *** effectiveness of the unsupervised classification of C-PolInSAR data was demonstrated by using an E-SAR L-band PolInSAR dataset of the Traunstein test site.