Coniferous and Broad-Leaved Forest Distinguishing Using L-Band Polarimetric SAR Data
Coniferous and Broad-Leaved Forest Distinguishing Using L-Band Polarimetric SAR Data
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基于L波段极化SAR数据的针叶林和阔叶林识别
DOI：
10.1109/tgrs.2020.3032468
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发表时间：
2021-09
影响因子：
8.2
通讯作者：
Fang Shang;Taiga Saito;S. Ohi;Naoto Kishi
中科院分区：
文献类型：
--
作者：
Fang Shang;Taiga Saito;S. Ohi;Naoto Kishi
提出了一种基于结构方位参数的L波段极化SAR数据针阔叶林识别方法。结构取向参数是一个平均的斯托克斯矢量为基础的歧视，这是敏感的等效水平和垂直结构的组成。该方法利用散射功率信息对结构取向参数进行补偿，消除了地形的影响。最后根据补偿后的参数的统计特征得到最终的判别结果。利用多组ALOS 2-PALSAR 2 level1.1数据进行的实验表明，该方法具有较高的森林类型判别性能。
This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing.