综合后向散射特征与极化特征的L波段SAR数据岩石分类
Lithology classification of L-band SAR data by combining backscattering and polarization characteristics
郭森淼 1姜琦刚 1梁诗晨 2王鹏1
作者信息
- 1. 吉林大学地球探测科学与技术学院,长春 130026
- 2. 吉林大学地质博物馆,长春 130026
- 折叠
摘要
以菲律宾民都洛岛为研究区域,选取ALOS PALSAR双极化数据(极化方式为HH和HV极化)作为数据源,通过提取后向散射系数(Sigma0_HH和Sigma0_HV)和极化分解参数(熵、角和反熵),使用最大似然分类方法实现研究区的岩石单元分类和填图.在加入了极化分解参数之后,总体精度由仅使用后向散射系数的36.706％提高到65.000％.海岸带沼泽和珊瑚礁的F1分数超过了 0.80,辉长岩和Mansalay组的F1分数超过了 0.75.引入极化特征后,岩石单元的边界被更好地提取,Mansalay组和Mindoro变质岩与其他岩石的可分性增强.3个极化分解参数弥补了多种岩石单元的后向散射系数难以区分的不足,显著提高了岩石单元的可分性.研究表明,L波段SAR数据的极化分解参数和后向散射系数相结合能提高植被覆盖区岩石单元的分类精度.
Abstract
Taking Mindoro Island in Philippines as the study area,and selecting ALOS PALSAR dual-polariza-tion data(polarization mode of HH and HV polarization)as the source data,the authors used the maximum likeli-hood classification method to classify the rock units and geological mapping in study area by extracting the backscat-tering coefficients(Sigma0_HH and Sigma0_HV)and the polarization decomposition parameters(entropy,angle and anisotropy).With the inclusion of polarization decomposition parameters,the overall accuracy increased from 36.706％to 65.000％,comparing to the result using only backscattering coefficients.The F1 scores of the coastal marsh and coral reef exceeded 0.80,and those of the gabbro and Mansalay Formation exceeded 0.75.After adding polarization features,the rock unit boundaries were better extracted and increased separability of the Mansalay Forma-tion and Mindoro metamorphic rocks from other rocks.Three polarization decomposition parameters compensate for the similarity of backscattering coefficients of multiple rock units and significantly improve the separability of rock units.It is shown that the combination of polarization decomposition parameters and backscattering coefficients of L-band SAR data can improve the classification accuracy of rock units in vegetation-covered areas.
关键词
岩石分类/合成孔径雷达/ALOS/PALSAR/最大似然法/混淆矩阵/民都洛岛/菲律宾Key words
lithology classification/synthetic aperture radar/ALOS PALSAR/maximum likelihood method/confusion matrix/Mindoro Island/Philippines引用本文复制引用
基金项目
中国地质调查局项目(DD20191011)
出版年
2024
NETL
NSTL
万方数据