南京大学学报（自然科学版）Issue(5)：966-975,10.DOI:10.13232/j.cnki.jnju.2015.05.007
基于极化 SAR 图像的玛纳斯河流域典型区积雪识别
Recognizing snow from polarimetric SAR images in typical area of Manasi River Basin
摘要
Abstract
Polarimetric synthetic aperture radar(SAR)sensors can not only provide an all-weather snow observational capacity,but also provide a wealth of polarization characteristics,which have the potential to discriminate the snow-cover from other natural scatters.In this paper,the data we acquired was Radarsat-2 image in typical area of Manasi River Basin,Xinjiang Province on 1 9 March 2014.At first,we used polarimetric decomposition methods to extract polarimetric features for snow recognition.Secondly,Jeffreys-Matusita (J-M)distance was applied for feature selection.We analyzed the separability of different polarimetric features to discriminate between snow and snow-free areas.At last,snow recognition was completed by using the best features and support vector machine(SVM).The results show that the volume scattering component of Yamaguchi and Freeman decomposition,eigenvalue of coherent matrix and Shannon entropy have strong recognition ability for snow,and compared with the single feature, combining several polarimetric features for snow recognition can obtain a better result and the accuracy based on the four polarimetric characteristics reached 84%.The snow identification by polarization features can acquirebetter effect and can remedy the limitationinsnow identification by visible spectral remote sensing under the cloud condition.关键词
Radarsat-2/玛纳斯河流域/目标分解/极化特征/积雪识别Key words
Radarsat-2/Manasi River Basin/polarimetric decomposition/polarimetric feature/snow recognition分类
信息技术与安全科学引用本文复制引用
郭金金,肖鹏峰,冯学智,朱榴骏,周淑媛..基于极化 SAR 图像的玛纳斯河流域典型区积雪识别[J].南京大学学报（自然科学版）,2015,(5):966-975,10.基金项目
国家自然科学基金(41271353),国家高分辨率对地观测系统重大专项(95 Y40B02900113/1504) （41271353）
