测绘学报 ›› 2015, Vol. 44 ›› Issue (5): 533-540.doi: 10.11947/j.AGCS.2015.20130244

• 摄影测量学与遥感 • 上一篇    下一篇

多时相双极化合成孔径雷达干涉测量土地覆盖分类方法

王馨爽1,2, 陈尔学1, 李增元1, 姚顽强3, 赵磊1   

  1. 1. 中国林业科学研究院资源信息研究所, 北京 100091;
    2. 国家测绘地理信息局陕西基础地理信息中心, 陕西 西安 710054;
    3. 西安科技大学测绘科学与技术学院, 陕西 西安 710054
  • 收稿日期:2013-12-10 修回日期:2014-12-01 出版日期:2015-05-20 发布日期:2015-05-27
  • 通讯作者: 陈尔学 E-mail: chenerx@caf.ac.cn E-mail:chenerx@caf.ac.cn
  • 作者简介:王馨爽(1988—),女,助理工程师,主要研究方向为微波遥感影像分类。
  • 基金资助:

    国家863计划(2011AA120405;2011AA120404)

Multi-temporal and Dual-polarization Interferometric SAR for Land Cover Type Classification

WANG Xinshuang1,2, CHEN Erxue1, LI Zengyuan1, YAO Wanqiang3, ZHAO Lei1   

  1. 1. Research Institute of Forest Resource Information Techniques, CAF, Beijing 100091, China;
    2. Shaanxi Geomatics Center of NASG, Xi'an 710054, China;
    3. Department of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2013-12-10 Revised:2014-12-01 Online:2015-05-20 Published:2015-05-27
  • Supported by:

    The National High-tech Research and Development Program of China(863 Program)(Nos.2011AA120405;2011AA120404)

摘要:

综合采用时相、极化和干涉3种维度的SAR数据进行土地覆盖分类。以黑龙江省逊克县多时相ALOS PALSAR数据覆盖区为研究区,利用不同时相极化SAR、干涉SAR信号对地物特征的敏感性,结合后向散射强度和干涉相干的时变特征进行地物解译,发展了基于多时相、多极化、干涉SAR数据的SVM土地覆盖分类方法。研究结果表明,引入双极化SAR中不同极化(HH-HV)间的相干系数,并结合所选择的时相特征、极化特征以及干涉相干特征进行分类,可解决双极化SAR影像中林地与城市及建设用地的混分问题,得到更高精度的土地覆盖分类结果。

关键词: 多时相, 极化, 干涉合成孔径雷达, 土地覆盖分类

Abstract:

In order to study SAR land cover classification method, this paper uses the multi-dimensional combination of temporal,polarization and InSAR data. The area covered by space borne data of ALOS PALSAR in Xunke County,Heilongjiang Province was chosen as test site. A land cover classification technique of SVM based on multi-temporal, multi-polarization and InSAR data had been proposed, using the sensitivity to land cover type of multi-temporal, multi-polarization SAR data and InSAR measurements, and combing time series characteristic of backscatter coefficient and correlation coefficient to identify ground objects. The results showed the problem of confusion between forest land and urban construction land can be nicely solved, using the correlation coefficient between HH and HV, and also combing the selected temporal, polarization and InSAR characteristics. The land cover classification result with higher accuracy is gotten using the classification algorithm proposed in this paper.

Key words: multi-temporal, polarization, InSAR, land cover classification

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