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冰川冻土 ›› 2013, Vol. 35 ›› Issue (3): 636-647.doi: 10.7522/j.issn.1000-0240.2013.0073

• 冰冻圈与全球变化 • 上一篇    下一篇

基于合成孔径雷达(SAR)的积雪监测研究进展

孙少波1,2, 车涛1   

  1. 1. 中国科学院寒区旱区环境与工程研究所, 甘肃 兰州 730000;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2012-10-20 修回日期:2013-01-22 出版日期:2013-07-25 发布日期:2013-07-25
  • 通讯作者: 车涛,E-mail:chetao@lzb.ac.cn E-mail:chetao@lzb.ac.cn
  • 作者简介:孙少波(1988- ), 男, 陕西宝鸡人, 2011年毕业于西北大学, 现为在读硕士研究生, 主要从事冰冻圈遥感研究.E-mail: sunshaobo133@163.com
  • 基金资助:

    中国科学院西部行动计划三期项目(KZCX2-XB3-15); 国家自然科学基金项目(40971188; 41271356)资助

A Review of the Research on Snow Cover Monitored with Synthetic Aperture Radar (SAR)

SUN Shao-bo1,2, CHE Tao1   

  1. 1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou Gansu 730000, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-10-20 Revised:2013-01-22 Online:2013-07-25 Published:2013-07-25

摘要:

积雪是冰冻圈中最重要的组成要素之一, 积雪研究对于气候变化、 水文循环等科学研究和农业灌溉、 减灾防灾等生产活动都具有重要意义.合成孔径雷达(SAR)不仅具有穿云透雾, 全天候观测地表的能力, 而且可穿透地表覆盖一定深度获取地表覆盖物内部特征信息.近年来SAR技术在冰冻圈科学研究中已广泛应用. 综述了SAR积雪监测研究的国内外进展, 对当前主要的SAR积雪遥感模型进行了总结分析, 着重介绍了当前主要的SAR和SAR干涉测量技术(InSAR)积雪面积制图方法、 雪水当量(SWE)反演算法、 积雪密度和雪深提取方法, 并对未来可能的研究方向进行了展望.

关键词: 积雪, 雪深, 雪密度, 雪水当量, SAR, InSAR

Abstract:

Snow is one of the most important elements in cryosphere. Most of snow cover is located in the remote regions where access is difficult and the climate and transportation conditions are poor. Thus remote sensing technology becomes a very useful and efficient method to obtain the snow information. Compared with optical remote sensing and passive microwave remote sensing, synthetic aperture radar (SAR) not only has the capabilities of penetrating clouds and providing day and night remote sensing data, but also has the capability of penetrating snow cover to retrieve subsurface information. In this review, the snow cover researches by SAR data in recent years, including several existing algorithms of SAR and InSAR to identify snow cover and estimate of snow water equivalent, snow depth, snow density and snow wetness, are described.

Key words: snow cover, snow depth, snow density, snow water equivalent, SAR, InSAR

中图分类号: 

  • P407