测绘通报 ›› 2017, Vol. 0 ›› Issue (10): 34-38.doi: 10.13474/j.cnki.11-2246.2017.0312

• 学术研究 • 上一篇    下一篇

一种改进光谱角匹配的水体信息提取方法

张伟1,2, 赵理君1, 郑柯1, 唐娉1   

  1. 1. 中国科学院遥感与数字地球研究所, 北京 100101;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2017-02-21 修回日期:2017-07-12 出版日期:2017-10-25 发布日期:2017-11-07
  • 通讯作者: 郑柯。E-mail:zhengke@radi.ac.cn E-mail:zhengke@radi.ac.cn
  • 作者简介:张伟(1992-),男,硕士生,现从事遥感图像处理与分类方面的研究。E-mail:zhangw@radi.ac.cn
  • 基金资助:
    高分辨率对地观测系统重大专项(03-Y20A04-9001-15/16;11-Y20A05-9001-15/16)

An Improved Method for Water Information Extraction Using MSAM

ZHANG Wei1,2, ZHAO Lijun1, ZHENG Ke1, TANG Ping1   

  1. 1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-02-21 Revised:2017-07-12 Online:2017-10-25 Published:2017-11-07

摘要: 快速、准确地从卫星遥感影像上获取水体信息已成为水资源调查及监测、湿地保护、洪涝灾害评估等领域的重要技术手段。本文以GF-4卫星的PMS传感器影像为数据源,提出了一种改进光谱角匹配(MSAM)的水体信息提取方法,以内蒙古中东部和长江中下游两个试验区为研究对象,对比分析了MSAM与单波段阈值法、NDWI阈值法、支持向量机和光谱角匹配等传统方法的水体信息提取结果,并进行了精度评价。试验结果表明,本文提出的MSAM方法不仅能准确地提取水体信息,而且能很好地区分水体与云阴影,对细小水体的提取也具有很好的效果。在内蒙古中部和长江中下游两个试验区的水体提取精度分别达到99.86%和98.37%,在5种水体提取方法中的精度最高,可以有效地提取水体信息。

关键词: 水体提取, 归一化差分水体指数, 支持向量机, 改进光谱角匹配

Abstract: Quickly and accurately obtaining water information from satellite remote sensing imagery has become an important technical means in the field of water resources investigation and monitoring,wetland protection,and flood disaster assessment. In this paper,a new water extraction method of a modified spectral angle mapping (MSAM) is proposed and GF-4's PMS images are used as research data.Two typical study areas are investigated, which are selected from the areas of middle-east of Inner Mongolia and middle-lower reaches of the Yangtze River.To evaluate the efficacy of the proposed MSAM method,four compared methods including single band threshold,NDWI threshold, support vector machine (SVM) and spectral angle mapping (SAM) are used in water extraction.Then accuracy assessments are taken on the water extraction results of the five different methods.The results show that the proposed method can not only extract water information accurately,but also distinguish water and the cloud shadows well and have a good ability in extracting small water bodies.And it obtains the highest accuracy compared with the other four water extraction methods,with the water extracting accuracies of the two study areas reaching 99.86% and 98.37% respectively.To sum up,the proposed method can be effectively used to extract water information of GF-4 remote sensing imagery.

Key words: water extraction, normalized difference water index, support vector machine, modified spectral angle mapping

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