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遥感技术与应用  2012, Vol. 27 Issue (5): 790-796    DOI: 10.11873/j.issn.1004-0323.2012.5.790
遥感应用     
基于小波分析的河道主溜线遥感检测研究
韩 琳1,2,张艳宁1,刘学工2,宋瑞鹏2,吴 岩2
(1.西北工业大学计算机学院,陕西 西安 710072;2.黄河水利委员会,河南 郑州 450004)
Research on River Main-stream Detection with WaveletTransform from Remote Sensing
Han Lin1,2,Zhang Yanning1,Liu Xuegong2,Song Ruipeng2,Wu Yan2
(1.School of Computer Science & Technology,Northwest polytechnical University,Xi an 710072,China;
2.Yellow River Conservancy Commission,Zhengzhou 450004,China)
 全文: PDF(3070 KB)  
摘要:

河道主溜是河势的关键要素,是防洪决策需要及时掌握的重要信息,遥感则是快速获取河道主溜的重要途径。根据对现实河道水流中主溜表象的实际观测,分析了河道横断面上主溜区域与非主溜区域表象特征,提出了基于小波多尺度峰值分析的河道主溜检测算法,并利用黄河下游河道TM遥感影像进行了主溜检测实验,以人工查勘主溜线为真值,对检测结果进行了精度评价,验证了该算法对检测河道主溜的有效性。

关键词: 小波变换TM图像黄河下游河势主溜    
Abstract:

River Main-stream is the key factor of river regime,which is a very important information for flood control decision.It is a good approach to get the main-stream information from remote sensing images in time.According to the field observation on water surface phenomena of river main-stream,water surface characteristics on main-stream and non main-stream were analyzed on river transect,and a river main-stream detection algorithm based on wavelet transform and its multi-scale peak value analysis was proposed.The proposed algorithm was verified by TM images on the lower reaches of Yellow River,and the precision was evaluated through comparing with manual-surveyed line on the same reaches,therefore the results validated that the proposed method can be used to river main-stream detection in the lower Yellow River.

Key words: Wavelet transform    TM image    Yellow river    River regime    Main-stream
收稿日期: 2012-04-27 出版日期: 2012-10-17
:  TP 753  
基金资助:

教育部高等学校科技创新工程重大项目培育资金项目“黄河自然灾害信息监测与预警网络系统” (708085)。

作者简介: 韩 琳(1978-),女,陕西渭南人,博士研究生,主要从事遥感技术应用研究。Email:hanlin@xxzx.yrcc.gov.cn。
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引用本文:

韩 琳,张艳宁,刘学工,宋瑞鹏,吴 岩. 基于小波分析的河道主溜线遥感检测研究[J]. 遥感技术与应用, 2012, 27(5): 790-796.

Han Lin,Zhang Yanning,Liu Xuegong,Song Ruipeng,Wu Yan. Research on River Main-stream Detection with WaveletTransform from Remote Sensing. Remote Sensing Technology and Application, 2012, 27(5): 790-796.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2012.5.790        http://www.rsta.ac.cn/CN/Y2012/V27/I5/790

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