基于Sentinel-1B SAR数据的洪水提取和监测

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英文篇名：Flood Extraction and Monitoring Based on Sentinel-1B SAR Data 作者：吴文会 ; 王丽欣 ; 马卓 英文作者：WU Wenhui;WANG Lixin;MA Zhuo;Polar Surveying and Mapping Engineering Center of Heilongjiang Bureau of Surveying,Mapping and Geoinformation;Heilongjiang Provincial Society of Surveying,Mapping and Geoinformation;Heilongjiang Institute of Technology; 关键词：Sentinel-1B ; SAR ; 洪水 ; OSTU阈值分割 ; 随机森林分类 英文关键词：Sentinel-1B SAR;;flood;;OSTU threshold segmentation;;random forest classification 中文刊名：DBCH 英文刊名：Geomatics & Spatial Information Technology 机构：黑龙江测绘地理信息局极地测绘工程中心;黑龙江省测绘地理信息学会;黑龙江工程学院; 出版日期：2019-04-25 出版单位：测绘与空间地理信息 年：2019 期：v.42;No.240 语种：中文; 页：DBCH201904032 页数：3 CN：04 ISSN：23-1520/P 分类号：120-121+128

摘要

洪涝灾害是我国最严重的气象灾害之一,及时准确的洪灾监测是防灾减灾的重要前期工作和基础。本文利用sentinel-1B雷达数据,以黑瞎子岛为研究区,联合使用OSTU阈值分割法和随机森林面向对象分类法针对像素统计单波形、双波形、多波形SAR影像提取洪水要素,实现对洪灾淹没面积的时序监测,为灾情监测提供数据和技术支撑。
        Flood disaster is one of the most serious meteorological disasters in China. How to realize timely and accurate flood monitoring is an important preceding and foundation for disaster prevention and mitigation. Using sentinel-1 B radar data and taking Heixiazi Island as the research area,this paper uses OSTU threshold segmentation method and random forest object-oriented classification method to extract flood elements from single-waveform,double-waveform and multi-waveform SAR images of pixel statistics,so as to realize sequential monitoring of flood inundated area,and provide data and technology for disaster monitoring.

引文

[1]汤玲英,刘雯,杨东,等.基于面向对象方法的Sentinel-1A SAR在洪水监测中的应用[J].地球信息科学学报,2018,20(3):377-384.
    [2]曾玲方,李霖,万丽华.基于Sentinel-1卫星SAR数据的洪水淹没范围快速提取[J].地理信息世界,2015,22(5):100-103.
    [3]孙亚勇,李小涛,杨锋杰,等.基于星载SAR数据的山区水体提取方法研究[J].中国水利水电科学研究院学报,2014,12(3):258-263.