基于面向对象方法的Sentinel-1A SAR在洪水监测 中的应用

doi:10.12082/dqxxkx.2018.170599

地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (3): 377-384.doi: 10.12082/dqxxkx.2018.170599

基于面向对象方法的Sentinel-1A SAR在洪水监测中的应用

汤玲英¹(), 刘雯^1,^2,^*(), 杨东¹, 陈乐¹, 苏扬媚¹, 徐宪立³

1. 湖南师范大学资源与环境科学学院,长沙 410081
2. 湖南师范大学地理空间大数据挖掘与应用湖南省重点实验室,长沙 410081
3. 中国科学院亚热带农业生态研究所,长沙 410125

收稿日期:2017-12-15 修回日期:2018-01-14 出版日期:2018-03-20 发布日期:2018-03-20
通讯作者: 刘雯 E-mail:595834337@qq.com;liuwenww@gmail.com
作者简介:
作者简介：汤玲英（1992-）,女,硕士生,研究方向为生态遥感应用研究。E-mail: 595834337@qq.com
基金资助:
国家自然科学基金项目（41501478）;湖南省重点学科地理学（2016001）;湖南省自然科学基金项目（2015JJ6068）

Flooding Monitoring Application Based on the Object-oriented Method and Sentinel-1A SAR Data

TANG Lingying¹(), LIU Wen^1,^2,^*(), YANG Dong¹, CHEN Le¹, SU Yangmei¹, XU Xianli³

1. College of Resources and Environmental Science, Hunan Normal University, Changsha 410081, China
2. Key Laboratory of Geospatial Big Data Mining and Application, Changsha 410081, China
3. Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China

Received:2017-12-15 Revised:2018-01-14 Online:2018-03-20 Published:2018-03-20
Contact: LIU Wen E-mail:595834337@qq.com;liuwenww@gmail.com
Supported by:
National Natural Science Foundation of China, No.41501478;Construction Program of the Key Discipline in Hunan Province, No.2016001;National Natural Science Foundation of Hunan China, No.2015JJ6068.

摘要/Abstract

摘要：

开展Sentinel-1A SAR数据在洪水淹没范围提取和水体变化监测方面的应用研究,对科学有效地管理洪涝灾害有重要意义。合成孔径雷达以其不受天气影响、能穿透云层、覆盖面积广等特点成为灾害监测的重要数据来源。面向对象的方法能有效解决影像的椒盐现象被广泛运用于信息提取研究。本文基于Sentinel-1A SAR数据,利用面向对象的方法构建洪水淹没范围提取流程,绘制灾前、灾中、灾后水体变化监测图,对比分析基于传统像元的提取方法,实现对广西临桂会仙岩溶湿地区域不同时期洪水动态监测。研究表明,Sentinel-1A SAR数据在洪水监测领域有巨大的应用潜力,相较于传统基于像元的方法,面向对象的方法能有效抑制杂斑生成,提高空间信息的利用效率,具有更好的提取精度。

关键词: Sentinel-1A, SAR, 洪水, 面向对象, 淹没范围, 喀斯特

Abstract:

In recent years, flood disasters have emerged successively, so extracting the disaster range and studying detection of the change of water body are of great significance to the scientific and effective management of flood disasters. Synthetic Aperture Radar (SAR) has the ability of penetrating clouds and generating ground information and it can collect data from large areas under any weather conditions. SAR has become an important means of natural disasters observation. Sentinel-1A is an important part of satellite in ESA's Copernicus Programm for monitoring environment. Therefore, discussions of the application of Sentinel-1A SAR data to the monitoring of flood disaster is meaningful. The traditional pixel-based methods have limitation in image speckle noise suppression, so the object-oriented method is introduced in this study. This study takes Sentinel-1A SAR images of the pre-flood, flooding and after-flood periods as data source. We introduce the object-oriented classification software - eCognition 9.0 to establish an extraction process of flooding area. Firstly, we use the SNAP software to preprocess the Sentinel-1A SAR images. Then, to account for objects features, we conduct experiments using multi-scale segmentation of eCognition 9.0, comparative analysis of the experimental results and we use the prior knowledge to determine the optimal segmentation scale. Based on the assigned class function of eCognition 9.0, we analyze the VV polarization mean feature to extract flooding area. Meanwhile, we use DEM data to remove the hill-shade in water extraction. Using the methods above, the detection of flood dynamic changes of different periods and flood submerge area extracted in the Huixian karst wetland in Guangxi was realized. Maps of the detection of flood changes in the pre-flood, flooding and after-flood periods were plotted. At last, we compared the traditional pixel-based water extraction method (Unsupervised classification and OSTU threshold segmentation). This research shows that Sentinel-1A SAR data has a great application potential in flood detection field. Compared with the traditional pixel-based method, the object-oriented method can effectively avoid the “salt and pepper phenomenon”, have high precision in flooding area extraction and can improve the utilization of spatial information.

Key words: Sentinel-1A SAR, flood, object-oriented, flood submerge area, Karst

汤玲英, 刘雯, 杨东, 陈乐, 苏扬媚, 徐宪立. 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.DOI:10.12082/dqxxkx.2018.170599

TANG Lingying,LIU Wen,YANG Dong,CHEN Le,SU Yangmei,XU Xianli. Flooding Monitoring Application Based on the Object-oriented Method and Sentinel-1A SAR Data[J]. Journal of Geo-information Science, 2018, 20(3): 377-384.DOI:10.12082/dqxxkx.2018.170599

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获取卫星	Sentinel-1A
极化方式	VV/VH
地距分辨率/m	20×22（方位向×距离向）
像元大小/m	10×10（方位向×距离向）
工作模式	干涉宽幅（宽幅250 km）
入射角度/°	30.797~46.22
影像时间	2016年4月03日（灾前） 2016年5月21日（灾中） 2016年6月14日（灾中） 2016年8月25日（灾后） 2017年5月28日（灾前） 2017年7月03日（灾中） 2017年7月15日（灾后）

基于面向对象方法的Sentinel-1A SAR在洪水监测中的应用

Flooding Monitoring Application Based on the Object-oriented Method and Sentinel-1A SAR Data

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基于面向对象方法的Sentinel-1A SAR在洪水监测 中的应用

Flooding Monitoring Application Based on the Object-oriented Method and Sentinel-1A SAR Data

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基于面向对象方法的Sentinel-1A SAR在洪水监测中的应用