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JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)  2017, Vol. 51 Issue (12): 2474-2480    DOI: 10.3785/j.issn.1008-973X.2017.12.022
Remote Sensing and Information Engineering     
Extraction of water information in complex water-net plain with Chinese GF-2 remotely sensed images
FU Yong-yong1, WANG Xu-hang2, DENG Jin-song1, YE Zi-ran1, ZHOU Meng-meng1, YOU Shu-cheng3, GUAN Tao4
1. Institute of Remote Sensing and Information Technique, Zhejiang University, Hangzhou 310029, China;
2. Power China Huadong Engineering Co. Ltd, Hangzhou 311122, China;
3. China Land Surveying and Planning Institute, Beijing 100035, China;
4. Zhejiang Institute of Land Surveying and Planning, Hangzhou 310007, China
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Abstract  

Based on object-oriented image analysis, a methodology combing selecting optimal segmentation scale and feature rule was proposed to extract water information in Hang-Jia-Hu water-net plain from the GF-2 remotely sensed images. To realize the rapid extraction of water information, the rates of change of local variance (ROC-LV) was calculated to determine the optimal scale parameter, and the separability and thresholds (SEaTH) method was used to establish the feature rule. Results show that the overall accuracy is 98.7%, the Kappa coefficient is 0.96, and the precision and recall of extracted water information are both more than 97.3%. The proposed methodology can correctly extract complicated water information and meet the demand of practical application.



Received: 12 March 2017      Published: 22 November 2017
CLC:  TP751.1  
Cite this article:

FU Yong-yong, WANG Xu-hang, DENG Jin-song, YE Zi-ran, ZHOU Meng-meng, YOU Shu-cheng, GUAN Tao. Extraction of water information in complex water-net plain with Chinese GF-2 remotely sensed images. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(12): 2474-2480.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2017.12.022     OR     http://www.zjujournals.com/eng/Y2017/V51/I12/2474


采用国产GF-2遥感影像的复杂水网平原水体信息提取

以国产高分二号(GF-2)影像为数据源,选取杭嘉湖水网平原作为典型研究区域,基于面向对象分析技术,提出一种选取最佳分割尺度和特征规则的方法.该方法通过局部方差变化率(ROC-LV)曲线峰值确定最佳分割尺度,采用分离阈值法(SEaTH)建立提取规则,实现水体信息的快速提取.结果表明:总体精度达到98.7%,Kappa系数达到0.96,水体信息提取准确度和查全率均值都在97.3%以上.所提方法能够有效地提取水体信息,满足实际应用需求.

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