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费腾、硕士生别婉娟的论文在International Journal of Remote Sensing 刊出
发布时间:2020-08-25 10:51:32     发布者:易真     浏览次数:

标题: Small water bodies mapped from Sentinel-2 MSI (MultiSpectral Imager) imagery with higher accuracy

作者: Wanjuan Bie,Teng Fei ,Xinyu Liu,Huizeng Liu &Guofeng Wu

来源出版物: International Journal of Remote Sensing   : 41 期:20 DOI: 10.1080/01431161.2020.1766150  出版年:  15 Aug 2020

摘要: Small water bodies have always been an important part of water ecology systems. In the past, due to the limitations of satellite spatial resolution and recognition method precision, there have been few satisfactory remote sensing small water bodies extraction methods. In this article, a method based on index composition and HSI (hue, saturation, and intensity) colour space transformation is proposed to precisely extract small water bodies. An easy-to-deploy, fast, universal, and effective algorithm is used to accurately identify paddy fields and exclude shadows. This method is tested and verified with Sentinel-2 MSI (MultiSpectral Imager) images in seven cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Compared with the traditional modified normalized difference water index (MNDWI) and enhanced water index (EWI) water extraction methods, the proposed HSI method has shown a better performance in small water bodies mapping with a kappa coefficient of 0.94, overall accuracy of 97%, producer’s accuracy of 96%, and user’s accuracy of 98% in test regions, which is significantly higher than the benchmarking water extraction methods. It provides a powerful supplement for the remote sensing monitoring of water resources in surface water bodies. The method proposed in this study exhibits extendibility, it also has the potential to extract other small features with minor modifications of the method.

作者关键词:

地址:[ Wanjuan Bie, Teng Fei]School of Resource and Environmental Sciences, Wuhan University , Wuhan, China

[Xinyu Liu]School of Sociology, Wuhan University , Wuhan, China

[Huizeng Liu&Guofeng Wu]MNR Key Laboratory for Geo- Environmental Monitoring of Great Bay Area, Shenzhen University , Shenzhen, China ;Guangdong Key Laboratory of Urban Informatics, Shenzhen University , Shenzhen, China ;Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University , Shenzhen, China

通讯作者及电子邮件: Teng Fei , feiteng@whu.edu.en

影响因子:2.976


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