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

ABSTRACT

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.

Acknowledgements

This work was supported by the Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20180507182022554). Sincere thanks to Junjie Li, Lei Guo, Yukun Wu, Lingjun Wang in Wuhan University for their help in data processing, thanks to Yingjing Huang in Wuhan University for her help in figures processing.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Basic Research Program of Shenzhen Science and Technology Innovation Committee [No. JCYJ20180507182022554].