A comparison study on the classification accuracy of 11 common water indices based on Landsat 8 OLI images

doi:10.7523/j.ucas.2023.088

Abstract

Abstract: Water index is one of the most effective methods to extract water bodies from remote sensing images. There are many kinds of water index, each with its own characteristics. It is, therefore, necessary to select the index with best classification accuracy. Taking Shijiazhuang city as the research area, 11 common water indices were used to extract water bodies from Landsat 8 OLI images. The accuracy of the water index extraction results is validated by using the Visual Interpretation (VI) result as the standard classification map from Sentinel-2 MSI based on the area test method in combination with transition matrix and sampling test method. Results show that there is little difference in the extraction of large water bodies among different water indices. Small ponds and rivers can better check the extraction ability of water index. It is proved that Water Index 2019 (WI2019) has the best water classification. WI2019 is then used to find out the recent expansion of water bodies after the start of South-to-North Water Diversion Project for water transfer. It is found out that the area of surface water body in Shijiazhuang excluding large reservoirs increased significantly, from 42 km² in 2014 to 62 km² in 2020, an increase of 20 km². In view of the canal seepage control treatment at the bottom of most newly added water bodies, with poor groundwater recharge function, and more ineffective evaporation, it is recommended to properly control the scale of water bodies in order to effectively reduce the waste of water transferred from outside.

Key words: Water Index, Accuracy Validation, Landsat 8 OLI, GEE, South-to-North Water Diversion Project

CLC Number:

K903

LI Longjie, YANG Yonghui. A comparison study on the classification accuracy of 11 common water indices based on Landsat 8 OLI images[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas.2023.088.

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