Water information extraction in Shanghai by integrating random forest model and six water indices

doi:10.13474/j.cnki.11-2246.2022.0052

Abstract

Abstract: In order to know water distribution information quickly and accurately, this paper selects Shanghai as the study area，constructs a feature set of water extraction based on multi-temporal Sentinel-2 satellite data, uses random forest model with high efficiency and good robustness to extract water in Shanghai. To improve the accuracy of water extraction, six water indices are added into the feature set of water extraction based on the characteristics of existing spectral bands: NDWI、MNDWI、AWEI_sh、WI₂₀₁₅、SWI and RWI. According to the characteristics of 10 spectral bands and 6 water indices, eight experimental schemes are designed to explore the effect of adding water indexes on water extraction. The results show that the scheme which included all the six water indices has the highest overall accuracy, which is 97.910%. NDWI and RWI can also improve the accuracy of water extraction and reduce the rate of leakage and error.

Key words: water information extraction, RF model, Sentinel-2, water index, Shanghai city

CLC Number:

P237

CUI Qinglin, WANG Mingquan, HUANG Yongjian. Water information extraction in Shanghai by integrating random forest model and six water indices[J]. Bulletin of Surveying and Mapping, 2022, 0(2): 106-109.

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