Comparison and analysis on the statistical models for the diurnal variations of lake ice albedo under clear skies of Lake Ulansuhai

Tang, Mingguang; Li, Zhijun; Lu, Peixiang; Cao, X.; Li, Guoyu; Leppäranta, Matti; Arvola, Lauri; Shi, Lijuan

doi:10.18307/2020.0625

Journal of Lake Sciences

2020

DOI: 10.18307/2020.0625

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Comparison and analysis on the statistical models for the diurnal variations of lake ice albedo under clear skies of Lake Ulansuhai

Mingguang Tang¹,

Zhijun Li²,

Peixiang Lu³

et al.

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Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features

et al. 2023

Water Science &Amp; Technology

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One of the most important indicators of lake eutrophication is chlorophyll-a (Chl-a) concentration, which is also an essential component of lake water quality monitoring. It is an efficient, economical and convenient method to monitor the Chl-a concentration through remote sensing images. Taking the Wuliangsuhai Lake as an example, the relevant bands of Sentinel-2 images were used as the input and the Chl-a concentration as the output to build neural network models. In the process of building the model, we mainly studied and tested the impact of adding time features to the model input on the model accuracy. Through the experiment, it was found that the month and day difference features of remote sensing images and Chl-a measurement could significantly improve the prediction accuracy of Chl-a concentration in varying degrees. Finally, it was determined that the neural network prediction model with 12 bands of Sentinel-2 images combined month features as inputs and 1 hidden layer, 8 neurons and Chl-a concentration as outputs was the best. Then, the accuracy of the model was validated when the test set accounts for 20 and 30%, and good results were obtained.

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Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features

et al. 2023

Water Science &Amp; Technology

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Comparison and analysis on the statistical models for the diurnal variations of lake ice albedo under clear skies of Lake Ulansuhai

Cited by 1 publication

References 7 publications

Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features

Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features

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