Inversion of suspended sediment distribution in Hangzhou Bay using artificial neural network algorithm

Xiaoqian Zhu; Fei Su; Zepeng Jin

doi:10.1117/12.3012465

21 December 2023 Inversion of suspended sediment distribution in Hangzhou Bay using artificial neural network algorithm

Xiaoqian Zhu, Fei Su, Zepeng Jin

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129701O (2023) https://doi.org/10.1117/12.3012465
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

The density of suspended particles is a crucial indicator for assessing the water quality, the study was based on high score 1 (GF-1) satellite remote sensing image, using a neural network model, choosing a double hidden layer set, building the Hangzhou bay turbid water suspended sediment concentration inversion model, to analyze the space-time characteristics of the suspended sediment density, and comparing with other conventional precision inversion method. The findings demonstrate that retrieving the suspended sediment concentration in Hangzhou Bay using the BP neural network model is viable, and compared with other conventional methods, the model has a higher correlation (R2 = 0.9398) for the inversion of turbidity water with higher suspended sediment concentration. In the spatial distribution of the Hangzhou bay area water suspended sediment concentration is high overall, Hangzhou bay water suspended sediment concentration to an average of 679 mg/L, the inversion results show that the water in Hangzhou Bay has a high overall concentration of suspended silt, internal differences obviously, among them the highest of the central region, and diminishing the coast gradually to bay mouth, respectively.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoqian Zhu, Fei Su, and Zepeng Jin "Inversion of suspended sediment distribution in Hangzhou Bay using artificial neural network algorithm", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129701O (21 December 2023); https://doi.org/10.1117/12.3012465

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