Training method of water quality parameter inversion model, and water quality monitoring method and device

Abstract

The invention provides a training method of a water quality parameter inversion model, and a water quality monitoring method and device. The training method comprises the following steps: acquiring water quality parameters and hyperspectral data in a target time period; performing waveband processing on the hyperspectral data to obtain multi-waveband spectral data; conducting correlation analysison the water quality parameters and the multiband spectral data, and taking the multiband spectral data corresponding to the multiple bands with the maximum correlation as target spectral data; and based on a training set constructed by the water quality parameters and the target spectral data, training a pre-constructed back propagation neural network until the back propagation neural network reaches convergence, thereby obtaining a water quality parameter inversion model. The method breaks through the limitation that an existing method is influenced by the time-phase characteristics of remote sensing images and models are difficult to unify, and reduces the analysis difficulty between the water quality parameters and the hyperspectral data.

Description

technical field [0001] The present application relates to the field of computer technology, in particular, to a training method of a water quality parameter inversion model, a water quality monitoring method, a device, an electronic device and a storage medium. Background technique [0002] Water quality monitoring is an important process in the study of water pollution. At present, water quality monitoring uses empirical methods, semi-empirical methods, and analytical methods to establish the relationship between remote sensing data and water quality parameters under multi-spectral bands. Remote sensing data of different water bodies in different spectral bands is an important basis for water quality monitoring. [0003] However, due to the complex optical characteristics of inland water bodies and fewer multispectral bands, it is difficult for the above methods to distinguish the differences of water quality parameters in the spectral bands, which brings great difficulties...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiment of the present application is to provide a training method for water quality parameter inversion model, water quality monitoring method, device, electronic equipment and storage medium, aiming at solving the problem that it is difficult to establish the relationship between remote sensing data and measured water quality parameters in current water quality monitoring

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