Land water reserve prediction method and equipment based on neural network algorithm

Abstract

The invention provides a land water reserve prediction method and equipment based on a neural network algorithm. The land water reserve prediction method comprises the following steps: acquiring spatial resolution of surface parameter information, land water reserve information and land water reserve information; carrying out resampling for reducing the spatial resolution on the surface parameterinformation to obtain first surface parameter information; constructing a neural network regression model based on the first surface parameter information and the land water reserve information; obtaining target surface parameter information in to-be-predicted time, and performing resampling for reducing spatial resolution on the target surface parameter information to obtain second surface parameter information; and inputting the second surface parameter information into the neural network regression model, and determining land water reserve information corresponding to the target surface parameter information within to-be-predicted time. Compared with the prior art, the method can achieve the precise prediction of the land water reserve information in a historical period, and obtains theland water reserve dynamic change data in a long time sequence.

Description

technical field [0001] The invention relates to the technical field of geographic information, in particular to a method and equipment for predicting land water storage based on a neural network algorithm. Background technique [0002] The earth is a dynamical system that changes with time and space, and the redistribution of mass in the earth system will lead to changes in the earth's gravitational field on different time scales. Thus, the migration and exchange of matter can be understood by using gravity observations. In the study of material migration, terrestrial water storage is of great significance to global climate change, economic development and human life. [0003] However, due to the limitation of the level of scientific development in the early years, gravity satellites could not be launched to detect changes in the earth's gravitational field. Therefore, it was impossible to obtain land water storage information in the historical period. There is a problem, ...

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Problems solved by technology

[0003] However, due to the limitation of the level of scientific development in the early years, gravity satellites could not be launched to detect changes in the earth's gravitational field. Therefore, it was impossible to obtain land water storage information in the historical period. There is a problem, and the existing methods for retrospective reconstruction of land water storage information have poor learning ability and weak noise resistance

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