Development of a model for predicting soil moisture dynamics

Abstract

This paper discusses the development of a model for predicting soil moisture dynamics based on remote sensing data and soil characteristics using neural networks. In the course of the study, preliminary data processing was carried out, including scaling of features and analysis of correlations between them. The constructed model showed high accuracy of predictions, which is confirmed by the values of the standard error (0.00849) and the coefficient of determination (0.854). The test results demonstrated the ability of the model to effectively reproduce the actual values of soil moisture, which makes it a useful tool for water management and planning of agrotechnical measures. In conclusion, possible ways to further improve the model and expand its application are discussed.