Snow space-time analysis and prediction method based on random forest

The invention provides an accumulated snow space-time analysis and prediction method based on a random forest, and the method comprises the steps: constructing a space weight matrix according to the space relation between geographic units, carrying out the feature decomposition of the centralized space weight matrix, screening a feature vector, taking the feature vector as an independent variable together with an environment variable, brightness temperature data and accumulated snow density, and carrying out the prediction. Modeling by using a random forest method; substituting optimal parameters obtained by modeling into all samples to obtain a random forest regression model, and analyzing influence factors of accumulated snow changes; and finally, substituting the optimal parameter into the new independent variable to obtain a predicted value of the accumulated snow. According to the method, the influence of environmental factors and spatial effects on the change of accumulated snow is considered at the sam