Method of integration of various data in the geospatial analysis system

The paper proposes a method of integrating disparate data in the geospatial analysis system, which consists in the fact that the geospatial analysis system combines the data received at its input in order to obtain more reliable and accurate data about the location of the object of analysis, its speed, attributive (additional) information and identity to a certain class, species or type, after which the analysis object's connections with other objects or events in the context of its surrounding environment are modeled, and then a generalized assessment of the state of the analysis object is formed by tracking telemetry and metadata. A feature of the method is that the geospatial analysis system at the stage of forming a generalized assessment of the state of the object of analysis together with the definition of conditions uses an improved procedure for forecasting changes in the state of the object of analysis, the essence of which is that the geospatial analysis system first builds an autoregressive forecasting model based on the Akaike information criterion, and then the geospatial analysis system compares the received forecasting error values with the reference values. The technical effect of using the specified method is to increase the efficiency of the geospatial analysis system by increasing the accuracy of forecasting the change in the state of the object of analysis.