Computer Visualization for the Algorithmization and Programming Task of Territorial Division Based on Interactive Mapping

The division of the territory into regions according to some attribute is the most important factor in the effective management of spatial development at the national, macroregional and regional levels of the economy. Applying a defragmented policy on this basis makes it possible to increase both the quality of public space management and the effectiveness of strategic planning. The author's method for visualizing the task of creating a digital twin of the economic zoning grid is presented in this paper based on interactive mapping as well as on the systematization of methods for reflecting the results of territorial division. The concept of economic complexity was used as a methodological approach, which is based on an understanding of the importance of producing complex products that require a wide range of knowledge and competencies. The basis for the visualization of economic zoning is the author's mathematical algorithm for territorial division of the country into macroeconomic regions, compiled on the basis of graph theory and implemented in the Graphviz software. The creation of a digital twin of the macroregions grid is based on the indicator "Average number of employees for the full range of organizations", according to which a single statistical database was formed for 83 regions of Russia for the period from 2009-2019 for 104 types of economic activity. The graph visualizes the strongest links between sectors of the economy by constructing a maximum spanning tree based on the Kruskal algorithm. The vertices of the industry connectivity graph are the types of activities according to OKVED, and the edges are the “distances” between them. To automate the process of creating a digital twin of the macroregions grid and its visualization, a software tool in the Python language was used. The advantage of the proposed visualization method is that the display of simulation results using interactive mapping allows reflecting all types of economic activity and the relationships between them in an easy-to-read format. This, in turn, makes it possible to predict the behavior of economic sectors in order to enhance the development of the constituent entities of the Russian Federation and the spatial development of the country as a whole.