Development of a methodology for calculating carbon units of heterogeneous territories based on machine learning

Abstract

The paper describes a method for calculating carbon units of heterogeneous territories based on machine learning. The hierarchical structure of areal territories and the structure of the interconnection of multi-scale images are described. An approach is given to identify and classify terrain objects in order to more accurately calculate the carbon reserve of the territory.