Geospatial database generation of forest growth using the QGIS software package

Abstract This article discusses the use of machine learning methods in the QGIS software package to create a geographic information database of forest growth. The authors explore the possibilities of applying machine learning algorithms to analyse satellite images of different resolutions and geospatial data to determine the growth of forest resources. The authors consider classification and forecasting methods and their advantages in the context of creating a database for tracking and managing forest resources. The research results confirm the effectiveness of using machine learning in QGIS for accurate and automated analysis of the dynamics of changes in forest cover, which can serve as a basis for decision-making in the field of forestry and protection of natural resource potential.