INFORMATION TECHNOLOGIES FOR SUSTAINABLE DEVELOPMENT OF FOREST RESOURCES
Section: GENERAL SECTION
Authors:
1.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
2.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
3.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
4.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
Type:
Сonference article
Published:
18.06.2025
Subject area:
004
Language:
Russian
Keywords:
digitalization, big data, geographic information systems, remote sensing, predictive modeling, forest monitoring, analytical systems, sustainable forest management, FORRUS-S, forestry
Abstract (English):
The article considers the application of big data technologies in the digitalization of forestry in Russia. The integration of remote sensing with GIS systems for real-time forest monitoring is analyzed. Modern methods for forecasting the state of forests are described, including analytical, empirical-statistical and simulation models. The Russian forecasting and modeling complex FORRUS-S for assessing the dynamics of forest stands is presented. The role of analytical tools in optimizing logging and preventing violations of the law is emphasized. The need to consolidate information sources and use spatial data for making management decisions is substantiated. It is demonstrated how digital technologies contribute to the balance between economic efficiency and environmental sustainability of Russian forests.
The article considers the application of big data technologies in the digitalization of forestry in Russia. The integration of remote sensing with GIS systems for real-time forest monitoring is analyzed. Modern methods for forecasting the state of forests are described, including analytical, empirical-statistical and simulation models. The Russian forecasting and modeling complex FORRUS-S for assessing the dynamics of forest stands is presented. The role of analytical tools in optimizing logging and preventing violations of the law is emphasized. The need to consolidate information sources and use spatial data for making management decisions is substantiated. It is demonstrated how digital technologies contribute to the balance between economic efficiency and environmental sustainability of Russian forests.
Keywords:
digitalization, big data, geographic information systems, remote sensing, predictive modeling, forest monitoring, analytical systems, sustainable forest management, FORRUS-S, forestry
digitalization, big data, geographic information systems, remote sensing, predictive modeling, forest monitoring, analytical systems, sustainable forest management, FORRUS-S, forestry
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