Identification and classification of disturbed lands based on geodata of satellite images using machine learning methods
Year: 2025
Type: dissertation
Abstract: The thesis is devoted to the development of an information technology for detecting and classifying disturbed lands using machine learning methods based on satellite data. Algorithms and a process model for data processing, storage, validation and visualization of geodata are proposed. A prototype system was created and tested on real data. Scientific novelty lies in the data management algorithm for monitoring. Practical significance—improved speed and accuracy of environmental monitoring.
Authors: Горбунов, А. В., Gorbunov, A. V.
Language: Russian
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: green
OpenAlex ID: W7115040189