Information technology for monitoring environmental threats using aerospace data and artificial intelligence

Abstract

The article is devoted to solving an urgent scientific and applied problem related to the development of information technology for monitoring environmental threats based on the integration of aerospace data and artificial intelligence methods. Modern environmental monitoring systems require the use of advanced information technologies capable of processing large volumes of heterogeneous spatial data and providing reliable information about the state of natural and anthropogenic systems.
The proposed approach is based on the integrated use of satellite remote sensing data, unmanned aerial vehicle observations, geoinformation technologies, and machine learning algorithms. The developed information technology includes methods for collecting, processing, and analyzing aerospace data, as well as algorithms for automated identification of environmental threats.
Special attention is paid to the use of artificial intelligence methods for automated interpretation of satellite images and the detection of environmental changes in marine and coastal ecosystems. Neural network models are used to perform classification and segmentation of remote sensing data, which significantly increases the accuracy of identifying environmental hazards. The main functional subsystems of the technology have been identified, which provide a consistent information processing cycle – from the collection of aerospace data to the formation of analytical materials for assessing the state of the natural environment.
The proposed technology also provides the creation of geoinformation models for assessing environmental risks and forecasting the development of hazardous processes. The developed algorithms make it possible to automate the processes of environmental monitoring and support decision-making in environmental management systems.
The results of the research can be used in environmental monitoring systems, decision support systems for environmental safety, and in the development of intelligent geoinformation systems. Further research should be directed towards improving artificial intelligence algorithms for processing aerospace data and expanding the capabilities of environmental monitoring information systems.