Methodology for Optimizing Vulnerability of Critical Infrastructure Objects Through Space Data and Artificial Intelligence Using “Cost-benefit” Approach

Critical infrastructure constitutes the backbone of modern society, encompassing sectors such as energy, transportation, and water supply.Risk assessment of critical infrastructure objects is an important task that helps to identify and analyse the potential threats and vulnerabilities of such objects.In recent years, especially after the outbreak of the war in Ukraine, the importance of space infrastructures (ground and space) has grown and they were included in the list of 11 areas of critical infrastructure in the latest EU directive.On the other hand, space technologies appear in key enablers to support resilient & sustainable Critical Infrastructure.This study examines the novel combination of multispectral satellite images and powerful machine learning algorithms, which together have exceptional prospects for enhancing the effectiveness and precision of evaluating and overseeing crucial infrastructure systems.