Information technologies for visualization and data processing in the sphere of geospatial intelligence

DOI: 10.31673/2412-4338.2024.044726

Abstract

Current research demonstrates the great potential of the integration of big data technologies and artificial intelligence for automated decoding of satellite images, monitoring of landscape changes, detection of violations and prediction of man-made risks. The use of machine learning algorithms in the visualization of geodata significantly accelerates the analysis of information of large arrays, which is critically important for environmental monitoring during military operations and rapid recovery of the territory. The detection of the state of ground objects is significantly improved by the use of multispectral and hyperspectral images, in particular from unmanned aerial vehicles, after their differentiation allows the creation of high-quality information products. However, hyperspectral images from space height still do not provide the necessary level of detail for operational-tactical intelligence. Research highlights the effectiveness of integrating big data and artificial intelligence for automatically deciphering satellite images, monitoring landscape changes, and assessing man-made risks. The use of machine learning algorithms accelerates the processing of large sets of data, which is a special place for environmental monitoring during military operations and territory recovery. Increasing the accuracy of detecting the state of objects is achieved with the help of multispectral and hyperspectral images, especially obtained from drones, and the latest images from the space platform still lack sufficient detail for operational tasks.

Keywords: information technologies, artificial intelligence, spectral channels, remote methods. machine learning algorithm, visualization of geodata, decoding of satellite images

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