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Abstract <p>In this paper, the risk of ice formation on main pipelines laid in permafrost soils using the Power of Siberia gas pipeline as an example has been estimated. Icing is a dangerous glacial phenomenon that can cause deformation and destruction of engineering structures. The main factors influencing the aicing, including groundwater sources, soil type, climatic conditions, and the spatial location of pipelines relative to watercourses and other objects have been analyzed. To estimate the aicing risk, a geoinformation analysis and Earth remote sensing (ERS) methods have been used using data from the Sentinel-1 and Landsat 8 satellites. Key predictors of aicing risk have been identified and integrated into mapping models using the Analytical Hierarchy Process (AHP). The obtained results have made it possible to rank the hazard levels of pipeline sections and propose priority zones for preventive engineering measures. The application of the proposed method can improve the accuracy of aicing risk assessment and facilitate the development of effective solutions to minimize the impact on pipeline infrastructure elements in permafrost conditions.</p>

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Integration of Remote Sensing and GIS for Analysis and Estimate of Icing Risk on of Northern Main Pipeline Sections

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • N. S. Shein,
  • S. A. Tikhonova,
  • G. P. Struchkova,
  • T. A. Kapitonova,
  • L. E. Tarskaya

摘要

Abstract

In this paper, the risk of ice formation on main pipelines laid in permafrost soils using the Power of Siberia gas pipeline as an example has been estimated. Icing is a dangerous glacial phenomenon that can cause deformation and destruction of engineering structures. The main factors influencing the aicing, including groundwater sources, soil type, climatic conditions, and the spatial location of pipelines relative to watercourses and other objects have been analyzed. To estimate the aicing risk, a geoinformation analysis and Earth remote sensing (ERS) methods have been used using data from the Sentinel-1 and Landsat 8 satellites. Key predictors of aicing risk have been identified and integrated into mapping models using the Analytical Hierarchy Process (AHP). The obtained results have made it possible to rank the hazard levels of pipeline sections and propose priority zones for preventive engineering measures. The application of the proposed method can improve the accuracy of aicing risk assessment and facilitate the development of effective solutions to minimize the impact on pipeline infrastructure elements in permafrost conditions.