Landslide is a common geological disaster with wide distribution and great harmfulness, which poses a serious threat to the safety of human life and property. Rainfall is the biggest influencing factor of loess landslide. Since rainfall is closely related to the PWV content, the Global Navigation Satellite System (GNSS) can not only obtain the three-dimensional deformation information of the location of the observation station, It can also be used to invert the moisture content. In order to make GNSS play a better role in landslide monitoring, based on the landslide event in Linxia city, In this paper, GAMIT software is used to calculate the data of three IGS stations combined with the monitoring station in Linxia city, and the PWV is inverted and compared with the rainfall, The PWV value accumulates continuously from low to high, and when it reaches a certain peak value and lasts for a period of time, rainfall events will occur. The results show that PWV has an obvious correspondence with actual rainfall, which proves the feasibility of ground-based GNSS inversion of moisture content. The three-dimensional surface deformation information obtained by the universal receiver is analyzed synthetically. The experimental results show that there is a correlation between the shape variables, PWV and rainfall, which proves the feasibility of GNSS meteorology for loess landslide monitoring. By analyzing the historical meteorological data of Linxia city, the rainy season is concentrated in May to September, during which the real-time calculation scheme can be adopted. When there is less rainfall from October to April of the next year, sky solution or weekly solution can be adopted. In addition, when the PWV is greater than 20 mm, real-time calculation can be performed to monitor landslide conditions. The cumulative PROCESS of PWV before rainfall is of great significance for monitoring loess landslide. Therefore, GNSS inversion of PWV provides a new monitoring strategy for loess landslide.


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    Titel :

    Research on Monitoring Strategy of Loess Landslide with GNSS Meteorology


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yang, Changfeng (Herausgeber:in) / Xie, Jun (Herausgeber:in) / Jiang, Jianwen (Autor:in) / Zhang, Shuangcheng (Autor:in) / Jia, Cunpeng (Autor:in) / Wang, Xuqiao (Autor:in) / Li, Xinrui (Autor:in)

    Kongress:

    China Satellite Navigation Conference ; 2022 ; Beijing, China May 22, 2022 - May 25, 2022



    Erscheinungsdatum :

    07.05.2022


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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