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Shock and Vibration of Rainfall on Rotational Landslide and Analysis of Its Deformation Characteristics

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27350%2F21%3A10248450" target="_blank" >RIV/61989100:27350/21:10248450 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.hindawi.com/journals/geofluids/2021/4119414/" target="_blank" >https://www.hindawi.com/journals/geofluids/2021/4119414/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1155/2021/4119414" target="_blank" >10.1155/2021/4119414</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Shock and Vibration of Rainfall on Rotational Landslide and Analysis of Its Deformation Characteristics

  • Original language description

    Earthquake, flood, human activity, and rainfall are some of the trigger factors leading to landslides. Landslide monitoring data analysis indicates the deformation characteristics of landslides and helps to reduce the threat of landslide disasters. There are monitoring methods that enable efficient acquisition of real-time data to facilitate comprehensive research on landslides. However, it is challenging to analyze large amounts of monitoring data with problems like missing data and outlier data during data collection and transfer. These problems also hinder practical analysis and determination concerning the uncertain monitoring data. This work analyzes and processes the deformation characteristics of a rainfall-induced rotational landslide based on exploratory data analysis techniques. First, we found that the moving average denoising method is better than the polynomial fitting method for the repair and fitting of monitoring data. Besides, the exploratory data analysis of the Global Navigation Satellite System (GNSS) monitoring data reveals that the distribution of GNSS monitoring points has a positive correlation with the deformational characteristics of a rotational landslide. Our findings in the subsequent case study indicate that rainfalls are the primary trigger of the Zhutoushan landslide, Jiangsu Province, China. Therefore, this method provides support for the analysis of rotational landslides and more useful landslide monitoring information.&lt;/p&gt;

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10500 - Earth and related environmental sciences

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Geofluids

  • ISSN

    1468-8115

  • e-ISSN

  • Volume of the periodical

    2021

  • Issue of the periodical within the volume

    11. 10. 2021

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    12

  • Pages from-to

  • UT code for WoS article

    000713518700002

  • EID of the result in the Scopus database

    2-s2.0-85118214806