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.</p>
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10500 - Earth and related environmental sciences
Result continuities
Project
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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
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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
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UT code for WoS article
000713518700002
EID of the result in the Scopus database
2-s2.0-85118214806