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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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;

Název v anglickém jazyce

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

Popis výsledku anglicky

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;

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10500 - Earth and related environmental sciences

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Geofluids

ISSN

1468-8115

e-ISSN

—

Svazek periodika

2021

Číslo periodika v rámci svazku

11. 10. 2021

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

—

Kód UT WoS článku

000713518700002

EID výsledku v databázi Scopus

2-s2.0-85118214806