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

Li Weiguo,Chen Yanhong,Yang Libing,Liu Yali,Xiangjian Dong

doi:10.1155/2021/4119414

Abstract

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.

Highlights

A landslide is a common geological hazard that seriously threatens life and property globally [1,2,3]
This paper provides insights into the types of landslides and the relationship between rainfall and other monitoring data through the analysis of the Zhutoushan landslide monitoring data in China and explores how to evaluate the outlier data using Exploratory data analysis (EDA)
According to the design requirements and field survey, this system comprises one Global Navigation Satellite System (GNSS) reference station located outside of the landslide, eight GNSS monitoring stations (Figure 1), six inclinometer monitoring points in which

Summary

Introduction

A landslide is a common geological hazard that seriously threatens life and property globally [1,2,3]. Exploratory data analysis (EDA) is a technique or method for analyzing and processing data sets for summarizing their main characteristics, usually by visualization, and it plays a paramount role in obtaining valuable information from data [11]. This method has been effectively applied to a variety of aspects [12], such as computer graphics [13], bioinformatics [14, 15], meteorology [16], traffic [17], and crops [18]. It is essential for irregular data to know whether it is caused by disturbance, gear disappointment, or avalanche distortion to avoid triggering a false alarm This requires data analysis and research to reduce the uncertainty impact of big data [26, 27].

Material and Methodology

Results and Discussion

Conclusions