Introductory Chapter: Landslides

*Ka Po Wong, Yuanzhi Zhang and Qiuming Cheng*

#### **1. Introduction**

#### **1.1 Concept of landslides**

Landslides, one of the catastrophic events on earth, can cause extensive impacts, for instance, loss of human life, destruction of infrastructures and residential developments, and damage to cultural and natural heritage [1]. Landslides occur when massive rocks, sand, debris, or a combination of these move downslope, also known as slumps and slope failure. **Table 1** demonstrates the types of landslides movement, namely, falling, toppling, rotational sliding, translational sliding, lateral spreading and flowing [2]. Most landslides occur in mountainous regions; however, the incremental human activities in the natural environment lead to landslides in low-relief areas, such as roadways, river bluff failures, and building excavations. Each occurrence of the landslide has multiple causes (see **Table 1**).

#### **2. Causes of landslides**

The leading causes and triggering mechanisms of landslides are physical, natural and human causes [3]. The physical causes include intense rainfall, prolonged intense precipitation, flooding, the rapid drawdown of floods and tides, rapid snowmelt, earthquake, volcanic eruption, thawing, freeze-and-thaw weathering and shrink-and-swell weathering. Natural causes consist of geological and morphological causes. Geological causes include sensitive materials, weathered materials, sheared materials, fissured materials, adversely oriented mass discontinuity and structural discontinuity, and contrast in permeability and contrast in stiffness. Morphological causes consist of tectonic or volcanic uplift, glacial rebound, glacial melt-water outburst, fluvial erosion of slope toe, wave erosion


#### **Table 1.** *Types of landslide movement.*

of slope toe, glacial erosion of slope toe, erosion of lateral margins, subterranean erosion, deposition loading slope or its crest and vegetative removal by forest fire and drought [3]. The human causes include rock, soil and slop excavation, unstable earth fills, loading of slope or its crest, drawdown and filling of reservoirs, deforestation, irrigation, mining waste containment, artificial vibration and water leakage from utilities. Human interventions in the natural environment trigger landslide, leading to the increase in the frequency of landslides and the severity of the damages and casualties [4]. Despite the various types of causes of landslides, the three main causes of the most damaging landslides in the world are slope saturation by water (i.e. severe rainfall), seismic activities with extremely high magnitude in steep landslide-prone areas and volcanic activities [5, 6]. The 1964 Alaska Earthquake triggered widespread landslides, causing massive monetary loss and loss of life [5]. An eruption in Mount St. Helens in 1980 triggered a severe landslide [6]. The sudden lateral shock wave hundreds of miles away made the top of the volcano 1,300 feet away. The shock wave and pyroclastic flow passed through the surrounding landscape, flattening forests, melting snow and ice, and creating massive mudslides [6].

#### **3. Landslides in different types**

Landslides that occur in urban areas can destroy infrastructures, for example, roads, residential buildings and public power supplies. Rainfall-induced landslides are ubiquitous in many metropolitan cities [7]. Most landslides caused by rainfall are shallow (i.e. less than a few meters deep), small in size, and moving quickly. Many rainfall-induced landslides turn into mudslides as they move along steep slopes, especially those entering the river, where they may mix with additional water and sediment. Apart from the landslide in the urban area, during the life of the reservoirs, some ancient landslides can be reactivated, and potential new landslide can be triggered in the reservoir areas [8]. The failure of the landslides is affected by the increase in pore water pressure and the decrease in the average effective stress. It is considered as a complex slope instability phenomenon because landslides show obvious kinematics in the failure, post-failure and propagation stages [9]. Landslide can also be caused by volcanic activities in which volcanic gas explosions can be triggered [10]. These landslides can form dams, block rivers and bury roads, bridges and houses. Tsunami, which is the results of submarine earthquakes and collapse of coastal volcanoes, can also be triggered by underwater and coastal landslides, like the 1980 Mount St. Helens eruption. When a fast-moving landslide body enters the water or the water is displaced before, and after the fastmoving underwater landslide, a tsunami may be generated upon impact [11].

#### **4. Remote sensing and GIS applications**

Numerous researchers have adopted landslide detection techniques to identify the landside boundaries on the land surface. The conventional techniques for landslide detection are geomorphologic field survey and visual analysis of aerially surveyed images (i.e., orthophotographs) [12]. The purposes of geomorphologic field survey and mapping are to detect and map landslides caused by earthquakes and other specific events, observe the types and characteristics of landslides to improve the visual quality of satellite images or orthographic images and investigate and verify the existing slope evolution inventory map developed using different methods [12]. Due to the reduction in the visualization of slope failure and the limited ability of accurate

#### *Introductory Chapter: Landslides DOI: http://dx.doi.org/10.5772/intechopen.99301*

information of the landslide boundary, there are defects in the field mapping of the landslide [12]. Visual analysis of aerially surveyed images is the oldest remote sensing methodology for detecting landslides. This method is unreliable; however, visual analysis of aerial images have widely been used due to the fact that experienced geomorphologists can effortlessly map and identify landslides on aerial images, trained geomorphologists do not need complex technical skills to obtain aerial photographs, the scale and the size of the aerial survey images allow for an extensive spatial range of terrain with a feasible number of images, and due to the large number of aerial survey photographs from the 1950s, investigators were able to analyze slope failures in the same area. The recent techniques developed for landslide detection are analysis of surface morphology using a high-resolution digital elevation model (HR-DEM) and investigation and analysis of satellite imagery (e.g. panchromatic band images, multiple band images, and radar). Surface morphology using HR-DEM is a sophisticated form of high spatial resolution image which is invisible to the naked eye [13]. HR-DEM is derived from airborne LiDAR data in the south and satellite images in the north. Satellite images of the landslide occurrence were demonstrated by modifying the model and the cover type and electromagnetic radiation from VIS to SWIR of the earth surface [14]. Furthermore, deep learning is the recent trend for landslide investigation using remotely sensed images and can be used for surface classification, transformation detection and object detection [15]. To improve the target of remote sensing-based application, using deep learning methods to achieve the latest results based on computer vision. Geographic Information System (GIS) was used to view different types of information simultaneously since maps and other forms of information are sometimes superimposed on each other using GIS [16]. Different types of information are used for constructing layers in GIS analysis, including the topographic map, terrain map, bedrock map, engineering soil map, forest cover map, aerial photography remote sensing and InSAR imaging [16]. The topographic map is used to indicate the gradient of slopes, configuration of terrain and drainage pattern.

The terrain map is to identify depth, material, terrain configuration, geological processes, the surface of drainage and slope gradient. The bedrock map can identify the types of bedrock, surface and subsurface of the structures and rock age over a topographic map base. The engineering soil map is used to identify the types of surficial material type, drainage and the covers of soils and vegetation. The forest cover map can identify the surface of vegetation, topographic features, surface drainage pattern, and soil drainage character. The identifiable features on aerial photographs can help users identify the type of landslide and reasonably evaluate the overburden features. These, in turn, provide a method for estimating the hazard of landslides on site. Most InSAR devices can penetrate fog and rain and can be used in difficult areas to reach on foot. Two satellite images can be merged to demonstrate the ground displacement for indicating any movement that occurs. Thus, the users can use this means to determine if the hillside moves.

#### **5. Landslide risk assessment and management**

To mitigate the damage brought by landslides, governments and related departments corporate to develop landslide risk assessment and management to address the uncertainty of the landslide hazards [17]. Recent landslide risk analysis and assessment provided a systematic and rigorous slope engineering practice and management. The framework of a landslide risk assessment and management consists of the estimation of the risk, the decision of acceptance level and the measures to control the unacceptance level of landslides. The issues required to be addressed are the probability of the occurrence of the landslide, runoff behavior of debris,

risk threatening human and property and vulnerability assessment of human and property. Morgan et al. [18] generated the formulas for computing the annual probability of loss for an individual life (Eq. (1)) and property value (Eq. (2)).

$$R(\text{DI}) = P(\text{H}) \times P(\text{S}|\text{H}) \times P(\text{T|S}) \times V(\text{L|T}) \tag{1}$$

where *R*(DI) is the annual probability of loss of an individual life; *P*(H) is the annual probability of the landslide event; *P*(S|H) is the probability of spatial impact given the event; *P*(T|S) is the probability of temporal impact given the spatial impact; and *V*(L|T) is the vulnerability of the individual (probability of loss of life given impact).

$$\mathbf{R(PD)} = \mathbf{P(H)} \times \mathbf{P(S|H)} \times \mathbf{V(P|S)} \times \mathbf{E} \tag{2}$$

where *R*(PD) is the annual loss of property value; *P*(H) is the annual probability of the landslide event; *P*(S|H) is the probability of the landslide impacting the property; *V*(P|S) is the proportion of property value lost; E is the element at risk (e.g. the value of the property).

#### **6. Landslide measures**

Several measures have been implemented. Artificial slope upgrading is a significant engineering work to improve and enhance the slope [19]. This practice is based on four main principles, namely removal, reinforcement, retention and replacement. There are four standard practices: fill slopes, soil cut slopes, retaining walls, and rock-cut slopes. For fill slopes, substandard fill slopes usually contain loose filling materials that tend to liquefy when they become saturated and subjected to shear. It needs to install soil nails through filling materials and provide a surface grid to connect the soil nail heads [19]. Existing trees can be preserved during the construction process. The soil nails are embedded in the influential underground stratum to ensure sufficient anchorage to prevent pulling out. Regarding soil cut slopes, trimming the slopes to a gentler profile is the usual method. The main construction activity is the excavation and removal of soil material from the slope [20]. Further, retaining walls for restraining the soil are usually used in steep slopes or the landscapes required to be shaped for engineering or construction works [21]. Gravity walls, pilling walls, cantilever walls and anchored walls are the common types of retaining wall as a landslide solution. The type of wall to be adopted is based on the circumstances, and the critical factors are soil type, slope angle, groundwater, and go on. For rock cut slopes, this construction practice is to upgrade the existing rock cut slopes [22]. The stabilization practices are scaling rocks, buttresses, dentition, rock dowels, rock bolts, rakings drains and mesh netting [22]. Importantly, all these practices are to keep the slope safe and make them look natural so that people can live in a safer and better environment.

#### **7. Summary and future perspective**

The research related to the types and causes of landslides have been investigated over time and the findings are similar. More regions are recommended to be *Introductory Chapter: Landslides DOI: http://dx.doi.org/10.5772/intechopen.99301*

assessed to ameliorate the accuracy and generalizability of the previous findings. Furthermore, machine learning and deep learning methods have popularly been applied in the landslide susceptibility mapping and landslide identification. The overall robustness of the results generated from machine learning and deep learning is outstanding. Therefore, adopting machine learning and deep learning in detecting landslides is utterly significant for preventing landslides since human and property losses can be mitigated.

#### **Acknowledgements**

This research was partially supported by the National Natural Science Foundation (U1901215), the Marine Special Program of Jiangsu Province in China (JSZRHYKJ202007), the Natural Scientific Foundation of Jiangsu Province (BK20181413), and the State Key Lab Fund for Geological Processes and Mineral Resources (2016).

#### **Conflicts of interest**

The authors declare no conflict of interest.

## **Author details**

Ka Po Wong1 , Yuanzhi Zhang2 \* and Qiuming Cheng3

1 Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong, China

2 Faculty of Social Science, Center for Housing Innovations and Institute of Asia-Pacific Studies, Chinese University of Hong Kong, Hong Kong, China

3 China University of Geoscience, State Key Laboratory for Geological Processes and Mineral Resources, Beijing, China

\*Address all correspondence to: yuanzhizhang@hotmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 2
