Sustainability in Engineering Sciences

**621**

Nepal

**1. Introduction**

area of 87 km2

**Chapter 50**

**Abstract**

Landslides

*and Sinan Jasim Hadi*

landslide susceptibility model.

Perceptual Structure and Pattern

Modeling of Aftershock-Induced

In this study, two unsupervised clustering techniques were used to generate meaningful training and testing landslide sample locations to produce landslide susceptibility map in north of Kathmandu Valley, Nepal. First, the landslide inventory data was prepared after enormous aftershock of magnitude 7.3 Mw on May 12, 2015. Secondly, unsupervised clustering algorithms (k-means, expectationmaximization (EM) using Gaussian mixture models (GMM)) were used in R programming environment to generate two samples of datasets. Additionally, a dataset was generated using random sampling and that for sampling comparison purpose. Later, eight terrain-based topographic conditioning factors were selected from freely available digital elevation model derivatives (slope, aspect, elevation, roughness, topographic wetness index (TWI), stream power index (SPI), area solar radiation (ASR), and curvature). Eventually, a total of three datasets was used to run logistic regression model to produce the landslide susceptibility map (LSM). Using uncertainty optimization, statistical tests (ANOVA, Wald test, tenfold cross validation, and ROC of AUC value) were performed. The unsupervised samples show more significant behavior over the unstable characteristic of the randomly selected samples. Gaussian mixture model (GMM) algorithm scored the highest in model performance and prediction capability. The findings present an alternative sampling strategy that significantly increases the efficiency and stability of the

**Keywords:** landslide prediction, unsupervised clustering, logistic regression, cluster,

Earthquake-induced landslide is a significant natural hazard especially in mountain areas and contributes in mountain-scale erosional budgets as well as life losses [1, 2]. An earthquake occurred on April 25, 2015 that struck at Barkpak, Gorkha, at a magnitude of 7.8 Mw and triggered landslides, rockfalls, and avalanches [3] which blocked roads and dammed rivers [4]. The biggest aftershock of magnitude 7.3 Mw on May 12, 2015, triggered many landslides as well. The major shock and the aftershock sequences produced almost 25,000 landslides with an approximate

, most landslides concentrating in the central Nepal through the

*Omar F. Althuwaynee, Badal Pokharel, Ali Aydda* 

#### **Chapter 50**
