A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility

Viet-Hung Dang,Nhat-Duc Hoang,Dieu Tien Bui,Le-Mai-Duyen Nguyen,Pijush Samui

doi:10.3390/f11010118

Viet-Hung Dang, Nhat-Duc Hoang + Show 3 more

Open Access

https://doi.org/10.3390/f11010118

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Abstract

This study developed and verified a new hybrid machine learning model, named random forest machine (RFM), for the spatial prediction of shallow landslides. RFM is a hybridization of two state-of-the-art machine learning algorithms, random forest classifier (RFC) and support vector machine (SVM), in which RFC is used to generate subsets from training data and SVM is used to build decision functions for these subsets. To construct and verify the hybrid RFM model, a shallow landslide database of the Lang Son area (northern Vietnam) was prepared. The database consisted of 101 shallow landslide polygons and 14 conditioning factors. The relevance of these factors for shallow landslide susceptibility modeling was assessed using the ReliefF method. Experimental results pointed out that the proposed RFM can help to achieve the desired prediction with an F1 score of roughly 0.96. The performance of the RFM was better than those of benchmark approaches, including the SVM, RFC, and logistic regression. Thus, the newly developed RFM is a promising tool to help local authorities in shallow landslide hazard mitigations.

Highlights

A landslide, which is defined as the slope movement of soil, mud, debris, or rock, is the most common geological hazard in the world [1]
To train and test the model predictive capability, the original dataset was randomly divided into training (70%) and testing (30%) sets
For land use planning and hazard mitigation, landslide susceptibility evaluation is a crucial task performed by the local authority in mountainous and remote areas in northern Vietnam

Summary

Introduction

A landslide, which is defined as the slope movement of soil, mud, debris, or rock, is the most common geological hazard in the world [1]. This hazard happens as a consequence of other events or actions, such as torrential rain, earthquake, deforestation, or mineral exploitation. Landslides have substantial social and economic impacts. During the 1995–2014 period, more than 3876 landslides occurred causing 163,658 deaths and 11,689 injuries [2]. According to the Institute of Geosciences and Mineral Resources in Vietnam, there are more than 10,200 locations that have a high risk of landslides in the northern mountainous provinces [3].

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