Landslide Prediction using Machine Learning

Abstract

In Korea, during the rainy season, landslides are a frequent geological hazard that can cause fatalities, property damage, and economic losses. Landslides are responsible for at least 17% of all fatalities from natural disasters worldwide and nearly 25% of all fatalities from natural disasters in Korea each year. Global climate change has increased the frequency of landslides, which has led to an increase in landslide-related losses and damages. Therefore, it is essential to perform exact landslide prediction, monitoring, and early warning of ground movements in order to reduce the losses and damages caused by landslides. There has been significant recent progress in the fields of landslide prediction and landslide damage reduction as a result of the numerous studies that have been undertaken in these fields.