Mobile Application for Rainfall-Landslide Early Warning System (RLEWS) using Global Precipitation Measurement (GPM)

Abstract

Malaysia has tropical climates near the equatorial zone that deliver widespread rainfall each year. Due to this, Malaysia is susceptible to landslide incidents as one of the main factors that can induce a landslide is rainfall. Landslides have a significant impact on many environmental and socioeconomic issues, including the loss of life, damage to property and infrastructure, and psychological stress among victims. According to a study, geological circumstances are primarily responsible for slope collapse in a number of these countries. A landslide-specific early warning system must be established despite the increased sensitivity to landslides to lower the danger of landslide hazards. The objectives of this project are to develop a mobile app for a landslide early warning system to be used as a monitoring tool of landslides using estimates from the Global Precipitation Measurement (GPM) precipitation data to alert if any warning signs from potential landslides occurrences were seen in Ulu Klang. The methodology of this project is using MySQL as a database server, and PHP as a programming language with the input/data from GPM rainfall data. The result is all users are notified of the condition of the landscape and the landslide occurrence in Ulu Klang.