Development of a Rainfall-Landslide Early Warning System (RLEWS) Using GPM Satellite Data for Malaysia’s Monsoon-Prone Areas

International Journal of Electronics and Communication Engineering

© 2026 by SSRG - IJECE Journal

Volume 13 Issue 1

Year of Publication : 2026

Authors : Norsuzila Ya’acob, Azita Laily Yusof, Ahmad Zaki Aiman Abdul Rashid, Nani Fadzlina Naim, Mohd Azri Abdul Aziz

10.14445/23488549/IJECE-V13I1P101

How to Cite?

Norsuzila Ya’acob, Azita Laily Yusof, Ahmad Zaki Aiman Abdul Rashid, Nani Fadzlina Naim, Mohd Azri Abdul Aziz, "Development of a Rainfall-Landslide Early Warning System (RLEWS) Using GPM Satellite Data for Malaysia’s Monsoon-Prone Areas," SSRG International Journal of Electronics and Communication Engineering, vol. 13,  no. 1, pp. 1-17, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I1P101

Abstract:

This study presents the development and evaluation of a Rainfall–Landslide Early Warning System (RLEWS) mobile application that uniquely integrates near–real-time rainfall data from NASA’s Global Precipitation Measurement (GPM) satellite for landslide risk prediction in Malaysia. Unlike conventional landslide warning approaches that rely primarily on ground-based rain gauge data, the proposed system utilizes satellite-derived rainfall information combined with multi-timescale rainfall thresholds to capture spatial and temporal rainfall variability during monsoon seasons. Rainfall data collected for Kemensah Heights and Taman Melawati (Kuala Lumpur, Malaysia) between November 2023 and March 2024 are analyzed to establish 1-day, 3-day, and 30-day cumulative rainfall thresholds associated with landslide occurrence. The developed RLEWS mobile application provides real-time visualization of rainfall conditions and automated warning levels, delivering timely alerts to users in landslide-prone areas. Results indicate that higher cumulative rainfall significantly increases landslide risk, with multi-duration rainfall indicators improving predictive performance. This study demonstrates the novel integration of satellite-based rainfall monitoring and mobile application technology as an effective approach for enhancing landslide early warning and disaster preparedness in monsoon-influenced urban environments.

Keywords:

Global Precipitation Measurement, Landslide, Mobile Application, Monsoon, Rainfall.

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