AUTOMATION OF DAILY LANDSLIDE POTENTIAL INFORMATION BASED ON REMOTE SENSING SATELLITE IMAGERY USING OPEN-SOURCE SOFTWARE TECHNOLOGY

Sutanto, Ahmad and Annas, Anwar and Ardha, Mohammad and Hidayat, Taufif and Khomarudin, Muhammad Rokhis (2023) AUTOMATION OF DAILY LANDSLIDE POTENTIAL INFORMATION BASED ON REMOTE SENSING SATELLITE IMAGERY USING OPEN-SOURCE SOFTWARE TECHNOLOGY. International Journal of Remote Sensing and Earth Sciences (IJReSES), 20 (1). p. 37. ISSN 0216-6739

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Abstract

This automation system automatically generated landslide potential information based on daily precipitation data. This system is essential to replace the previous manual processing system with an automated and integrated system. The results of the developed system are the distribution of areas with landslide potential based on daily precipitation data. The system was built using QGIS Processing Modeler Algorithms and Python script programming. This allows the automation process to be performed quickly and accurately. The landslide susceptibility map used is from the National Disaster Management Agency, so the information is more reliable. Himawari-8 is used to determine the potential for extreme precipitation in 10 minutes because this satellite has a very high temporal resolution. The system is already in use and has proven to replace manual processing and is faster than landslide information manual processing which executed each algorithm separetely. Further development will be more challenging if the system can be connected to the sensors installed on site so that the sensors on site can issue a landslide warning in case of extreme precipitation so that the surrounding communities can respond immediately. Opportunities for future development of the system may also be incorporated into landslide potential prediction based on the precipitation forecast model.

Item Type: Article
Uncontrolled Keywords: landslide, rainfall, Himawari 8, early warning system
Subjects: Natural Resources & Earth Sciences
Depositing User: Mrs Titi Herawati
Date Deposited: 29 Dec 2025 07:09
Last Modified: 29 Dec 2025 07:09
URI: https://karya.brin.go.id/id/eprint/57220

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