Geoplanning : Journal of Geomatics and Planning
Vol 11, No 1 (2024)

Mapping Landslide Vulnerability using Machine Learning Approach along the Taba Penanjung-Kepahiang Road, Bengkulu Province

Abrar, Camelia Batun (Unknown)
Lubis, Ashar Muda (Unknown)
Fadli, Darmawan Ikhlas (Unknown)
Akbar, Arya J (Unknown)
Samdara, Rida (Unknown)



Article Info

Publish Date
08 Mar 2024

Abstract

Landslides occur when masses of rock, debris or soil move due to various factors and processes that cause land movement. The Taba Penanjung-Kepahiang route is one of the areas in Bengkulu Province that is highly prone to landslides. This causeway is the only fastest land route connecting the Bengkulu-Kepahiang area. In recent years, the road area has often been cut off due to landslides and fallen trees, which have caused road access to be cut off and obstructed and claimed lives. This study uses a Machine Learning (ML) and GIS approach with Variable Frequency Ratio using 16 independent factors obtained from the spatial database and DEM, which correlate with landslide events. This research aims to gain an in-depth understanding of the factors that cause landslides. In addition, the research focus is the development of a Disaster Mitigation Model to design and implement effective strategies to reduce the risk and impact of landslide disasters through in-depth analysis The dependent factor is the location of the landslide from the historical landslide area for the last five years, with a distribution of 70/30%. Furthermore, frequency ratio is used to analyze the correlation between conditioning factors and historical landslides. Then, the independent and dependent factors were normalized to create a landslide susceptibility map. Frequency Ratio (FR) indicates the likelihood of an event occurring, with drainage density (FR= 0.69), shear wave velocity (Vs30) (FR= 0.66), slope (FR= 0.60), and rainfall (FR= 0.55).  The output of the processed data is in the table below.

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Journal Info

Abbrev

geoplanning

Publisher

Subject

Earth & Planetary Sciences

Description

Geoplanning, Journal of Geomatics and Planning (E-ISSN: 2355-6544), is an open access journal (e-journal) focusing on the scientific works in the field of applied geomatics technologies for urban and regional planning including GIS, Remote Sensing and Satellite Image Processing. This journal is ...