High-Resolution Landslide Susceptibility Map Generation using Machine Learning (Case Study in Pacitan, Indonesia)

Darminto, Mohammad Rohmaneo; Widodo, Amien; Alfatinah, Adillah; Chu, Hsin

doi:10.18517/ijaseit.11.1.11679

Cited by 10 publications

(10 citation statements)

References 39 publications

(46 reference statements)

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“…The method used in this research is Frequency Ratio (FR). The objective of this method is to identify landslide prone areas based on past landslide occurrence data which in turn can be used as a parameter for landslide disaster mitigation [10]. The parameters used in this research are Slope, NDVI, Lithology, Land Use, Rainfall (mm/month).…”

Section: Methodsmentioning

confidence: 99%

Mapping of Landslide Potential Zone with FRM Method and Mitigation in Ayah, Kebumen Regency

Rahman,

Ramadan,

Hudzaifah

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Landslides phenomena occur yearly in Ayah sub-district and various factors persist in the future cause these landslides. The Frequency Ratio Method is one approach to mapping landslide potential. It involves direct data collection of potential landslide points in the field. This method uses parameters such as Lithology, slope, NDVI, Monthly Precipitation, and Land Use to calculate landslide potential. These parameters are overlaid with the frequency of potential landslide points in Ayah sub- district. The resulting frequency ratio value is classified into five potential landslide zones. The findings reveal that high values covering 10.97% and very high values covering 41.75% are distributed across almost all the settlements in Ayah Sub-district, except for the northern area. The high frequency value shows the dominance of steep slope, presence of weathered breccia and limestone lithology as well as agricultural land with fibrous roots and it is also related to the complex changes in land use, such as mining and clearing activities. This highlights the importance of taking preventive and escalation measures among the relevant stakeholders to minimize the impact of this landslide.

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Section: Methodsmentioning

confidence: 99%

Mapping of Landslide Potential Zone with FRM Method and Mitigation in Ayah, Kebumen Regency

Rahman,

Ramadan,

Hudzaifah

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…The method used is frequency ratio (FR). The frequency ratio method is based on the assumption that the future land movement events will occur under the similar condition to the past landslide movement (Darminto et al, 2021;Silaban, 2021). The parameters used in this study are slope, lithology, land use, vegetation index, rainfall, and fault fracture density.…”

Section: Methodsmentioning

confidence: 99%

Mapping of Landslide Potential Zone with Frequency Ratio Method and Mitigation Efforts in Banjarnegara Regency, Central Java, Indonesia

Muhammad

Priyono

Rahmania

et al. 2022

jss

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Indonesia is a country with a very high potential for disaster. This is supported by the existence of Indonesia which is surrounded by three world plates, namely the Eurasian plate, the Indian-Australian plate and the Pacific plate. One of natural disaster which occur in Indonesia is landslide. This situation has similarities with the research area located in the Banjarnegara Regency, Central Java. Aim of this research is to provide information on the level of influence of the class and conditioning factors of landslides, and a picture of areas that have vulnerability to landslides and as an effort to provide information to related parties. This research was conducted by geological mapping and remote sensing using DEM (Digital Elevation Model) and landsat-8 as field support data and visualization of the condition of the research area. The results of this study found that the results of mapping with frequency ratio method, the percentage of low insecurity is 66.83%, moderate insecurity is 17.94%, high insecurity is 1.87%, and very high insecurity is 0.02%. Areas with very high land movement potential are in karangkobar and pandanarum districts with a total area of 0.094589 km². The area has a very high potential because it has litology with volcanic rock types, very low vegetation and the presence of straightness. Therefore, various mitigations are needed both structural and non-structural.

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“…In this research we have been successfully implementing the ML approach to access and to map landslide vulnerability along Taba Penanjung Kepahiang road. Previously The ML has been widely used in landslide mapping in several regions in Indonesia, such as Aldiansyah & Wardani (2024), Darminto et al (2021) and Irawan et al, (2021). Previous researches used ML with different algorithms, with almost the same input parameters.…”

Section: Correlation Analysis Between Landslide and Independent Factormentioning

confidence: 99%

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

Abrar,

Samdara,

Fadli

et al. 2024

Geoplanning J. Geomatics Plann.

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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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High-Resolution Landslide Susceptibility Map Generation using Machine Learning (Case Study in Pacitan, Indonesia)

Cited by 10 publications

References 39 publications

Mapping of Landslide Potential Zone with FRM Method and Mitigation in Ayah, Kebumen Regency

Mapping of Landslide Potential Zone with FRM Method and Mitigation in Ayah, Kebumen Regency

Mapping of Landslide Potential Zone with Frequency Ratio Method and Mitigation Efforts in Banjarnegara Regency, Central Java, Indonesia

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

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