Landslide Risk Mapping in East Java, Indonesia, Using Analytic Hierarchy Process – Natural Breaks Classification

Fariza, Arna; Rusydi, Ilham; Hasim, Jauari Akhmad Nur; Basofi, Arif

doi:10.1109/isriti.2018.8864367

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…From each of these parameters, the data obtained is in the form of data covering the entire area of the New Road Section (Mengwitani-Singaraja, which will then be classified based on research case studies so that a parameter map will be obtained that already has each class. The classification of landslides susceptibility uses the natural break method [22,23] so that the results show a significant difference based on each parameter. The causes of landslides are based on the smallest value to the largest value.…”

Section: Determination Of Landslide Hazard Susceptibility Classmentioning

confidence: 99%

Spatial Distribution of Landslide Susceptibility in New Road Construction Mengwitani-Singaraja, Bali-Indonesia: Based on Geospatial Data

Diara¹

2022

GEOMATE

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Landslides often occur in the Mengwitani-Singaraja new road construction area. This study aims to analyze the spatial distribution of landslide susceptibility as a basis for disaster mitigation. This study uses a quantitative and descriptive method. Data analysis through scoring technique and thematic map overlay. The parameters needed in this study include the slope, landform, geological structure, rainfall, soil type, and land cover. Spatial analysis was performed using a Geographic Information System (GIS). The study results are categorized into three landslide susceptibility maps, namely high, medium and low. Baturiti and Sukasada sub-districts are areas that have a high level of landslide susceptibility of 15.62%. The low landslide susceptibility area is the area that has the highest area, which is 30.38%, and the medium landslide susceptibility area is 26.87%. Other sites have no susceptibility for landslide susceptibility (27.1 %). High landslide susceptibility because the area is located on volcanic upper slope landforms, volcanic cones, with fractured and sloping geological structures, very steep slopes (> 45%), high rainfall (> 2,400 mm/yr.), andosol soil types, as well as land cover with low vegetation density. The occurrence of landslides in the field is spatially dominant on the road section that crosses Candikuning Village to Gitgit Village. Land management is recommended by installing coconut fiber gabions on steep slopes and terraces, plant cultivation according to conservation rules, and the addition of organic matter.

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Section: Determination Of Landslide Hazard Susceptibility Classmentioning

confidence: 99%

Spatial Distribution of Landslide Susceptibility in New Road Construction Mengwitani-Singaraja, Bali-Indonesia: Based on Geospatial Data

Diara¹

2022

GEOMATE

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“…Natural Breaks classification, also called Jenks optimization method, is a data classification method designed to determine the best arrangement of values into different classes. This is done by seeking to reduce the standard deviation value within each class and maximizing that between the classes themselves (Basofi et al 2018;Novellino et al 2021). The percentage of susceptibility classes is summarized in Table 3.…”

Section: Landslide Susceptibilitymentioning

confidence: 99%

Multi-temporal relative landslide risk analysis for sustainable development of rapidly growing cities

Napoli¹,

Miele²,

Guerriero³

et al. 2021

Preprint

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In the last decades, developing countries have experienced an increase in impact of natural disasters due to both the ongoing climate change and the sustained expansion of urban areas. Intrinsic vulnerability of settlements due to poverty and poor governance, as well as the lack of tools for urban occupation planning and mitigation protocols, have made such impact particularly severe. Cuenca (Ecuador) is a significant example of a city that in the last decades has experienced considerable population growth and an associated increasing of loss due to landslide occurrence. Despite such effects, updated urban planning tools are absent, a condition that suggested an evaluation of multi-temporal relative landslide risk, here presented based on updated data depicting the spatial distribution of landslides and their predisposing factors, as well as population change between 2010 and 2020. In addition, a multi-temporal analysis accounting for risk change between 2010 and 2020 has been carried out. Due to the absence of spatially distributed data about the population, electricity supply contract data have been used as a proxy of the population. Results indicate that current higher relative risk is estimated for municipalities (parroquias) located at the southern sector of the study area (i.e. Turi, Valle, Santa Ana, Tarqui and Paccha). Moreover, the multi-temporal analysis indicates that most municipalities of the city located in the hilly areas that bound the center (i.e. Sayausi, San Joaquin, Tarqui, Valle, Sidcay, Banos, Sidcay, Ricaurte, Paccha and Chiquintad), experiencing sustained population growth, will be exposed to an increased risk with a consistently growing trend. This information is consistent with landslide susceptibility data derived by a machine learning-based analysis that indicate higher susceptibility to landslides in hilly areas surrounding the city center. The obtained relative risk maps can be considered as a useful tool for guiding land-planning, occupation restriction and early warning strategy adoption. The used methodological approach, accounting for landslide susceptibility and population variation through proxy data analysis, has the potential to be applied in a similar context of growing-population cities of low to mid-income countries, where data, usually needed for a comprehensive landslide risk analysis, are only partly available.

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“…Vulnerability is based on physical, economic, social and environmental losses caused by disasters. While hazard is based on the potential and impacts resulting from disasters (Basofi et al, 2018). In addition, one of BNPB's policies is creating Safe School Disaster to increase student awareness so that they have a good plan during and after the disaster, and are always responsive in responding to disaster emergencies (Husna and Fauzi, 2019).…”

Section: The Assessment Of Stakeholders Action 31 Governments Actionmentioning

confidence: 99%

The assessment of landslides disaster mitigation in Java Island, Indonesia: a review

Zamroni

Kurniati

Prasetya

2020

J. Geoscience Eng. Environ. Technol.

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The frequency of landslides and the fact that a large number of people live in the landslides-prone areas lead to a high death toll in Java Island, Indonesia – over 1,112 people in the period between 1999 and 2005. Indonesian National Disaster Management Agency (Badan Nasional Penanggulangan Bencana [BNPB]) reported 2,766 landslides that occurred in Java from 2014 to 2019, with 662 deaths. From its state, it looks as if Indonesia 's disaster mitigation is still weak. It is very essential to a deep understanding of landslides disaster mitigation weakness in Indonesia with the approach of governments, researchers, and local communities action. This research is a review of landslides disaster mitigation in Java Island with the approach of governments, researchers, and local communities action. Furthermore, the purpose of this study is to highlight the driving forces of landslides disaster mitigation in Java Island, Indonesia. From the assessment of each stakeholder (government, researchers, and local communities), the driving forces of landslides disaster mitigation in Java Island are the central government has commanding disaster management activities to local governments. However, the implementation of landslides disaster mitigation at the regional level has some obstacles such as the lack of residential development planning.Many landslide research results have only become scientific papers but the landslides-prone areas have not been fully paid attention by the local government such as the absence of landslide danger warning signs.In addition, the level of preparedness and awareness among local communities is not constant at any given time. Usually, community preparedness levels can be high following a disaster. It is likely, however, to diminish over time.

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Landslide Risk Mapping in East Java, Indonesia, Using Analytic Hierarchy Process – Natural Breaks Classification

Cited by 5 publications

References 6 publications

Spatial Distribution of Landslide Susceptibility in New Road Construction Mengwitani-Singaraja, Bali-Indonesia: Based on Geospatial Data

Spatial Distribution of Landslide Susceptibility in New Road Construction Mengwitani-Singaraja, Bali-Indonesia: Based on Geospatial Data

Multi-temporal relative landslide risk analysis for sustainable development of rapidly growing cities

The assessment of landslides disaster mitigation in Java Island, Indonesia: a review

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