Spatial multi criteria approach for tsunami risk assessment

Sambah, Abu Bakar; Miura, Fusanori; Guntur, -; Fuad,

doi:10.1088/1755-1315/162/1/012019

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…Because Indonesia does not have all of them, so in this research, we propose three new input data to substitute them; coastal topography in west coast Banten, Sunda Strait bathymetry, and rainfall intensity from six stations in Banten. There are several methods used to estimate tsunami inundation zone; extreme learning machine (ELM) [9], weighted overlay [10] [11], and analytical hierarchy process (AHP) [12]. The method is used in this study is the weighted overlay.…”

Section: Methodsmentioning

confidence: 99%

Determination of Inundation Zone Using Artificial Intelligence as a Basis for Infrastructure Development in Special Economic Areas of Tanjung Lesung Banten

Oktavianti¹,

Septyandy²,

Indra³

2020

Proceedings of Tourism Development Centre International Conference

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According to history, Sunda Strait has experienced several tsunamis recorded in the tsunami catalog caused by several geological phenomena such as Krakatau eruption (416, 1883, and 1928), earthquake (1722, 1852, and 1958), and other suspected causes of land failure in the form of landslides both on the coast and on a submarine (1851, 1883, and 1889). One of the most recent tsunami incidents in the Sunda Strait was the tsunami on December 22, 2018, which triggered a flank collapse as the volcano part built on the caldera's steep wall resulting from 1883 eruption. According to The Indonesia National Disaster Management Agency (BNPB), the number of victims of the Sunda Strait tsunami died at 437 people, and losses for tourism ranged from Rp150 billion. One example of a successful tourism area that could rise after the tsunami is Pucket Beach, Thailand. This beach, affected by the 2004 Indian Ocean Tsunami, can increase the number of tourist arrivals even exceeded the number of visits before the tsunami caused by mapping vulnerability areas and comprehensive risk analysis. This study's aim implies these methods because the majority of tourism areas in Indonesia have not applied the master plan that includes the tsunami risk area, one of which is in the special economic zone (KEK) of Tanjung Lesung. To anticipate future tsunamis, an inundation zone model of tsunami waves will arrive at the coast. Inundation zones or tsunami wave runoff zones are generated from non-linear relationships between the Sunda Strait bathymetry, tide gauge signals, west coast of Banten topography, and rainfall on Sunda Strait tsunami 2018 using artificial intelligence by weighted overlay method. The inundation resulting from this research can be used as a reference for the local government for infrastructure development that supports Tanjung Lesung tourism.

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Section: Methodsmentioning

confidence: 99%

Determination of Inundation Zone Using Artificial Intelligence as a Basis for Infrastructure Development in Special Economic Areas of Tanjung Lesung Banten

Oktavianti¹,

Septyandy²,

Indra³

2020

Proceedings of Tourism Development Centre International Conference

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“…The results of the guided classification were vector data, which then were converted into raster data using the Polygon to Raster function in the Conversion Tools toolbox. After that, a reclassification process was carried out using the Reclassify function in the Spatial Analyst toolbox by setting the land use class and vulnerability class referring to Sambah et al (2018), which can be seen in Table 3.…”

Section: Land Usementioning

confidence: 99%

“…Then, each parameter was weighted in aunit of percent (%), with the total weight of all the parameters being 100%. The weighting of the physical tsunami vulnerability parameters refered to Sambah et al (2018), which can be seen in the Table 4. sessment of disaster management efforts.…”

Section: Overlaysmentioning

confidence: 99%

A Modelling and Mitigation Strategy for the Impact of the Tsunami Disaster at Tamban Beach, Malang Regency, using a Geographic Information System

Rudianto¹,

Widodo²,

Guntur³

et al. 2022

EEC

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Tsunami events are caused by a series of waves resulted from sudden changes in the water column, seismicactivities such as the eruption of underwater volcanoes,landslides on cliffs above or below the sea, andfalling asteroids. The Meteorology, Climatology, and eophysics Agency released a warning of a potentialearthquake in the southern part of Java Island, including the Malang Regency, with a magnitude of 8.7 onthe Richterâs scale. It means that a tsunami with amaximum inundation height of up to 22 meters coulddestroy Tamban Beach. The objectives of this study were1)to examine the spatial aspect of Tamban Beachand its relevance to the ecological aspect as well as thetime aspect related to the estimation,2) to formulatea strategy to save the community, and 3) to estimate the impact of the damage to cover and land use. Themethods used were a scoring technique and an overlay analysis using a Geographic Information System(GIS), with parameters including the distance to the coast and river from the sea, slope, elevation, land use,tsunami run-up prediction, and inundation model. The Partial Least Squares (PLS) method was used todetermine the relationship between the level of vulnerability of an area to the tsunami disaster with variousassessments and efforts to mitigate the disaster. The results showed that most of the coastal areas of TambanBeach had a moderate level of vulnerability, except for the residential areas that had a high level ofvulnerability. A tsunami mitigation strategy was significantly influenced by the areaâs level of vulnerabilityto a disaster and the assessment of disaster management efforts.

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“…Penggunaan satelit penginderaan jauh dan Sistem Informasi Geografis (SIG) telah menjadi alat yang memiliki integrasi, dikembangkan dengan baik, dan berhasil dalam penelitian bencana untuk efektivitas resiko manajemen dan mitigasi bencana yang ada (Abu Bakar Sambah et al 2018). Sistem Informasi Geografis (SIG) memiliki kemampuan dalam mengumpulkan dan menganalisa data dari tiap titik geografis di muka bumi, serta melakukan integrasi antardata yang berbeda dalam satu sistem geografis (Abu Bakar Sambah et al 2020).…”

Section: Pendahuluanunclassified

Pemetaan Kerentanan Tsunami untuk Mendukung Ketahanan Wilayah Pesisir

Isdianto

Kurniasari

Subagiyo

et al. 2021

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Tsunami merupakan bencana yang jarang terjadi namun cukup memberikan kerusakan yang parah terhadap daerah pesisir yang terkena dampaknya. Banyaknya korban jiwa dan juga harta benda disebabkan oleh kurangnya kesiapan masyarakat dalam menghadapi bencana tsunami, sehingga perlu adanya studi tentang ketahanan wilayah pesisir dalam menghadapi bencana tsunami. Langkah awal untuk membangun ketahanan bencana tsunami adalah mengidentifikasi karakteristik ancaman, kerentanan dan resiko bencana tsunami. Sistem Informasi Geografis (SIG) digunakan dalam memetakan kerentanan suatu daerah terhadap bencana tsunami, dengan parameter kerentanan antara lain kemiringan lahan, tingkat elevasi daratan, penggunaan lahan dan jarak dari garis pantai, dan diolah dengan metode Weighted Overlay Analysist. Hasil dari identifikasi variabel kerentanan tsunami menunjukkan bahwa nilai kemiringan lahan antara 2- 6% tergolong rentan, elevasi daratan antara 5 – 10 meter tergolong rentan, penggunaan lahan yang didominasi pertanian tergolong rentan, dan jarak dari garis pantai yang memiliki kerentanan sangat besar apabila semakin dekat dengan pantai. Hasil pengolahan data dengan Weighted Overlay Analysist dari beberapa parameter kerentanan menunjukkan bahwa sebagian besar daerah di Kabupaten Cilacap memiliki kerentanan tsunami dalam kategori Cukup Rentan hingga Rentan, sehingga perlu adanya tindakan penyadaran masyarakat akan bahaya tsunami, penetapan jalur evakuasi tsunami, serta upaya relokasi, adaptasi, dan proteksi di wilayah pesisir.

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Spatial multi criteria approach for tsunami risk assessment

Cited by 6 publications

References 10 publications

Determination of Inundation Zone Using Artificial Intelligence as a Basis for Infrastructure Development in Special Economic Areas of Tanjung Lesung Banten

Determination of Inundation Zone Using Artificial Intelligence as a Basis for Infrastructure Development in Special Economic Areas of Tanjung Lesung Banten

A Modelling and Mitigation Strategy for the Impact of the Tsunami Disaster at Tamban Beach, Malang Regency, using a Geographic Information System

Pemetaan Kerentanan Tsunami untuk Mendukung Ketahanan Wilayah Pesisir

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