Study of characteristic of tsunami base on the coastal morphology in north Donggala, Central Sulawesi

Rahmadaningsi, W S N; Assegaf, Alimuddin Hamzah; Setyonegoro, Wiko; Paharuddin,

doi:10.1088/1742-6596/979/1/012020

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…According to an earlier study by Horspool et al [7], who conducted a national probabilistic tsunami hazard assessment in Indonesia, which included Sulawesi Island among the study areas, over the last 100 years, the eastern part of Indonesia has experienced more massive tsunami events than has the western part. The northern arm of Sulawesi may generate earthquakes and tsunamis as a result of the subduction zone in the Sulawesi Sea [8]. Rahmadaningsi [8] constructed a simulation using a single fault method and simulated tsunami inundation using raster calculator functions in ArcGIS software, based on the 1996 earthquake that occurred at Toli-Toli, North Sulawesi.…”

Section: Introductionmentioning

confidence: 99%

“…The northern arm of Sulawesi may generate earthquakes and tsunamis as a result of the subduction zone in the Sulawesi Sea [8]. Rahmadaningsi [8] constructed a simulation using a single fault method and simulated tsunami inundation using raster calculator functions in ArcGIS software, based on the 1996 earthquake that occurred at Toli-Toli, North Sulawesi. The result shows that bay-shaped shorelines are associated with higher tsunami run-ups than straight or cape-shaped shorelines.…”

Section: Introductionmentioning

confidence: 99%

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An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia

Syifa

Kadavi

Lee

2019

Sensors

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A Mw 7.4 earthquake hit Donggala County, Central Sulawesi Province, Indonesia, on 28 September 2018, triggering a tsunami and liquefaction in Palu City and Donggala. Around 2101 fatalities ensued and 68,451 houses were damaged by the earthquake. In light of this devastating event, a post-earthquake map is required to establish the first step in the evacuation and mitigation plan. In this study, remote sensing imagery from the Landsat-8 and Sentinel-2 satellites was used. Pre- and post-earthquake satellite images were classified using artificial neural network (ANN) and support vector machine (SVM) classifiers and processed using a decorrelation method to generate the post-earthquake damage map. The affected areas were compared to the field data, the percentage conformity between the ANN and SVM results was analyzed, and four post-earthquake damage maps were generated. Based on the conformity analysis, the Landsat-8 imagery (85.83%) was superior to that of Sentinel-2 (63.88%). The resulting post-earthquake damage map can be used to assess the distribution of seismic damage following the Palu earthquake and may be used to mitigate damage in the event of future earthquakes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia

Syifa

Kadavi

Lee

2019

Sensors

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“…In addition, a tsunami is not always produced by an earthquake. [16] [4] further explains that underwater volcanic eruptions (for example the Krakatau eruption in 1883), hilly coastal landslides (for example Landslides in Lituya Bay in 1958), and the impact of meteors from outer space are other potential factors causing a tsunami on the coast. Therefore, given the tsunami that can spread rapidly in the high seas without losing much of its energy, coastal regions in the vast oceans such as the Indian Ocean, the Pacific Ocean and the Atlantic Ocean are very vulnerable to the impact of the tsunami.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Physical Development of the Coastal Tourism Regions on Tsunami Potentially Zones in Pariaman City- Indonesia

Hermon¹

2019

GEOMATE

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The purpose of this research is to determine the location of evacuation lines, TES or assembly points and shelters, and knowing the extent of the distribution of coastal tourism regions, as well as the distance of evacuation routes to TES or assembly points and shelters when tsunami occurs through the creation of a zoning model of coastal tourism-based disaster mitigation regions in Pariaman City. Methods in this research, i.e determining the location of TES or assembly points and shelters, and determine the capacity of TES or assembly points and shelters. Data processing and analysis for determining location, the capacity of TES or assembly points and shelters through the GIS approach. The results showed the tourism region of Gandoriah beach (7.8 Ha) an average tourist visit in 1 month in 2017 as many as 89.188 people/month with the number of TES or assembly points 2 and shelters 2, the tourism regions of Anas Malik and Cermin beach (16.11 Ha) an average tourist visit in 1 month in 2017 as many as 55.743 people/month with the number of shelter 1, the tourism region of Kata beach (19.68 Ha) an average tourist visit in 1 month in 2017 as many as 44.594 people/month the number of TES or assembly points 3 and does not have a shelter; and the tourism region of Naras beach (7.54 Ha) an average tourist visit in 1 month in 2017 as many as 33.445 people/month with the number of TES or assembly point 1 and shelter 1.

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Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia

Jena

Pradhan

Beydoun

et al. 2020

Science of The Total Environment

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Study of characteristic of tsunami base on the coastal morphology in north Donggala, Central Sulawesi

Cited by 3 publications

References 2 publications

An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia

An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia

Evaluation of Physical Development of the Coastal Tourism Regions on Tsunami Potentially Zones in Pariaman City- Indonesia

Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia

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