A Statistical review of the dates and patterns of volcanic activity of Lewotolo Volcano, East Nusa Tenggara, Indonesia

Muliawati, T; Harbowo, D G

doi:10.1088/1755-1315/1245/1/012006

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…This position can have an impact on gravitational attraction, which affects fluid dynamics in the magma chamber, as well as the surface hydrostatic pressure caused by tidal changes. A similar phenomenon can also be found in several volcanoes, such as Mount Etna in Italy, Mount Lewotolo in Indonesia, and other frequently erupting volcanoes that appear to interact with annual planetary gravity [13][14][15][16][17]. The plot results showed a relationship between increased activity and dates in the Gregorian calendar.…”

Section: Height Of Ash Columnsupporting

confidence: 67%

State transition matrix and Markov-chain diagram for frequent volcanic eruptions: Krakatoa, Indonesia

Harbowo,

Muliawati

2024

E3S Web of Conf.

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Krakatoa has been a global attraction throughout history. Historical records of eruptions on this volcanic island complex provide thrill and excitement for visitors at once. They are often stunned by sudden eruptions, noticed by columns of ash billowing high into the sky and drawing attention to the scene. However, eruptions such as this also risk visitors of an improper radius. Therefore, in this study, we aimed to reveal the probability pattern of eruptions to sustain preparedness for the worst. Through the Anakrakatau eruption dataset that we collected from 2018 to 2023 [n=540], we propose a transition matrix diagram of eruption events generated from probability analysis. The approach of this method is based on a Markov-chain analysis. This study assessed the period between eruptions and the probabilities of observed column height. In this study, state determination refers to the k-means clustering (k=3) each variable. The results show that there are states that represent the variety of circumstances transitions in frequent small activity eruption. The highest probability achieved at eruption with maximum ash column below 800 m and time gaps between eruptions in less than two days. The results of this study provide new insights into the probability of annual eruptions and provide information for sustainable risk mitigation purposes. This report can be a reference for visitors to the Krakatau area, either for education or research.

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Section: Height Of Ash Columnsupporting

confidence: 67%

State transition matrix and Markov-chain diagram for frequent volcanic eruptions: Krakatoa, Indonesia

Harbowo,

Muliawati

2024

E3S Web of Conf.

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Biogeographical land bridges of Bali-Nusa Penida-Lombok: A possible dispersal pathway for terrestrial fauna during the Pleistocene Glacial periods

Harbowo,

Agustina

2024

BIO Web Conf.

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Fossil records in the Lesser Sunda region provide evidence of colonization by prehistoric humans and terrestrial fauna, dating back to the Pleistocene glacial periods. We believe that Nusa Penida was once part of a dispersal pathway connecting a biogeographical land bridge between Bali and Lombok. Therefore, in this study, we aim to identify the presence of this land bridge using a bathymetric map and reconstruct it at different global sea levels corresponding to glacial conditions. The study also examined the Bouguer Gravity Anomaly to estimate its lithological characteristics. The results indicate that land bridges possibly existed on both the western and eastern sides of Nusa Penida during the Pleistocene glacial periods, at least since 800,000 years ago. These land bridges directly connected the southern part of Bali to the southern part of Lombok. As sea levels rose during interglacial periods, they gradually submerged. Particularly on the eastern side, the remnants of the land bridge are located approximately 225 meters below the modern sea level. This land bridge seemingly experienced intense abrasion due to the pre-modern Indonesian Throughflow (ITF); local tectonic events might also be responsible. This study provides insights into land-based biogeographical dispersal pathways across the Wallace Line.

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Advancing the automated foraminifera fossil identification through scanning electron microscopy image classification: A convolutional neural network approach

Harbowo,

Muliawati

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Handling more than thousand fossil foraminifera data is very challenging, especially for old-way identification. Determining morpho-taxonomy by conventional microscopic observation is very time-consuming and can lead to innacuracy identification. We are certain that the process could be advanced through big data analysis using a machine learning approach. Foraminifera fossils have already become a common standard for biostratigraphic proxies and paleoenvironmental interpretation. Therefore, the objective of this study was to develop an automated identification method using Convolutional Neural Networks (CNN). We used standardized Scanning Electron Microscopy (SEM) images of foraminifera acquired from various open-source databases for image classification. The analysis was conducted using Python programming language in Google Colaboratory. The image dataset is categorized based on its genus (n: 138) and divided into training and test/validation data for accuracy simulation (total image: 1833; data training: 1387; test/validation: 237/237). The best-fit accuracy values of the training-data and testing-data were between 97-86%:73-77%, with parameters including epoch number ranging up to 40, learning rates of 0.05, and a batch size of 64. These values indicate good prospects for foraminifera SEM Image taxonomic classification, demonstrating a noteworthy level of identification accuracy (63%). The outcomes of this study offer a new method for further effective automated morpho-taxonomic identification of foraminifera fossils using other conventional optic microscopy.

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A Statistical review of the dates and patterns of volcanic activity of Lewotolo Volcano, East Nusa Tenggara, Indonesia

Cited by 3 publications

References 17 publications

State transition matrix and Markov-chain diagram for frequent volcanic eruptions: Krakatoa, Indonesia

State transition matrix and Markov-chain diagram for frequent volcanic eruptions: Krakatoa, Indonesia

Biogeographical land bridges of Bali-Nusa Penida-Lombok: A possible dispersal pathway for terrestrial fauna during the Pleistocene Glacial periods

Advancing the automated foraminifera fossil identification through scanning electron microscopy image classification: A convolutional neural network approach

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