Long Term Ground Deformation of Mount Raung as Inferred by InSAR and GPS Data

Kriswati, Estu; Agustan, Agustan; Frederik, Marina C. G.; Saepuloh, Asep; Darmawan, Soni; Alfianti, Hilma

doi:10.1109/apsar52370.2021.9688412

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…Methodologies for producing landslide susceptibility maps are mainly based on GIS technology. Previous published works has been explained to solve the deficiencies and difficulties in landslide susceptibility assessment [19,[21][22][23]. Practically, the procedure for preparing landslide susceptibility maps should be applicable and accurate to the field scale.…”

Section: Discussionmentioning

confidence: 99%

Application of modified Segment Tracing Algorithm (mSTA) Method to Identify Landslide Susceptibility Zones Around Mt. Sinabung, Indonesia

Zahratunnisa,

Saepuloh,

Kriswati

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Lineament could present the fractured zones and increase the landslides occurrence probabilities. This study aims to assess landslides susceptibility zones based on recorded landslide events corresponded to the detected lineaments around Mt. Sinabung, Indonesia. In this study, we use Synthetic Aperture Radar (SAR) data to increase the extraction accuracy of fracture-related lineament at Mt. Sinabung. The lineament densities were calculated to identify the landslide susceptibility zones including frequency, length, and intersection using modified Segment Tracing Algorithm (mSTA) method for area about 10.9 × 9 km. Based on visual observations and technical report, a total of 61 landslides were occurred around Mt. Sinabung from 2016, 2018, and 2021. An Ordinary Kriging density map of the lineament frequency using 800 × 800 m cells showed agreement between the lineament density and landslide distribution. Comparing landslide location and lineament density, landslide occurrences were located mainly at high and moderate lineament densities. We have classified the landslide density for three years into low, moderate, and high based on histogram quartile analyses. This classification could be used to mitigate the landslide hazard in a large area.

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Section: Discussionmentioning

confidence: 99%

Application of modified Segment Tracing Algorithm (mSTA) Method to Identify Landslide Susceptibility Zones Around Mt. Sinabung, Indonesia

Zahratunnisa,

Saepuloh,

Kriswati

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Another advantage of using LiCSBAS is that users can monitor ground deformation easily, quickly, and in large coverage area with the availability of LiCSAR data. Some scientific research regarding LiCSBAS method includes deformation monitoring studies in Southern Sumatra (Al Ghiffari, 2022 andNugroho, 2022), around the Opak Fault area (Dewanto, 2020), landslide zones (Rosyidy, 2021), volcanic activity on Mount Raung (Kriswati, 2021), and subsidence due to groundwater exploitation (Ghorbani, 2022).…”

Section: Methodsmentioning

confidence: 99%

The Utilization of LiCSBAS for Deformation Monitoring in Geresa Segment of Matano Fault, Central Sulawesi, Indonesia

Muhammad Razzaaq Al Ghiffari,

Djoko Nugroho,

Rachmat Ramadhan

et al. 2024

J. Geoscience Eng. Environ. Technol.

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Sulawesi is situated between the confluence of three plates, resulting in a very complex tectonic setting on the island. This has an impact on the occurrence of geological structures, including faults. One of them is the Matano Fault which consists of 6 segments (Kuleana Segment, Pewusai Segment, Matano Segment, Pamsoa Segment, Ballawai Segment, and Geresa Segment). The research area is located in Morowali Regency, covering the Geresa Segment. Morowali Regency recorded an earthquake with a magnitude of 5.7 in 2012. This indicates that deformation has occurred. Therefore, this study aims to identify the deformation velocity around the Geresa Segment area. The methods used are geological observation and satellite image data processing to obtain information on deformation rates. The geological field study includes aspects of geomorphology, geological structure, and the rock types distribution. Meanwhile, the processing of satellite image data in the form of InSAR is carried out through the LiCSBAS package tools that has been integrated with LiCSAR. The analysis results illustrate the difference in deformation velocity around the Geresa Segment area. The area which is composed of Tolaka formation and Ultramafic complex tends to uplift with a deformation rate of up to 17 mm/year. In addition, alluvium that covers the southeastarn part has a land subsidence of up to 7 mm/year.

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“…After a small explosive eruption in 2020 (Table 1), another eruption, producing both ash and lava ow, occurred from January to April 2021 (Table 1). These two eruptions were preceded by some in ation of the volcano (Kriswati et al 2021). To better understand the volcanic activity at Raung, we used different remote sensing data.…”

Section: -Geological Settingmentioning

confidence: 99%

The use of high-resolution satellite topographic data to quantify volcanic activity at Raung volcano (Indonesia) from 2011 to 2021

Galetto,

Lillo,

Pritchard

2024

Preprint

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Quantifying erupted masses of magma is fundamental to determine the size of eruptions. Pre- and post- eruptive Digital Elevation Models (DEMs) derived from satellite data can quantify erupted masses, even in remote areas. Here we used bistatic Synthetic Aperture Radar (SAR) data from the TanDEM-X satellite and EarthDEMs derived by stereo-optical data, to investigate topographic changes and the erupted mass at the caldera of Raung (Indonesia), which is one of the most frequently erupting volcanoes on Java. We found that erupted masses associated with Magnitude ≤ 2 eruptions occurred from 2000 to mid-2014 are difficult to be estimated with these DEMs, due to the difficultly to separate the signal of the limited amount of ash deposited within the caldera from data errors. On the contrary, these DEMs mapped at high resolution deposits of Magnitude ≥ 3 eruptions. The November 2014 – August 2015 eruption produced 11.72 ± 1.58 x1010 kg of magma (Magnitude 4.06 ± 0.06), generating lava flows with a maximum height of ~ 46–50 meters and a new intra-caldera cone. The January-April 2021 eruption, never studied before, erupted at least 2.29 ± 0.76 x1010 kg of magma (Magnitude 3.34 ± 0.15), generating lava flows (maximum thickness ~ 16–21 meters) and the growth of the intra-caldera cone. Our analysis reveals that the different pre-eruptive DEMs used to process SAR data and calculate topographic and volume changes can affect extrusive mass estimates by up to ~ 60%. Erupted masses at Raung here estimated could be used in future studies to develop physics-based models coupling extrusion rates with other monitoring parameters to further improve the knowledge of this frequently erupting volcano.

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Long Term Ground Deformation of Mount Raung as Inferred by InSAR and GPS Data

Cited by 6 publications

References 11 publications

Application of modified Segment Tracing Algorithm (mSTA) Method to Identify Landslide Susceptibility Zones Around Mt. Sinabung, Indonesia

Application of modified Segment Tracing Algorithm (mSTA) Method to Identify Landslide Susceptibility Zones Around Mt. Sinabung, Indonesia

The Utilization of LiCSBAS for Deformation Monitoring in Geresa Segment of Matano Fault, Central Sulawesi, Indonesia

The use of high-resolution satellite topographic data to quantify volcanic activity at Raung volcano (Indonesia) from 2011 to 2021

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