Identifying Successive Eruption of Guntur Volcanic Complex Using Magnetic Susceptibility and Polarimetric Synthetic Aperture Radar (PolSAR) Data

Saepuloh, Asep; Bakker, Erwin

doi:10.1088/1755-1315/71/1/012004

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Guntur Volcano has the repose time of more than 160 years, however increasing seismicity has been detected since 1997. The number of VT earthquakes increased on October 1997, May 1999, November 2002, and June 2005 (Sadikin, 2008). On September 2011, the number of VT earthquakes reached 277 events, and then exceeded to 300 events on September 2013.…”

Section: J O Gmentioning

confidence: 97%

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Determination of Hypocentre and Seismic Velocity Structure in Guntur Volcano Using Seismic Data from 2010 to 2014

Basuki¹,

Nugraha

Hidayati³

et al. 2019

Indonesian J. Geosci.

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Guntur Volcano was in a dormant state even though its seismicity had increased on April, 2013 and August, 2013. In this study, determination of hypocentre and seismic velocity structure was conducted using seismic data from 2010 to 2014 as recorded by a seismic station of the Centre for Volcanology and Geological Hazard Mitigation of Indonesia (CVGHM). Volcano-Tectonic (VT) earthquakes were identified and carefully picked for P-and S-wave arrival times. More than 600 events of VT earthquakes from 2010-2014 were located using maximum likelihood estimation algorithm. The initial 1-D seismic velocity was calculated using Velest method in order to get the initial velocity as the input for the tomographic inversion. The results show distribution of VT hypocentres were clustered in three regions, namely Guntur Volcano, Kamojang geothermal area, and Darajat geothermal area. At the Guntur Volcano region, the VT events were located mostly at the northern part of the crater with the depth of hypocentre ranges from 0-4 km. The distribution of the VT events made alignment from the southwest to the northeast with the depth of hypocentre mostly ranges from 0-2 km at Kamojang region. Meanwhile, at Darajat geothermal area, the VT events were located at the depth of 0-2 km and made alignment from the southeast to the northwest. The low velocity zone associated with hot material or fluids was located at the depth of 5 km beneath the Guntur Crater. The location of VT earthquakes at the depth of 0-4 km beneath Guntur Crater was coincided with the area with high Vp and Vs anomalies. The low velocity zones were also found at Kamojang Crater and Cipanas hotspring area. It was predicted that the low velocity zone at the Kamojang Crater was related to a high temperature of the vapour system, whereas the reservoir of water was preferred to be dominated at the Cipanas hotspring.

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Section: J O Gmentioning

confidence: 97%

“…The previous study on VT earthquake and magmatic system at the Guntur Volcano by Sadikin (2008) mentioned the locations of VT earthquakes were distributed in three regions, between (Mount/Crater?) Masigit to Guntur Crater, between Gandapura Caldera to Gajah Crater, and at Kamojang geothermal area.…”

Section: J O Gmentioning

confidence: 99%

Determination of Hypocentre and Seismic Velocity Structure in Guntur Volcano Using Seismic Data from 2010 to 2014

Basuki¹,

Nugraha

Hidayati³

et al. 2019

Indonesian J. Geosci.

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“…The scattering power of four component decomposition( Ps , Pd , Pv , and Ph )(Yamaguchi, 2012;Saepuloh and Bakker, 2017) …”

mentioning

confidence: 99%

An Application of Segnet for Detecting Landslide Areas by Using Fully Polarimetric Sar Data

Antara¹,

Shimizu²,

Osawa³

et al. 2019

EJES

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The study location of landslide is in Hokkaido, Japan which occurred due to the Iburi Earthquake 2018. In this study the landslide has been estimated by the fully Polarimetric SAR (Pol-SAR) technique based on ALOS-2 PALSAR-2 data using the Yamaguchi’s decomposition. The Yamaguchi's decomposition is proposed by Yoshio Yamaguchi et.al. The data has been analyzed using the deep learning process with SegNet architecture with color composite. In this research, the performance of SegNet is fast and efficient in memory usage. However, the result is not good, based on the Intersection over Union (IoU) evaluation obtained the lowest value is 0.0515 and the highest value is 0.1483. That is because of difficulty to make training datasets and of a small number of datasets. The greater difference between accuracy and loss graph along with higher epochs represents overfitting. The overfitting can be caused by the limited amount of training data and failure of the network to generalize the feature set over the training images.

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Identifying Thermal Properties of Ground Surface Derived by SAR and Laboratory Measurements

Saepuloh

Army

Agustan

2018

2018 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

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Identifying Successive Eruption of Guntur Volcanic Complex Using Magnetic Susceptibility and Polarimetric Synthetic Aperture Radar (PolSAR) Data

Cited by 3 publications

References 8 publications

Determination of Hypocentre and Seismic Velocity Structure in Guntur Volcano Using Seismic Data from 2010 to 2014

Determination of Hypocentre and Seismic Velocity Structure in Guntur Volcano Using Seismic Data from 2010 to 2014

An Application of Segnet for Detecting Landslide Areas by Using Fully Polarimetric Sar Data

Identifying Thermal Properties of Ground Surface Derived by SAR and Laboratory Measurements

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