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This study comprehensively investigates the source mechanisms associated with the mainshock and aftershocks of the Mw = 6.3 Yogyakarta earthquake which occurred on May 27, 2006. The process involved using moment tensor inversion to determine the fault plane parameters and joint inversion which were further applied to understand the spatial and temporal slip distributions during the earthquake. Moreover, coseismal slip distribution was overlaid with the relocated aftershock distribution to determine the stress field variations around the tectonic area. Meanwhile, the moment tensor inversion made use of near-field data and its Green’s function was calculated using the extended reflectivity method while the joint inversion used near-field and teleseismic body wave data which were computed using the Kikuchi and Kanamori methods. These data were filtered through a trial-and-error method using a bandpass filter with frequency pairs and velocity models from several previous studies. Furthermore, the Akaike Bayesian Information Criterion (ABIC) method was applied to obtain more stable inversion results and different fault types were discovered. Strike–slip and dip-normal were recorded for the mainshock and similar types were recorded for the 8th aftershock while the 9th and 16th June were strike slips. However, the fault slip distribution from the joint inversion showed two asperities. The maximum slip was 0.78 m with the first asperity observed at 10 km south/north of the mainshock hypocenter. The source parameters discovered include total seismic moment M0 = 0.4311E + 19 (Nm) or Mw = 6.4 with a depth of 12 km and a duration of 28 s. The slip distribution overlaid with the aftershock distribution showed the tendency of the aftershock to occur around the asperities zone while a normal oblique focus mechanism was found using the joint inversion.

Kelud is one of Indonesian volcano lies between Kediri and Blitar districts of East Java province. This volcano has erupted since 1000 where casualties of 200000 people emerged until the last eruption in 2014. Therefore, it is needed a volcano early warning system to detect the eruption earlier for minimizing the casualties. We have developed an early warning system based on sensor nodes consist of vibration, temperature and gasses (sulfur and carbon dioxide) sensors to monitor the physical parameter of the volcano, drone surveillance, mapping and temperature measurement, and mobile robot consists of the same sensor as in the node for both normal and emergency situations. The system has been tested in Kelud volcano in August 2019. In a normal condition, the system has detected 1 Hz of seismicity, under 1 ppm of sulfur and carbon dioxide, 23-55.3oC of the lake temperature, 32oC of the ground temperature and 23-25oC of the air temperature. The system could be used for 37 hours of full operation for 1 charging cycles of solar cell’s charging process where suitable for dangerous environment application.

We present the combination of permutation entropy (PE) and power spectral density (PSD) analysis on continuous seismic data recorded by short-period seismic stations during the 2010 Merapi volcano eruption. The calculation of PE aims at characterizing the randomness level in seismic noise, while the PSD parameters use to detect the background noise level in various frequency bands. It was previously observed that a significant reduction of randomness before the volcano eruption could be indicated as one of the short-term precursors due to the lack of high frequencies (>1 Hz) in the noise wave-field caused by high absorption losses as the hot magma uprises to the upper crust. The results show no significant reduction in signal randomness before the eruption series. The characteristic of events during the preeruptive period and the crisis tends to be chaotic (PE in the range 0.9 to 1). Further calculations show that the standard deviation in PE decreased in four days before the first eruption onset on 26 October. PE was stable at the highest values (very close to 1) and gradually returned to the previous fluctuation after the eruption onset. The level of background noise in the low- and high-frequency bands appeared to have the same tendency. The two main eruptions correspond to the two highest peaks of noise levels.

Yogyakarta earthquake, Mw 6.3, 27 May 2006 had killed 5,571 victims and destroyed more than 1 million buildings. This incident became the most destructive earthquake disaster over the last 11 years in Indonesia. Earthquake mitigation plan in the area has been carried out by understands the location of the fault. The location of the fault is still unclear among geoscientists until now. In this case, analysis of the aftershocks using oct-tree importance sampling method was applied to support the location of the fault that responsible for the 2006 Yogyakarta earthquake. Oct-tree importance sampling is a method that is recursively subdividing the solution domain into exactly eight children for estimating properties of a particular distribution. The final result of the subdividing process is a cell that has a maximum Probability Density Function (PDF) and identified as the location of the hypocenter. Input data consists of the arrival time of the P wave and S wave of the aftershocks catalog from 3-7 June 2006 and the coordinate of the 12 seismometers, and 1D velocity model of the study area. Based on the hypocenter distribution of the aftershocks data with the proposed method show a clearer trend of the fault compared with the aftershocks distribution calculated with theHypo71program. The fault trend has a strike orientation of N 42° E with a dip angle of 80° parallel with the fault scarp along the Opak River at the distance of about 15 km to the east. This fault trend is similar with the fault orientation obtained using the Double Difference Algorithm.

One-dimensional modeling of magnetotelluric (MT) data has been performed using an online application on a web-based virtual private server. The application was developed with the Python language using the Django framework with HTML and CSS components. The input data, including the apparent resistivity and phase as a function of period or frequency with standard deviation, can be entered through an interactive web page that can be freely accessed at https://komputasi.geofisika.ugm.ac.id. The subsurface models, represented by resistivity as a function of depth, are iteratively improved by changing the model parameters, such as the resistivity and the layer depth, based on the observed apparent resistivity and phase data. The output of the application displayed on the screen presents resistivity as a function of depth and includes the RMS error for each iteration. Synthetic and real data were used in comparative tests of the application's performance, and it is shown that the application developed accurate subsurface resistivity models. Hence, this application can be used for practical one-dimensional modeling of MT data. One-dimensional inversion MT data is performed using an online application.Input data can be entered or imported through an interactive web page.The application's performance showed accurate subsurface resistivity models.

Gravitational instability of discrete lava lobes in an active dome-building volcano may generate rockfalls that travel up to hundreds of meters from the summit. Understanding the behaviour of rockfalls is important for volcanic hazard assessment as rockfalls can precede large dome collapses that generate pyroclastic flows. Here, we investigate the mechanisms, trajectory, velocity and seismic characteristic of rockfalls at the Merapi volcano through high-resolution video and seismic-spectrum frequency analysis. High-resolution videos of rockfall events were converted to images for every second and were scaled with a georeferenced 3D point cloud to convert pixels into scaled units on the order of a meter. The scaled images were analysed using pixel tracking to investigate the mechanism, trajectory, and velocity of rockfalls. Results illustrate that the rockfall mechanisms include gravitational free fall, rolling and bouncing, airborne rotation and rolling over high-friction basal surfaces. The dynamic mechanisms of gravitational rockfalls at Merapi are strongly controlled by the topography and the condition of the basal surface, which is responsible for the continuous fluctuations in rockfall velocity. Maximum rockfall velocity occurs when rocks become airborne while rotating over the steepest area with velocity up to ~90 m/s. Material rolling over gently sloping, high-friction basal surfaces can significantly reduce the rockfall velocity to 2 m/s, which then ceases the rock movement. Our high-resolution video documents the relatively short durations of gravitational rockfall events at Merapi in the range of 24–61 s and has different time duration with the short-period seismic signals as the movement of small rock fragments over sandy area is not detected by seismic signal. Spectral analysis of seismic frequencies indicates that gravitational rockfalls at Merapi are characterized by high frequencies, with a range of 4–17 Hz. This study provides new insights and improves our understanding of the dynamic mechanism of rockfall events at dome-building volcanoes.

The improvement of an external fiber optic sensor both in design and in operational was conducted based on displacement measurement. The purpose of the investigation is to measure the frequency and the amplitude of seismograph signal using the fiber-optic displacement sensor. This sensor setup consists of an optical fiber transmitter, an optical fiber bundle probe, photodiode detector and a seismograph stimulator. The use of stimulator is as a volcano signal model for the testing process. The sensor has the capability to measure the seismograph signal from 0.5 to 1.5 Hz and the linearity is more than 99 %. The proposed sensor is simple, sensitive, provides high dynamic range, and offers lower cost of the fabrication and thus it is suitable to be applied in real field. Furthermore, this sensor generates more excellent result in accuracy and reliability.

Seismic reflection is one of the most popular methods in geophysical prospecting. Nevertheless, obtaining high resolution and accurate results requires a sophisticated processing stage. There are many open-source seismic reflection data processing software programs available; however, they often use a high-level programming language that decreases its overall performance, lacks intuitive user-interfaces, and is limited to a small set of tasks. These shortcomings reveal the need to develop new software using a programming language that is natively supported by Windows® operating systems, which uses a relatively medium-level programming language (such as C#) and can be enhanced by an intuitive user interface. SEISGAMA was designed to address this need and employs a modular concept, where each processing group is combined into one module to ensure continuous and easy development and documentation. SEISGAMA can perform basic seismic reflection processes. This ability is very useful, especially for educational purposes or during a quality control process (in the acquisition stage). Those processes can be easily carried out by users via specific menus on SEISGAMA’s main user interface. SEISGAMA has been tested, and its results have been verified using available theoretical frameworks and by comparison to similar commercial software.

A detailed study had been conducted on the sediment of Mount Samalas’ volcanic eruption in 1257 AD. Using the framework of the reconstruction of the ancient eruption of Mount Samalas, the first step was to map and analyze the deposits of volcanic sediment. Secondly, we analyzed the effect of geomorphology and the distance function to the isopach thickness. The results show that a combination of methods allowed to provide a high resolution map of the distribution of the thickness of the volcanic deposits, both on the slope and in alluvial areas. Geo-electric survey results (both Vertical Electric Sound (VES) and 2D mapping) show consistent changes in the pattern of contrast resistivity layer interface, for all areas. The pattern changes in a row of the top layer, the high resistivity turned into the low. Furthermore, the second and third layer interface changes from low to the high resistivity. High resistivity on the top layer is interpreted as a layer of unconsolidated volcanic sediment. High resistivity values are range from 736 to 2000 Ohm.m on the top layer in the area of the slopes while in the area of alluvial, the resistivity values range from 20 to 958 Ohm.m. Generally, the volcanic deposits in the area of the slopes have a higher value of isopach (>17 m) than in areas of alluvial (

We present an image of the hydrothermal system of Merapi volcano based on results from electrical resistivity tomography (ERT), self-potential, and CO 2 flux mappings. The ERT models identify two distinct low-resistivity bodies interpreted as two parts of a probably interconnected hydrothermal system: at the base of the south flank and in the summit area. In the summit area, a sharp resistivity contrast at ancient crater rim Pasar-Bubar separates a conductive hydrothermal system (20–50 Ω m) from the resistive andesite lava flows and pyroclastic deposits (2000–50,000 Ω m). The existence of preferential fluid circulation along this ancient crater rim is also evidenced by self-potential data. The significative diffuse CO 2 degassing (with a median value of 400 g m −2 d −1 ) is observed in a narrow vicinity of the active crater rim and close to the ancient rim of Pasar-Bubar. The total CO 2 degassing across the accessible summital area with a surface of 1.4 ⋅ 10 5 m 2 is around 20 t d −1 . Before the 2010 eruption, Toutain et al. (2009) estimated a higher value of the total diffuse degassing from the summit area (about 200–230 t d −1 ). This drop in the diffuse degassing from the summit area can be related to the decrease in the magmatic activity, to the change of the summit morphology, to the approximations used by Toutain et al. (2009) , or, more likely, to a combination of these factors. On the south flank of Merapi, the resistivity model shows spectacular stratification. While surficial recent andesite lava flows are characterized by resistivity exceeding 100,000 Ω m, resistivity as low as 10 Ω m has been encountered at a depth of 200 m at the base of the south flank and was interpreted as a presence of the hydrothermal system. No evidence of the hydrothermal system is found on the basis of the north flank at the same depth. This asymmetry might be caused by the asymmetry of the heat supply source of Merapi whose activity is moving south or/and to the asymmetry in topography caused by the presence of Merbabu volcano in the north. On the basis of our results we suggest that stratified pyroclastic deposits on the south flank of Merapi screen and separate the flow of hydrothermal fluids with the gaseous part rising through the crater rims, while the liquid part is flowing downwards to the base of the edifice.