Volcanic Earthquakes Research Articles

A Typical of Tsunami Generation Caused by Volcano Flank Collapse in Banda Neira, Maluku, Indonesia

Abstract The history eruption of the Banda volcanoes was recorded in 1632, 1816, and 1988 and was preceded by significant earthquakes. In the eruption in 2017, there were 28 volcanic earthquakes, indicating a rock cracking process due to the movement of magma in the form of gas, liquid, and rock solids. We suspect that when the earthquake occurs, the rock-cracking process upon the eruption will potentially trigger the volcano flank to collapse into the sea and generate a tsunami in the Banda Naira and surrounding area. We contribute to modeling the travel time and tsunami inundation resulting from the flank collapse of Banda Volcano. BATNAS bathymetry data is used to run tsunami simulations. We use aerial photography from field survey data to interpret Banda Volcano failure parameters, including diameter, direction of sliding of the collapse, and slope of the collapse of the side of the Banda Volcano. Based on the tsunami simulation, the volcano flank collapse source on Banda Volcano produced a maximum tsunami in Banda Naira as high as 6.2 meters, and the tsunami will arrive around 6 – 8 minutes. While in AI Island, tsunami inundation reached 55.87 m and arrived in 4 minutes. Meanwhile, the maximum elevation of Banda Naira Island is 3.5 meters, with a population of 21,000 people in March 2024. Tsunami inundation has the potential to submerge entire residential areas in Banda Neira.

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Analisis Pemberitaan Banjir Lahar Dingin di Sumatera Barat dalam Media Detik.com dan Antaranwes.com

News related to the cold lava flood disaster in West Sumatra that was broadcasted in print, electronic and online media became public consumption, causing perceptions in the community. Online media both Antaranews.com and Detik.com have news related to cold lava floods in West Sumatra. The media provided information from different perspectives in presenting the news. The floods came from material from Mount Marapi that erupted some time ago, most of which was on the slopes of the mountain. The material was washed away by rainwater downstream. Meanwhile, Antaranews.com provides information to the public by quoting the statement of Andalas University researchers that the accumulation of fallen tree material in the upper reaches of the Batang Anai river became a natural dam, due to the volcanic eruption of Mount Marapi accompanied by high rainfall as the cause of the collapse of natural dams and resulting floods. Framing analysis is viewed from syntactic, thematic, script and rhetorical structures. This research uses a qualitative approach with the theory of Zhongdang Pan and M. Kosicki. The results prove that the two online media have different points of view and news packaging, each emphasizing based on the data and facts received. After analyzing the two news articles, the researcher concluded that both news articles provided information on the causes of the flood disaster in West Sumatra. However, if seen in the Detik.com online media, the floods were caused by moderate to heavy rains that washed away volcanic material from the eruption of Mount Marapi in the form of cold lava. Another case with the information put forward by the Antaranews.com media that the flood was caused by the collapse of a natural dam in the upstream section of the Batang Anai river due to the vibration of the volcanic earthquake of Mount Marapi accompanied by high rainfall.

Geotechnical Assessment of Seismic Vulnerability in the Built Environment of Fako Division, South West Region of Cameroon

Introduction: Volcanic earthquakes may trigger severe hazards with considerable impact on the natural and built environment and the surrounding population. Aim: Evaluate the geotechnical characteristics of soils in Fako division to estimate their seismic vulnerability and recommend suitable stabilization techniques to enhance the safety and resilience of built environments. Place and Duration of Study: This study was conducted over a period of 12 months beginning from June 2022 to May 2023. Methodology: It employed a multi-criteria geotechnical approach, involving soil sampling, laboratory analysis, and seismic risk analysis. Soil samples collected from various locations within the study area, were subjected to laboratory tests to determine their plasticity (Atterberg limits) and load-bearing capacity (California Bearing Ratio - CBR). Historical data analysis and seismic hazard mapping were used to assess seismic vulnerability which helped to identify highly susceptible and unstable areas that may require engineered interventions. Results: The findings revealed significant variations in soil plasticity and load-bearing capacity, correlating with observed settlement and instability issues in the region. Historical seismic events, highlighted significant structural damage in areas with high plasticity and low CBR values, underscoring the necessity for robust soil stabilization measures (geotechnical interventions) to mitigate seismic risks and enhance the resilience and safety of structures, reducing the risk of settlement and instability within the Mount Cameroon area, particularly Fako Division.

El Chichón volcanic activity before and after the Mw8.2, 2017, Chiapas earthquake, México. Is El Chichón ready to erupt?

El Chichón volcano is the most active volcano in the state of Chiapas, México, and experienced its last Plinian eruption (VEI = 5) in 1982. To better assess its volcanic hazard, we studied its readiness to erupt by estimating changes in its internal stress state. These stress changes are difficult to calculate accurately, for example in the absence of focal mechanisms, but their existence can be indirectly revealed by the presence of volcano-tectonic earthquakes, for example following a large tectonic earthquake. We show that the seismic rate recorded at El Chichón volcano increased slightly after the large Mw8.2 Tehuantepec earthquake of 8 September 2017, Chiapas. However, this rate quickly returned to its background level after only 2 months, without any external volcanic manifestations, suggesting that the volcano is not ready to erupt in the near future. Previous observations of slight increases in the volcanic seismicity rate following large earthquakes have been explained by the presence of active hydrothermal systems in the vicinity of the volcano. We propose a similar explanation for El Chichón volcano which is known for its large hydrothermal system. Furthermore, the characteristics of the 2017 seismicity (spatial and magnitude distributions), and the horizontal-to-vertical spectral ratio also confirm the presence of high amounts of water near the volcano. We show that the 2017 volcano-tectonic seismicity is of hydrothermal rather than magmatic origin, in agreement with recent independent geochemical and aeromagnetic studies.

Deep‐Learning‐Based Phase Picking for Volcano‐Tectonic and Long‐Period Earthquakes

AbstractThe application of deep‐learning‐based seismic phase pickers has surged in recent years. However, the efficacy of these models when applied to monitoring volcano seismicity has yet to be fully evaluated. Here, we first compile a data set of seismic waveforms from various volcanoes globally. We then show that the performances of two widely used deep‐learning pickers deteriorate systematically as the earthquakes' frequency content decreases. Therefore, the performances are especially poor for long‐period earthquakes often associated with fluid/magma movement. Subsequently, we train new models which perform significantly better, including when tested on two data sets where no training data were used: volcanic earthquakes along the Cascadia subduction zone and tectonic low‐frequency earthquakes along the Nankai Trough. Our model/workflow can be applied to improve monitoring of volcano seismicity globally while our compiled data set can be used to benchmark future methods for characterizing volcano seismicity, especially long‐period earthquakes which are difficult to monitor.

Interpretasi Mekanisme Erupsi Gunung Api Lokon berdasarkan Aktivitas Kegempaan Pra-Erupsi 4 – 12 September 2014

Prior to the eruption of Lokon Volcano on September 13 2014 at 03.09 WITA, there were 62 volcanic earthquake events recorded by seismometers since September 4 2014. This research aims to interpret the eruption mechanism of Lokon Volcano based on seismic activity in the pre-eruption period. 04 - 12 September 2014. The distribution of source points for volcanic earthquakes, both hypocenters, can be visualized using the seismic method, namely by processing digital seimogram data using Swarm 3.1.0 software, GAD (Geiger's method with Adaptive Damping) and Origin 8. Data used, sourced from three stations, namely, Empung (EMP), Wailan (WLN), Kinilow (KIN). Lokon volcano. The hypocenter distribution of volcanic earthquakes is concentrated at a depth of 0 - 1,500 m above sea level and it was found that the aseismic area which is assumed to be a shallow magma pocket area from the Lokon volcano is at a depth of 1,500 - 3,000 m above sea level. The interpretation results show that the eruption mechanism of Lokon Volcano originates from disturbances in the volcanic system which are thought to be the result of tectonic earthquakes in the subduction zone. This causes the magma to rise upwards to supply shallow magma pockets until it reaches maximum pressure and an eruption occurs.

Magma intrusion process during pre-magmatic period (2010−2013) of Sinabung volcano as revealed by seismicity of volcano-tectonic and hybrid earthquakes

Sinabung volcano in Indonesia reactivated, with a series of phreatic eruptions, in August and September 2010. These eruptions were followed by various types of magmatic eruption at the summit, including lava dome growth, pyroclastic density currents, lava flow, and vulcanian eruptions, starting in December 2013. Prior to the magmatic eruptions, Sinabung exhibited two sequences of phreatic eruption and an increase in the seismicity of volcanic earthquakes. This study clarifies the progress of magma intrusion during the pre-magmatic period based on the hypocenter distribution, waveform similarity, seismic moment, rupture length, and stress drop for volcano-tectonic (VT) and hybrid earthquakes. It was found that the hypocenters of VT earthquakes are distributed north and northwest of the summit at a depth range of 1–10 km below sea level. Deep seismicity (4–10 km) alternated with shallow seismicity (2–4 km). The last shallow seismicity, from July to mid-December 2013, was different from previous seismicity in terms of higher intensity, as determined from the seismic moment, a temporary increase in the rupture length, and the migration of hypocenters towards the summit. The seismicity of VT earthquakes was altered by a swarm of hybrid earthquakes in mid-December. The hybrid earthquakes were smaller, in terms of seismic moment (mostly <3 × 1010 Nm), than the VT earthquakes. Their hypocenters were concentrated in the shallowest depth range (−0.5 to 1.5 km below sea level) directly below the summit, their source process was repeatable (they could be grouped into six earthquake families), their dominant peak was in a low-frequency range (2.5–4.5 Hz), and they had a relatively low stress drop (<0.15 MPa). This suggests that the swarm of hybrid earthquakes was induced by a frequent repeated fracture of fluid-filled cracks due to the intrusion of magma up to directly below the summit. The transition of the earthquake family and the change in its source parameters, namely an increase in the stress drop prior to the appearance of a lava dome and then a slight decrease, may reflect a gradual change in internal pressure in the hypocentral zone through the magma intrusion process.

Active Faults, Kinematics, and Seismotectonic Evolution during Tajogaite Eruption 2021 (La Palma, Canary Islands, Spain)

During the 2021 La Palma strombolian and fissure eruption, two faults were identified that controlled the spatial distribution of earthquake hypocenters and effusive eruptive vents. One of these faults has a NW-SE trend (Tazacorte Fault: TZF) and the other one shows an ENE-WSW trend (Mazo Fault: MZF). Previous works on fault structural analysis in La Palma indicated that the eruption zone was compatible with an extensional tectonic strain ellipsoid which activated normal-strike-slip directional faults at the confluence of TZF and MZF. These fractures were activated during the 2021 Tajogaite eruption, determining the NW-SE and WSW-ENE spatial distribution of vents. Both faults were mapped in real time during the volcanic eruption from fieldwork and remote sensing imagery (aerial drone images). We have collected more than 300 fracture data associated with the effusive vents and post-eruption seismic creep. Since the affected area was densely inhabited, most of these fractures affect houses and infrastructures. Some of the houses affected by the TZF were damaged 9 months after the eruption, although they were not damaged during the eruption. Surprisingly, these houses already had repairs made to the same fractures since 1980, giving information of previous fault creep movement. During the 2021 Tajogaite eruption, shallow seismicity was spatially related to both faults, suggesting a seismic behavior instead of the precedent creep movement. However, the lack of seismicity after the eruption indicates that the faults went back to creep aseismic behavior, similarly to 1980. The mapping and monitoring of these faults (TZF and MZF) is relevant bearing in mind that they have been active since 1980 and the post-eruptive phase of the 2021 volcanic eruption, which has to be included in the land use planning in areas affected by the volcanic eruption and creep movement. Furthermore, both faults could act as seismogenic sources triggering volcanic earthquakes with potential high macroseismic intensities and mass movements. The data presented here show the importance of having this type of study before the onset of the eruption, thus allowing a better interpretation of seismic data during volcanic unrest.

HYPOCENTER DISTRIBUTION ANALYSIS OF SINABUNG VOLCANO ERUPTION IN 2021 USING GEIGER'S WITH ADAPTIVE DAMPING (GAD) METHOD

Sinabung Volcano is located in the Karo Highlands, Karo Regency, North Sumatra, Indonesia, with a peak of 2460 meters above sea level. This volcano experienced an increase in volcanic activity in the April-October 2021 period, so it is necessary to analyse volcanic seismicity to determine the hypocenter distribution of the volcano. This study aims to determine the hypocenter distribution and classification of volcanic earthquake types based on seismogram recording data of Sinabung Volcano at four stations, namely LKW, BGR, MDD and SGR stations. The method used in this research is Geiger's method with adaptive damping (GAD) to determine the distribution of hypocenters. The results showed that the hypocenter distribution gathered below the crater centre with depths from 0.172 km to 7.139 km. The determination of the hypocenter distribution of volcanic earthquakes is expected to provide information on the depth of the earthquake to determine the movement of magma and the characteristics of events that occur during the pre-eruption process of Sinabung Volcano so that this data can be used for mitigation decision making when there is an increase in the activity of Sinabung Volcano.

Event classification of volcanic earthquakes based on K-Means clustering: Application on Anak Krakatau Volcano, Sunda Strait

It is important to quickly recognize any physical changes in volcanology and accompanying phenomena at each stage of an eruption in terms of mitigating volcanic eruptions. Automatic classification of the type of volcanic earthquake is required, especially since the data recorded by seismic equipment is classified as big data. Analyzing big data manually will take a lot of time. Therefore, we use unsupervised machine learning such as K-means clustering to generate an automated system of classifying the volcanic events based on their waveform and spectrum characteristics. We examine the clustering of volcanic earthquakes at Anak Krakatau volcano, Sunda Strait during June to July 2014. We use one seismic station which is KRA4 to calculate the K-means clustering at Anak Krakatau volcano. We apply unsupervised machine learning such as K-means clustering to classify volcanic earthquakes. We successfully applied the K-means clustering method and found three clusters that represent the volcanic earthquake types based on the characteristics of the waveform in time and frequency domains. We observed different waveform and frequency characteristics for different clusters. The result is Cluster 1 is characterized by rapid increases in a few seconds, then gradual decreases with time, and the frequency dominant range of 4-4.7 Hz. Cluster 2 is characterized by gradual increases in a few seconds, then gradual decreases with time, and the frequency dominant range of 6-6.5 Hz. Cluster 3 is characterized by gradual increases in a few seconds, then gradual decreases with time in longer duration, and the frequency dominant range of 7-7.5 Hz. This study is useful to automatically classify the big data of daily volcanic activity that is generated continuously to mitigate the volcanic hazard.

A statistical analysis of volcano-tectonic earthquake swarms in the off Nicobar region of the Andaman Sea

A statistical analysis of volcano-tectonic earthquake swarms in the off Nicobar region of the Andaman Sea

Quantifying Magma Overpressure Beneath a Submarine Caldera: A Mechanical Modeling Approach to Tsunamigenic Trapdoor Faulting Near Kita‐Ioto Island, Japan

AbstractSubmarine volcano monitoring is vital for assessing volcanic hazards but challenging in remote and inaccessible environments. In the vicinity of Kita‐Ioto Island, south of Japan, unusual M ∼ 5 non‐double‐couple volcanic earthquakes exhibited quasi‐regular recurrence near a submarine caldera. Following the earthquakes in 2008 and 2015, a distant ocean bottom pressure sensor recorded distinct tsunami signals. In this study, we aim to find a source model of the tsunami‐generating earthquake and quantify the pre‐seismic magma overpressure within the caldera's magma reservoir. Based on the earthquake's characteristic focal mechanism and efficient tsunami generation, we hypothesize that submarine trapdoor faulting occurred due to highly pressurized magma. To investigate this hypothesis, we establish mechanical earthquake models that link pre‐seismic magma overpressure to the size of the resulting trapdoor faulting, by considering stress interaction between a ring‐fault system and a reservoir of the caldera. The trapdoor faulting with large fault slip due to magma‐induced shear stress in the submarine caldera reproduces well the observed tsunami waveform. Due to limited data, uncertainties in the fault geometry persist, leading to variations of magma overpressure estimation: the pre‐seismic magma overpressure ranging approximately from 5 to 20 MPa, and the co‐seismic pressure drop ratio from 10% to 40%. Although better constraints on the fault geometry are required for robust magma pressure quantification, this study shows that magmatic systems beneath calderas are influenced significantly by intra‐caldera fault systems and that tsunamigenic trapdoor faulting provides rare opportunities to obtain quantitative insights into remote submarine volcanism hidden under the ocean.

Reappraisal of volcanic seismicity at the Kirishima volcano using machine learning

Volcanic earthquakes provide essential information for evaluating volcanic activity. Because volcanic earthquakes are often characterized by swarm-like features, conventional methods using manual picking require considerable time to construct seismic catalogs. In this study, using a machine learning framework and a trained model from a volcanic earthquake catalog, we obtained a detailed picture of volcanic earthquakes during the past 12 years at the Kirishima volcano, southwestern Japan. We detected ~ 6.2 times as many earthquakes as a conventional seismic catalog and obtained a high-resolution hypocenter distribution through waveform correlation analysis. Earthquake clusters were estimated below the craters, where magmatic or phreatic eruptions occurred in recent years. Increases in seismic activities, b values, and the number low-frequency earthquakes were detected before the eruptions. The process can be conducted in real time, and monitoring volcanic earthquakes through machine learning methods contributes to understanding the changes in volcanic activity and improving eruption predictions.Graphical

Thermal pattern of Tatun volcanic system by satellite-observed temperatures and its correlation with earthquake magnitudes

The land surface temperature (LST) of volcanoes detected from satellite sensors reflects the thermal status of heat sources in the subsurface. Volcanic earthquakes occur as magma and volcanic fluids transport to the surface from depth. Thus, both LST and earthquake magnitude are key parameters to the study of active volcanoes. Here we investigate the volcanic status of Tatun Volcanic Group (TVG) based on LST and seismic observations. The Earth-observing satellites onboard thermal sensor derived land surface temperature, and the seismic records retrieved volcanic earthquake magnitude are used to delineate the past and current pattern of volcanic activity plus the future trend of the TVG. The spatiotemporal distribution of LST and volcanic earthquake magnitude in TVG are analyzed. The high-similarity trends of the 4-decade LST time series and 3-decade earthquake magnitude time series are inspected. The retrieved surface thermal pattern shows the non-steady-state nature of the subsurface thermal sources at this volcanic complex. The LST trend exhibits a rather positive correlation with the energy released from volcanic earthquakes and consequently, the presumption on the connection between LSTs and earthquakes is validated.

Fan‐hinged shear instead of frictional stick–slip as the main and most dangerous mechanism of natural, induced, and volcanic earthquakes in the earth's crust

AbstractFrictional stick–slip instability along pre‐existing faults has been accepted as the main mechanism of earthquakes for about 60 years, since it is believed that fracture of intact rocks cannot reflect such features inherent in earthquakes as low shear stresses activating instability, low stress drop, repetitive dynamic instability, and connection with pre‐existing faults. This paper demonstrates that all these features can be induced by a recently discovered shear rupture mechanism (fan‐hinged), which creates dynamic ruptures in intact rocks under stress conditions corresponding to seismogenic depths. The key element of this mechanism is the fan‐shaped structure of the head of extreme ruptures, which is formed as a result of an intense tensile cracking process, with the creation of inter‐crack slabs that act as hinges between the shearing rupture faces. The preference of the fan mechanism over the stick–slip mechanism is clear due to the extraordinary properties of the fan structure, which include the ability to generate new faults in intact dry rocks even at shear stresses that are an order of magnitude lower than the frictional strength; to provide shear resistance close to zero and abnormally large energy release; to cause a low stress drop; to use a new physics of energy supply to the rupture tip, providing supersonic rupture velocity; and to provide a previously unknown interrelation between earthquakes and volcanoes. All these properties make the fan mechanism the most dangerous rupture mechanism at the seismogenic depths of the earth's crust, generating the vast majority of earthquakes. The detailed analysis of the fan mechanism is presented in the companion paper “New physics of supersonic ruptures” published in DUSE. Further study of this subject is a major challenge for deep underground science, earthquake and fracture mechanics, volcanoes, physics, and tribology.

Capturing Mayotte's deep magmatic plumbing system and its spatiotemporal evolution with volcano-tectonic seismicity

Since 2018 an unexpected number of earthquakes have been occurring offshore Mayotte, in the Mozambique Channel. They are linked to the eruption of the Fani Maoré submarine volcano. Using a recently-developed comprehensive automatic catalog, we explore two years of volcano-tectonic (VT) seismicity between March 2019 and March 2021 and analyse in detail the active structures of the magmatic plumbing system using ~33,000 events. The VT earthquakes highlight three magma storage zones and two aseismic conduits that had never been observed before. The temporal evolution of the seismicity reveals a probable regime change in March 2020. While before, the plumbing system reacted to the drainage of magma from a deep reservoir and to the migration of magma towards the seafloor, it is now responding to new migrations of fluids and to the redistribution of the stress-load across the system's pre-existing faults. This analysis is key to better understand long-term volcanism worldwide.

New physics of supersonic ruptures

AbstractUntil recently, it is believed that the rupture speed above the pressure wave is impossible since spontaneously propagating ruptures are driven by the energy released due to the rupture motion, which is transferred through the medium to the rupture tip region at the maximum speed equal to the pressure wave speed. However, the apparent violation of classic theories has been revealed by new experimental results demonstrating supersonic shear ruptures. This paper presents a detailed analysis of the recently discovered shear rupture mechanism (fan hinged), which suggests a new physics of energy supply to the tip of supersonic ruptures. The key element of this mechanism is the fan‐shaped structure of the head of extreme ruptures, which is formed as a result of an intense tensile cracking process with the creation of intercrack slabs that act as hinges between the shearing rupture faces. The fan structure is featured with the following extraordinary properties: extremely low friction approaching zero; amplification of shear stresses above the material strength at low applied shear stresses; creation of a self‐disbalancing stress state causing a spontaneous rupture growth; abnormally high energy release; generation of driving energy directly at the rupture tip which excludes the need to transfer energy through the medium. The fan mechanism operates in intact rocks at stress conditions corresponding to seismogenic depths and in pre‐existing extremely smooth interfaces due to identical tensile cracking processes at these conditions. This is Paper 1 (of two companion papers) which discusses the fan theory and extreme ruptures in experiments on extremely smooth interfaces. Paper 2 entitled “Fan‐hinged shear instead of frictional stick‐slip as the main and most dangerous mechanism of natural, induced and volcanic earthquakes in the earth's crust” considers extreme ruptures in intact rocks. Further study of this subject is a major challenge for deep underground science, earthquake and fracture mechanics, physics, and tribology.

Seismicity and Magmatic System of the Changbaishan Intraplate Volcano in East Asia

AbstractA high‐precision earthquake catalog is made from continuous waveform data recorded at 360 portable seismographs deployed for one month in the Changbaishan‐Tianchi volcanic area based on an automatic earthquake detection and location workflow. Then we investigate detailed 3‐D structures of P and S wave velocities (Vp and Vs) and Vp/Vs ratio of the crust beneath the study region. Our results reveal a high‐Vp/Vs zone accompanied with active volcanic earthquakes beneath the Tianchi caldera at ∼5 km depth, which may reflect a magma chamber. The intense seismic activities within 2 km depth beneath the Tianchi caldera from 2002 to 2005 occurred directly above the magma chamber revealed by this study, which could be related to upward migration of high‐pressure volatiles originating from the magma chamber. A potential middle‐crustal magma chamber might provide continuous magmatic materials feeding the upper‐crust magma chamber and lead to ruptures of surrounding rocks, resulting in two swarms of volcanic seismicity during the observation period. We deem that the diverse eruption styles of the Changbaishan volcano are closely associated with the multilevel structure of magma chambers in the upper and middle crust.

The Impact of Environmental, Social, And Economic Factors Due to Anak Krakatau Volcano Tsunami Using Remote Sensing Technology

Tsunamis often occur in the territory of Indonesia because it is widely traversed by encounters between earth plates under the sea. Thus, if an earthquake occurs, it has the potential to generate a tsunami. The Indonesian region is also located in the ring of the fire area, and is the country with the highest number of active volcanoes with more than 127 events, that can encourage volcanic earthquakes. In addition, when volcanoes erupt offshore, the potential for a tsunami will be even greater because the expulsion of material can generate landslides toward the sea, causing a tsunami. The tsunami that happened in the eruption of Anak Krakatau on December 22, 2018, in the Sunda Strait, resulted in a tsunami in the Lampung and Banten areas. This study tries to compare environmental, social, and economic factors before and after the tsunami in the coastal areas of Lampung and Banten. The integration of remote sensing data will be carried out to determine environmental, social, and economic factors such as Land Cover, NDWI, NDVI, Night Light, and NO2 data. Random Forest Machine Learning will also be involved in shaping land cover models. Random Forest is often used because it has high accuracy. The results show a significant change in land cover in coastal areas and the impact of environmental, social, and economic factors. This study is expected to support the mitigation process in the event of a tsunami in the future. In addition, it is expected to be used by policymakers in planning development after the tsunami disaster.