This project presents a comparative seismological analysis of three tectonically active regions: Himalaya, California, and Alaska to understand how earthquake waveforms and frequency content differ based on fault mechanisms and tectonic settings. By using real-time waveform data obtained from the IRIS FDSN client and processing it through the ObsPy library in Python, the study extracts and visualizes both seismograms and spectrograms for a variety of moderate to large earthquakes from each region. In addition to temporal waveform analysis, spatial distribution is explored through map views, depth cross-sections, and 3D hypocentral plots, helping to understand how earthquake foci vary in geometry, clustering, and depth depending on tectonic context. Yearly histograms are also generated to examine temporal patterns of seismicity, providing insights into the frequency of earthquakes over time in each region. The Himalayan region, representing a thrust-fault environment due to continental collision (India–Eurasia plate convergence), exhibits long-duration waveforms with dominant low-frequency energy, especially during major events like the 2015 Gorkha M7.8 earthquake. The California region, characterized by strike-slip faulting along the San Andreas system, shows more impulsive waveforms with broader frequency content, reflective of shallow, brittle crustal rupture. Meanwhile, Alaska, situated on a subduction zone, demonstrates the most intense and long-lasting seismic signals, particularly during massive events such as the 2021 M8.2 Chignik earthquake, where energy is primarily concentrated at very low frequencies (<5 Hz) and hypocenters reach significant depths. By comparing waveform shapes, frequency content, depth distributions, and temporal occurrence, this project clearly illustrates how tectonic regimes influence earthquake behavior. The findings underscore the importance of seismic waveform analysis for understanding earthquake mechanics, seismic hazard assessment, and regional seismotectonic frameworks.

The 11 March 2011 Mw 9.0 Tohoku-Oki megathrust earthquake off the coast of northeastern Japan represents one of the most significant seismic events in recorded history, both in magnitude and in the scale of its aftershock sequence. In this study, a decade-long seismic catalog (2001–2011) preceding the mainshock and post-seismic records extending to 2015 were analyzed using data retrieved from the IRIS/ISC catalogs. Pre-mainshock seismicity revealed a background dominated by events of M 2–5, punctuated by episodic swarms and moderate earthquakes (M 6–7) at roughly biennial intervals. Cumulative and monthly rate analyses showed a steady background trend followed by an acceleration of seismicity in the final years before the mainshock, suggestive of foreshock activity. Post-mainshock analysis demonstrated an extraordinary increase in seismicity, with more than 15,000 earthquakes occurring in the first month after the mainshock. This aftershock sequence exhibited a rapid decay over subsequent months and years, consistent with Omori’s law, while larger aftershocks (M ≥ 6) were concentrated within the first year. Magnitude–time distributions confirmed that the seismic system transitioned from a background state to a crisis state, reflecting stress redistribution along the subduction interface. The combined pre- and post-seismic analysis underscores the role of long-term monitoring and statistical evaluation of seismicity in subduction zones for hazard assessment. The Tohoku-Oki event highlights both the potential precursory signals in seismic catalogs and the long-lived impact of giant megathrust earthquakes on regional seismicity.

This notebook examines the differing seismic signals of episodic lava fountains from Kilauea’s 2024–2025 summit eruption. By comparing Episodes 1, 26, and 30, I identified spectral and seismic indicators of how the eruptive conduit developed and how this influenced the intensity of the fountains produced. Differing seismic energy distribution and depth patterns inform about magma transport pathways, which can help us predict eruptive behavior.

This notebook examines the differing seismic signals of episodic lava fountains from Kilauea’s 2024–2025 summit eruption. By comparing Episodes 1, 26, and 30, I identified spectral and seismic indicators of how the eruptive conduit developed and how this influenced the intensity of the fountains produced. Differing seismic energy distribution and depth patterns inform about magma transport pathways, which can help us predict eruptive behavior.

In this project, I apply methods acquired during the workshop to analyze microseismicity, including foreshocks, aftershocks, and slow earthquakes, associated with the coseismic rupture. The analysis indicates an increase in seismicity rate about ten days prior to the mainshock, followed by a short-term decrease about three days before rupture. Additionally, aftershocks persisted for nearly two months after the event and expected to continue for some time in the future. Meanwhile, for episodic tremor and slip (ETS), further investigation is required to clarify the activity.

Mount Merapi is one of the most hazardous volcanoes in the world due to its high activity and the dense population living around its slopes, particularly in the Yogyakarta region. Its eruptions present serious threats such as pyroclastic flows, ashfall, and lahars, making it important to monitor and understand its seismic activity. This study focuses on the volcanic event of March 27, 2014, with the aim of analyzing tremor activity linked to the eruption. The Real-time Seismic Amplitude Measurement (RSAM) method was applied to identify the event, followed by spectral analysis using a 10-minute window before the eruption. The results reveal two main frequency peaks, ranging from 2–3 Hz and 14–18 Hz, which characterize the pre-eruption tremor. These spectral features suggest a close relationship between tremor signals and eruption dynamics. The findings highlight that frequency content analysis, combined with amplitude monitoring, can provide valuable insight into the behavior of volcanic tremors and contribute to better understanding of volcanic activity at Mount Merapi.

This study analyzes one month of aftershocks following the 2015 Gorkha Earthquake and compares observed counts with Omori’s law predictions. Regression analysis yielded a best-fit line with slope 1.870, intercept –16.123, and R² = 0.809, showing strong correlation. Results validate Omori’s law for modeling aftershock decay and provide insight into seismic hazard assessment in the region.

On July 16, 2025 a magnitude 7.3 earthquake struck offshore in the Alaska Peninsula "Shumagin Gap" region, the latest in a series of earthquakes magnitude 7 or greater. An image of the Aleutian subduction zone has been commonly used in introductory physical geology textbooks as an example of the concept of a seismic gap, so theoretically, one would expect a large earthquake in "Shumagin Gap" would close the gap, resetting the stress regime. Instead there have been several large earthquakes since the 2020 theoretical 'reset' quake.

On 13 September 2025, 10:37 (UTC+8), there is a moment magnitude 7.4 earthquake occurred near the east coast of Kamchatka, Russia. The approximation location is [53.21N, 160.05E] with a focal depth of 10 km according to the Hong Kong Observatory (HKO) measurement. Meanwhile, regarding the map offered by HKO, there are several foreshocks and aftershocks before and after the main earthquake. Meanwhile, there is one more magnitude 7.8 earthquake right after 5 days for the first large magnitude earthquake. As Kamchatka is near the Ring of Fire, aka which is quite active in seismic activities & Volcanoes, I would like to investigate it.

On 13 September 2025, 10:37 (UTC+8), there is a moment magnitude 7.4 earthquake occurred near the east coast of Kamchatka, Russia. The approximation location is [53.21N, 160.05E] with a focal depth of 10 km according to the Hong Kong Observatory (HKO) measurement. Meanwhile, regarding the map offered by HKO, there are several foreshocks and aftershocks before and after the main earthquake. Meanwhile, there is one more magnitude 7.8 earthquake right after 5 days for the first large magnitude earthquake. As Kamchatka is near the Ring of Fire, aka which is quite active in seismic activities & Volcanoes, I would like to further investigate it.

The notebook explores the Dec 26, 2004 mag 9.2 earthquake and its aftershocks in the Indian Ocean for a period from August 2004-March 2005. This earthquake is the most devastating earthquake of the 21st century. According to studies, the earthquake was caused by fault movement along the subduction zone where the Indian plate is subducting under the Burma plate. The notebook plots show that aftershocks continued for three months after the main earthquake.

Iran is situated along one of the most seismically active regions in the world, where the Arabian tectonic plate converges with the Eurasian plate. This ongoing collision has shaped Iran’s complex geology, producing numerous faults and seismic zones, particularly in regions such as the Zagros Mountains and Alborz ranges. As a result, Iran experiences frequent and sometimes devastating earthquakes, impacting millions of people and critical infrastructure. In addition to natural tectonic forces, anthropogenic activities like reservoir impoundment and mining have also been linked to induced seismicity in parts of Iran. Understanding the patterns of earthquake occurrence — spatially, temporally, and in terms of magnitude — is vital for seismic hazard assessment and risk mitigation efforts. Iran’s unique tectonic setting leads to a wide range of earthquake characteristics, from shallow crustal events to deeper seismicity, with magnitudes varying from small microearthquakes to major destructive events exceeding magnitude 7. This diversity necessitates detailed monitoring and analysis to unravel seismic source behavior and improve forecasting models. In this analysis, we explore the earthquake data recorded in Iran from 2010 through 2025. Using comprehensive earthquake catalogs compiled from national and international sources, we investigate the distribution of events, their magnitudes, and temporal trends. By combining spatial plotting, density mapping, and magnitude-frequency statistics, we aim to identify seismic clusters, fault zone activity, and temporal variations in earthquake occurrence. The study also examines correlations between seismicity and geological structures, as well as the implications of observed trends for earthquake hazard assessment. By better understanding these seismic patterns, we hope to support efforts to enhance earthquake preparedness, inform urban planning, and reduce risk to vulnerable communities. This work demonstrates how modern data visualization and analysis techniques can provide meaningful insights into complex tectonic regions such as Iran, where seismic hazard remains a critical public safety concern.

Iran lies in a highly seismic region where the Arabian and Eurasian plates collide, creating numerous faults, particularly in the Zagros and Alborz mountains. This tectonic activity causes frequent earthquakes, ranging from minor tremors to destructive events over magnitude 7. From 2010–2025, earthquake data analysis reveals spatial clusters, magnitude-frequency trends, and temporal variations. Understanding these patterns is crucial for hazard assessment, preparedness, and reducing risks to communities.

Site effects constitute the entire range of phenomena that affect the seismic waves arriving in a site. These include the amplifications of the seismic energies and their corresponding ground shaking. Considering that these can lead to aggravated impacts and damages, the site response is critical to study in the context of earthquake hazards and disaster risk mitigation. One way seismic waves are amplified is through their interaction with the topography. Topographic amplification can occur when earthquake energies are focused into particular landforms. On the other hand, material amplification occurs when seismic waves resonate at the fundamental frequencies of the rocks and soils in an area. Contrasts between adjacent geologic units can also lead to the amplification of passing waves. Scripts implemented using jupyter notebooks were created to investigate and gain insights into the site response. Seismic inventories, catalogs, and waveforms were requested and processed using workflows taught in the Seismology Skill Building Workshop 2025, which were used to enable the procedures in the investigation. The Augustine Island in Alaska was chosen as the study area to utilize the earthquake records from the monitoring stations of the Alaska Volcano Observatory present on different parts of the terrain. Another consideration in the study area is the presence of seismicities in the region related to the convergence of the Pacific and North American plates. Analysis of seismic records of one of the moderate-sized aftershocks of the 2016 Iniskin (Southern Alaska) Earthquake suggests that the site response was dominated by the amplification related to the volcanic materials in the island compared to the terrain.

Code Overview: This notebook demonstrates seismic data acquisition and analysis using ObsPy and Cartopy. Focusing on IU.ANMO (USA), it shows waveform retrieval, filtering, spectrograms, and mapping. The same workflow applies to any global station (e.g., GE.MORC in Morocco, II.KONO in Norway, IU.TIXI in Siberia), supporting applications in earthquake monitoring, volcanic tremor studies, and nuclear test discrimination. Key Commands and Functions: Client("IRIS") Connects to the IRIS FDSN service to access global seismic data. get_waveforms(network, station, location, channel, start, end) Downloads waveform data for the specified station and channel within a time window. st.merge(method=1, fill_value="interpolate") Merges multiple segments into a continuous trace, filling gaps if necessary. st.filter("lowpass", freq=...) / st.filter("highpass", freq=...) Applies frequency filters to isolate long-period or high-frequency energy. tr.spectrogram(...) Generates a spectrogram (time–frequency representation) to examine spectral content. Cartopy mapping (ax.plot, ax.set_extent) Creates geographic maps, plotting seismic station locations and contextual features. Applications in Seismology: Event discrimination → distinguishing nuclear tests, earthquakes, and collapses. Earthquake seismology → analyzing local, regional, and teleseismic phases. Volcanology → filtering to highlight volcanic tremor (long-period vs high-frequency). Engineering seismology → bandpass filtering for ground motion studies. Education → introducing waveform handling, spectral analysis, and mapping.

Code Overview: This notebook demonstrates seismic data acquisition and analysis using ObsPy and Cartopy. Focusing on IU.ANMO (USA), it shows waveform retrieval, filtering, spectrograms, and mapping. The same workflow applies to any global station (e.g., GE.MORC in Morocco, II.KONO in Norway, IU.TIXI in Siberia), supporting applications in earthquake monitoring, volcanic tremor studies, and nuclear test discrimination. ???? Key Commands and Functions Client("IRIS") Connects to the IRIS FDSN service to access global seismic data. get_waveforms(network, station, location, channel, start, end) Downloads waveform data for specified station and channel within a time window. st.merge(method=1, fill_value="interpolate") Merges multiple segments into a continuous trace, filling gaps if necessary. st.filter("lowpass", freq=...) / st.filter("highpass", freq=...) Applies frequency filters to isolate long-period or high-frequency energy. tr.spectrogram(...) Generates a spectrogram (time–frequency representation) to examine spectral content. Cartopy mapping (ax.plot, ax.set_extent) Creates geographic maps, plotting seismic station locations and contextual features. ???? Applications in Seismology Event discrimination → distinguishing nuclear tests, earthquakes, and collapses. Earthquake seismology → analyzing local, regional, and teleseismic phases. Volcanology → filtering to highlight volcanic tremor (long-period vs high-frequency). Engineering seismology → bandpass filtering for ground motion studies. Education → introducing waveform handling, spectral analysis, and mapping. *Since I could not upload my original final project, I was required to elaborate something simpler, which I find very unfortunate.

A regional seismic catalogue was analysed to identify patterns of spatial, temporal and energetic occurrence of recorded earthquakes. This type of analysis is fundamental in seismology to evaluate tectonic activity, validate instrumental catalogues and establish zones with greater rupture potential. Pandas was used to load the CSV file and convert the date column into datetime objects. Data were grouped by year, month and faults using `groupby()`. For histograms `seaborn.histplot()` was used and for bar charts `matplotlib.pyplot.bar()` was used. The relationship between magnitude and depth was visualised with `scatterplot()`. Finally, epicentre maps were produced with PyGMT, a professional geoscience tool, ideal for representing complex spatial phenomena.

This Jupyter notebook attempts to highlight the Orkney 5.5 Magnitude Earthquake in South Africa caused by a collapsed gold mine, showing constant seismic activity over the years leading to the mine collapse and eventual earthquake.

This Jupyter notebook attempts to highlight the Orkney 5.5 Magnitude Earthquake in South Africa caused by a collapsed gold mine, showing constant seismic activity over the years leading to the mine collapse and eventual earthquake.

Georgia seismicity (1990-2025) is analyzed via FDSN catalogs: maps, depth structure, temporal rates, and FMD (Mc, b-value). A focused case study of the 2009-09-07 Oni (Racha) M~6 event examines a 30-day aftershock window and mainshock waveforms (response removal, 0.1-5 Hz filter, spectra, spectrograms). Results are interpreted in the context of Caucasus tectonics, with conclusions and open questions.

On October 27, 2012, a magnitude 7.8 thrust earthquake struck off the west coast of Haida Gwaii, British Columbia, Canada, marking the second-largest seismic event in Canadian history, after the 1949 Queen Charlotte Islands earthquake. This notebook presents an analysis of the regional seismicity surrounding the Haida Gwaii earthquake and examines the mainshock's seismic characteristics through waveform and spectral analysis. Using earthquake catalog data retrieved from the Incorporated Research Institutions for Seismology (IRIS) database, I analyzed 50 years of seismic activity (1970-2022) within a 200-kilometer radius of the epicenter. The catalog search, filtered for events with a minimum magnitude of 3.0, yielded 1,874 earthquakes that reveal tectonic activity in the region. Temporal analysis of magnitude distribution shows frequent moderate-magnitude events (M 4-6) characteristic of the Queen Charlotte Fault zone, with the 2012 event distinctly visible as the largest in the regional record. Depth distribution analysis confirms that most earthquakes occur at shallow depths of less than 30 kilometers, consistent with the strike-slip tectonic regime of the Queen Charlotte Fault system. Detailed examination of the mainshock utilized seismogram data from nearby stations to characterize the earthquake's seismic signature. Waveform analysis captured the primary arrivals and extended energy release of the event. Spectrogram analysis revealed that the strongest seismic energy was concentrated in the low-frequency range between 0.1 Hz and 10 Hz, with dominant energy lasting approximately 50 seconds. This low-frequency energy concentration is typical of large subduction-zone earthquakes and explains the event's tsunami-generating potential, which triggered warnings extending as far as Hawaii. To isolate and emphasize the long-period seismic energy characteristic of thrust earthquakes, a bandpass filter (0.01-1.0 Hz) was applied to the waveform data. The filtered seismogram effectively removed high-frequency noise and highlighted the smooth, low-frequency content diagnostic of large tectonic ruptures. This frequency signature is consistent with thrust/subduction earthquakes and confirms the event's capacity for tsunami generation through ocean floor displacement. Despite its significant magnitude, the 2012 Haida Gwaii earthquake caused only minor local damage and, remarkably, no fatalities. This outcome reflects the remote offshore location of the epicenter and the relatively sparse population density of the region. The combination of regional seismicity patterns, mainshock waveform characteristics, and spectral analysis provides valuable insights into the seismotectonic framework of the Queen Charlotte Fault system and demonstrates the importance of continued seismic monitoring in this active plate boundary zone. This analysis contributes to understanding large earthquakes in Canadian waters and emphasizes the relationship between earthquake frequency content and tsunami hazard assessment.

On October 27, 2012, a magnitude 7.8 thrust earthquake struck off the west coast of Haida Gwaii, British Columbia, Canada, marking the second-largest seismic event in Canadian history, after the 1949 Queen Charlotte Islands earthquake. This notebook presents an analysis of the regional seismicity surrounding the Haida Gwaii earthquake and examines the mainshock's seismic characteristics through waveform and spectral analysis. Using earthquake catalog data retrieved from the Incorporated Research Institutions for Seismology (IRIS) database, I analyzed 50 years of seismic activity (1970-2022) within a 200-kilometer radius of the epicenter. The catalog search, filtered for events with a minimum magnitude of 3.0, yielded 1,874 earthquakes that reveal tectonic activity in the region. Temporal analysis of magnitude distribution shows frequent moderate-magnitude events (M 4-6) characteristic of the Queen Charlotte Fault zone, with the 2012 event distinctly visible as the largest in the regional record. Depth distribution analysis confirms that most earthquakes occur at shallow depths of less than 30 kilometers, consistent with the strike-slip tectonic regime of the Queen Charlotte Fault system. Detailed examination of the mainshock utilized seismogram data from nearby stations to characterize the earthquake's seismic signature. Waveform analysis captured the primary arrivals and extended energy release of the event. Spectrogram analysis revealed that the strongest seismic energy was concentrated in the low-frequency range between 0.1 Hz and 10 Hz, with dominant energy lasting approximately 50 seconds. This low-frequency energy concentration is typical of large subduction-zone earthquakes and explains the event's tsunami-generating potential, which triggered warnings extending as far as Hawaii. To isolate and emphasize the long-period seismic energy characteristic of thrust earthquakes, a bandpass filter (0.01-1.0 Hz) was applied to the waveform data. The filtered seismogram effectively removed high-frequency noise and highlighted the smooth, low-frequency content diagnostic of large tectonic ruptures. This frequency signature is consistent with thrust/subduction earthquakes and confirms the event's capacity for tsunami generation through ocean floor displacement. Despite its significant magnitude, the 2012 Haida Gwaii earthquake caused only minor local damage and, remarkably, no fatalities. This outcome reflects the remote offshore location of the epicenter and the relatively sparse population density of the region. The combination of regional seismicity patterns, mainshock waveform characteristics, and spectral analysis provides valuable insights into the seismotectonic framework of the Queen Charlotte Fault system and demonstrates the importance of continued seismic monitoring in this active plate boundary zone. This analysis contributes to understanding large earthquakes in Canadian waters and emphasizes the relationship between earthquake frequency content and tsunami hazard assessment.

This project investigates the reservoir-triggered seismicity (RTS) in the globally unique Koyna-Warna region of Maharashtra, India, utilizing seismic data from 1962 onwards. The study employs advanced seismological analysis techniques learned in the SSBW workshop to examine earthquake rate evolution over decades, b-value temporal trends, focal mechanisms, rupture directivity, frequency-magnitude distributions, spectral characteristics, and site amplification effects.

The 2010 earthquake in Haiti was originally primarily associated with the Enriquillo-Plantain Garden Fault system, a major strike-slip fault running through southern Haiti, however after further research, a new unmapped blind thrust fault which was named the Leogane fault was deemed responsible. This introductory investigation aims to assess the seismicity rate before the mainshock and use focal mechanism to identify features of this new fault plane responsible for the 2010 earthquake in Haiti.

A mainshock magnitude 8.0 earthquake happened in the province of sichuan in 2008-05-12 at 14:28:01 and it made a disastrous casualties. The earthquake's epicenter was located 80 kilometres (50 mi) west-northwest of ChengduThe earthquake ruptured the fault for over 240 km (150 mi), with surface displacements of several meters.The earthquake also caused the largest number of geohazards ever recorded, including about 200,000 landslides and more than 800 quake lakes distributed over an area of 110,000 km square. This notebook is done for analysing the recent seismicity at that time to see whether they can predict the earthquake or not. First, data recorded on 2008-05-12 to 2008-05-13 is used to see the trend of earthquake location and find the epicentre of mainshock.Also, the data from Sichuan is missing from Iris so instead the data from Shanghai station SSE is used. We can still see the power of 2008 Sichuan Wenchuan earthquake by seismic graphs and spectrograms.

Our research focuses on the major 2025-01-07 M7.1 Xizang Earthquake in Tibet. The seismically active Qinghai-Tibet Plateau exhibits widespread continental earthquakes characterized by shallow focal depths, complex source mechanisms, and substantial damage potential. This study plots the seismograms recorded across four stations and gives an analysis of the aftershock sequences and focal mechanisms. Spectrograms are used to visualize the frequency content of the seismic waves.

Our research focuses on the major 2025-01-07 M7.1 Xizang Earthquake in Tibet. The seismically active Qinghai-Tibet Plateau exhibits widespread continental earthquakes characterized by shallow focal depths, complex source mechanisms, and substantial damage potential. This study plots the seismograms recorded across four stations and gives an analysis of the aftershock sequences and focal mechanisms. Spectrograms are used to visualize the frequency content of the seismic waves.

I will study the December 5, 2024 M=7.0 offshore interplate earthquake near the Mendocino Triple Junction. After this earthquake, Humboldt Bay, near Eureka California, was observed to run in and out for over 6hrs. Fromm high peak to high peak the period of one-half hour, and an amplitude of high peak to lowest level was of a few feet. I will investigate possible causes of this unusual bay behavior after the quake.

I will study the December 5, 2024 M=7.0 offshore interplate earthquake near the Mendocino Triple Junction. After this earthquake, Humboldt Bay, near Eureka California, was observed to run in and out for over 6hrs, with periods of one-half hour, and an amplitude of a few feet. I will investigate possible causes of this unusual bay behavior of the bay after the quake.

This Jupyter Notebook presents a concise, multi-method analysis of an unprecedented earthquake swarm near Zacatecas, Mexico, utilizing a seismic catalog (2020–Present) and InSAR geodetic data. The study is compelled by a dramatic shift in regional seismicity: the current swarm activity contrasts sharply with the pre-2020 catalog, which registered only 14 historical events. Catalog analysis reveals key patterns: Spatial Concentration: Earthquakes form a distinct cluster to the northwest of Zacatecas. Structural Geometry: Hypocenters delineate a clear ring/circle pattern. Temporal Variation: Events show clustering within specific time ranges. The analysis integrates classical seismology—beginning with the retrieval and plotting of seismograms and spectrograms—with geodetic investigation. We employ ASF OPERA CSLC data to generate an interferogram overlay on a digital map, allowing for the concurrent assessment of subsurface movement (seismicity) and potential surface deformation (InSAR). Tectonically, the swarm is situated in the continental interior between the Sierra Madre Occidental and the Mesa Central, both major volcanic blocks. This reproducible framework is essential for characterizing the mechanisms—likely driven by intraplate stress, fluid, or magmatic processes—that define this sudden and unusual increase in seismic hazard.

**Abstract** For my final Skill Building Workshop project, I set out to explore how seismic P-waves travel through rock and water along paths connecting Tamil Nadu, Sri Lanka, and the II.PALK seismic station. My motivation was twofold: first, to practice integrating seismology and geology data in Python, and second, to investigate whether we could constrain the effective velocity of water by comparing modeled paths to observed arrival times. Understanding these velocities matters because they provide benchmarks for how seismic energy interacts with both crustal formations and ocean basins—information that is essential for both earthquake hazard studies and broader Earth science applications. To carry out the study, I selected II.PALK because of its proximity to two moderate earthquakes (2011 and 2012) and because it provides clear P-wave arrivals. I annotated the process of choosing this station by examining catalogs in the Tamil Nadu–Sri Lanka region, checking for reliable event metadata, and confirming waveform availability. The analysis began with digitized geology maps of Tamil Nadu and Sri Lanka. I collected ground control points (GCPs) by clicking recognizable features and pairing them with latitude/longitude coordinates, then fit affine transforms to georeference the images. With maps aligned, I built legend tables by typing in formation names and their RGB colors, and assigned each formation a rough P-wave velocity (Vp) range based on rock type. This created a combined reference of formations, colors, and estimated seismic speeds. Next, I downloaded and analyzed seismograms for the two earthquakes. From these, I measured P-pick offsets (arrival times) using ObsPy and averaged them per event. Each great-circle wavepath from the earthquakes to II.PALK was then partitioned into segments by overlaying them on the georeferenced geology maps. Every segment was labeled with either a formation or “Water,” and its length was computed using geodesic spacing at ~250 m resolution. I then compared observed travel times to modeled ones. Non-water segments were assigned times based on their estimated Vp ranges, while the long water leg was left as the unknown. Solving for water speed yielded estimates that were checked against whole-path averages. Diagnostics flagged cases where observed picks were shorter than even the fastest possible rock paths, suggesting timing uncertainties or misclassified lengths. The final results were saved in compact CSV reports with stable and timestamped filenames. These included per-event summaries of path lengths, chosen water segments, ignored unknowns, known-time brackets, and the derived water velocities. Visual outputs—plots of GCPs, map overlays, path partitions, and per-label time breakdowns—helped justify interpretations. Through this project I learned how to stitch together multiple data types—maps, seismograms, and earthquake catalogs—into a single workflow. The main outcome was not just a number for the velocity of water, but a demonstration of how image processing, geospatial transforms, waveform analysis, and geophysical reasoning can be combined in a reproducible Jupyter Notebook. Future work could refine the velocity ranges, improve map digitization, and extend the analysis to additional stations or events.

The railway trunks between Saarbrücken and Mannheim run through the village of Scheidt(Saar). The trunks are used at night time by frightliners to transport goods between these two industrial areas. The valleys in the area are narrow, and the railway trunks are typically directly next to private houses. I grew up in this area, first living in the valley in Scheidt, where the nightly noise and vibrations are a distinct feature of the village, and later up the hill on the Scheidterberg, which is more distant from the trunks, and much quieter. Recently I placed my Raspberry Shake & Boom with identity RD773 at my childhood house on the Scheidterberg. This device features a vertical geophone, and an infrasound sensor. Several hundred meters away from the trunks, seismic signals lasting several minutes are seen by the sensors at night time. Nightly noise affects the sleep of the people living in the village. Because of its impact on health, the noise emissions are regulated, and controlled by the authorities. A rail noise map of the area can be seen in the Lärmkarte of the Eisenbahnbundesamt at https://www.eba.bund.de/download/laermkartierung/DINA3_LKZ_Lnight_6811.pdf. We will familiarize with the location, and then search for seismic stations in order to investigate if the moving freightliners can explain these nightly seismic noise singals, and if they leave an infrasound signal at the distance.

The Thwaites glacier is located in Antarctica, and is one of the largest on this continent. The glacier receives high attention in understanding the effects of global warming because it has been identified as having a blocking effect on the ice flowing from the Antarctic continent into the sea. If the Thwaites glacier collapsed, then large masses of ice can flow easier into the sea, leading to rising sea levels, and a positive albedo feed-back loop (https://en.wikipedia.org/wiki/Thwaites_Glacier). For this risk it has earned its nickname "Doomsday Glacier". We are interested if a geological earth quake triggers seismic activity in the ice. If so, an earthquake could become the final trigger to make a destabilized glacier to finally collapse.

Kherson is located in the Oblast Kherson, on the north side of the Dnieper river. At time of writing, the city is on the Ukrainian side of the front line between Russian attackers and Ukrainian defenders. A large part of the population has fled the city, because a safe life no longer is possible due to Russian sheltering from south of the river. We investigate the seismic and infrasound noise in the city.

The Mw 7.5 earthquake that struck Palu, Central Sulawesi, Indonesia on September 28, 2018, was a catastrophic event that led to significant liquefaction, landslides, and a devastating tsunami, resulting in over 4,300 fatalities. This event is of particular scientific interest due to its complex rupture mechanism, which involved supershear rupture velocity along a strike-slip fault, a phenomenon not typically associated with generating large tsunamis. The motivation for this project is to leverage open-source seismological tools, primarily the Python library ObsPy, to analyze the publicly available seismic data from this event. The goal is to characterize the earthquake sequence and examine its waveform data to better understand the seismotectonic setting and rupture characteristics. To investigate the event, this study first queries the IRIS earthquake catalog for seismicity in the Palu region for the entirety of 2018, focusing on events with a magnitude of 4.0 or greater. The spatial distribution of these earthquakes is then mapped using Cartopy and plotted alongside known fault lines to visualize the relationship between seismic activity and regional tectonics. The analysis reveals a clear alignment of epicenters along the Palu-Koro fault system, confirming its role as the primary source of the sequence. Subsequently, the project focuses on waveform analysis from the GE.TOLI2 station, located near the epicenter. High-quality broadband waveform data for the mainshock is downloaded from the GEOFON data center. Standard waveform processing techniques are applied, including instrument response removal and the application of a bandpass filter (0.5-2.5 Hz), to isolate the frequency band of interest for body waves. The resulting seismograms provide a clear view of the P- and S-wave arrivals and the overall ground motion characteristics. This analysis serves as a foundational exercise in computational seismology, demonstrating a complete workflow from data acquisition and processing to visualization and preliminary interpretation. While the results are consistent with broader scientific findings about the Palu earthquake, they also open avenues for further questions. Future work could involve a more detailed analysis, such as creating a spectrogram to study the frequency content evolution over time, plotting a frequency-magnitude distribution to assess the b-value of the sequence, or performing a cross-sectional analysis to delineate the fault plane at depth. This project successfully showcases the power of open-access data and software in modern seismological research.

The July 29, 2025, magnitude 8.8 earthquake on the Kamchatka Peninsula, Russia, was the largest earthquake in a seismic sequence that began 10 days earlier. The largest earthquakes before the M8.8 mainshock were a M7.4 and 3 M6.6 earthquakes on July 20. The purpose of this notebook is to conduct a spatiotemporal and magnitude-based analysis of the foreshock sequence to categorize it and determine if the sequence exhibited unusual behavior.

This project analyzes the 2025 Kamchatka earthquakes, focusing on two major events: M 8.8 (July 29, 2025) and M 7.8 (September 18, 2025). It evaluates their spatial, temporal, and tectonic relationships, confirming the M 7.8 event as a likely aftershock or triggered event of the M 8.8 mainshock. The study uses USGS data, Gutenberg-Richter law, and Båth’s law to assess seismic activity patterns, including aftershock decay and probability of large events. Python scripts fetch and visualize earthquake data, revealing a 73.85% annual probability of an M≥7.8 event in the region.

Campi Flegrei, located in Pozzuoli, Italy, is Europe's largest active caldera, home to over 360,000 people. Recent seismic activity has involved five earthquakes above magnitude 4.0. Along with the uplift phase that began in 2005, this has raised concerns about the potential reactivation of the volcano. This notebook aims to analyze strong motion in the active onshore area of the caldera to gather more information about the subsurface conditions and the earthquakes' impact on residents.

On 22 January 2024, a strong earthquake struck Central Asia, causing significant shaking in Almaty, Kazakhstan. In this project, I analyze waveform data from regional seismic stations using ObsPy. I explore signal characteristics, arrival times, frequency content, and source parameters to better understand the event and its regional impact.

On 22 January 2024, a strong earthquake struck Central Asia, causing significant shaking in Almaty, Kazakhstan. In this project, I analyze waveform data from regional seismic stations using ObsPy. I explore signal characteristics, arrival times, frequency content, and source parameters to better understand the event and its regional impact.