Identification of snow avalanche release areas and flow characterization based on seismic data studies

[eng] The main objectives of this PhD thesis are the identification of the snow avalanche release areas and the snow avalanche flow regime characterization with the use of seismic data. We aim to search for new methods for conducting detailed studies of the seismic signal generated by snow avalanches, considered as a moving seismic source. One of the main bases for achieving these objectives is to use widely tested seismological methods designed for the study of single seismic sources. In order to adapt them to a record of a moving source generating seismic vibrations (snow avalanches), we decided to apply windowing methods to the seismic signal so that the seismic signal could be processed in small portions. Over each time window of the seismic signal, we perform the study of ground particle motion polarization (3D) and obtain the frequency content information (Power Spectral Density). In the seismic signal produced by snow avalanches can be identified sections linked to the relative position of the avalanche front with respect to the position of the seismic sensor. The evolution of the total envelope of the seismic signal (At(t)) allows us to establish a criterion for the identification of the different sections based on the seismic signal amplitude. Furthermore, we are able to identify the moment when the snow avalanche mass starts to move (first vibrations generated by the avalanche) using an appropriate configuration of the STA/LTA algorithm adapted for our purposes. For each of the sections of the seismic signal, we apply a different methodology to obtain different information about the snow avalanche flow in each avalanche part. We seek to identify the snow avalanche release area by analysing the signal produced at the beginning of the snow avalanche mass movement (Signal Onset - SON). The study of the polarization of the ground particle motion (3D, ZNE coordinate system) makes it possible to identify the area where the first vibrations are generated, and by extension link it to the start of the snow avalanche mass movement. By analysing the seismic signal section corresponding to when the snow avalanche mass is flowing over the seismic sensor (Signal Over the sensor - SOV), we characterize the snow avalanche flow and identify the different regions in the snow avalanche body. The seismic signal is rotated to the QLT coordinate system in order to better link the information of the seismic signal to the flow progression direction. Work on this PhD thesis has also enabled us to establish a homogenization of the seismic data processing steps for studying snow avalanches. We automated these processes for all the data acquired in the Vallée de la Sionne test site between winter seasons 2013 and 2020, thereby creating a database consisting of more than 420 seismic events (source: automatic data acquisition system activations at VDLS). From all these events we managed to identify the snow avalanches and to test the procedures designed in this thesis for the release area identification and the flow characterization. Although the designed methods are subject to some limitations, we consider that the contribution to novel approaches for the study of the seismic signal produced by moving sources is proved. The release area identification has a very good success rate (78%) in a supervised application. The automated execution could be improved with a better isolation process for the seismic signal SON section. The method for the flow characterization provides new information regarding the interaction of the flow with the ground and with the snow cover. We consider that future studies in this direction may yield information about the snow avalanche basal friction as an indirect measurement.[cat] En aquesta tesi els objectius principals són la identificació de les zones d’alliberament d’allaus de neu i la caracterització del seu tipus de flux a partir de l’ús de dades sísmiques. Perseguim noves maneres de realitzar una caracterització detallada del senyal sísmic generat per allaus de neu. Ens basem en l’ús de mètodes sismològics àmpliament provats per a l'estudi de fonts sísmiques puntuals. Per tal de poder implementar aquests mètodes al registre sísmic d’una font sísmica en moviment (allaus de neu), utilitzem procediments de tractament del senyal en finestres de temps. En cada finestra del senyal sísmic, realitzem l’estudi de la polarització del moviment de la partícula (3D) i n’obtenim la informació del contingut en freqüències. L’evolució de l’evolvent total del senyal sísmic (At(t)), ens permet establir un criteri per a la identificació de diferents seccions en el senyal, relacionades amb la posició relativa de l’allau respecte el sensor sísmic. També podem identificar l’instant en què s’inicia el moviment de l’allau mitjançant una configuració adequada de l’algorisme STA/LTA. En cadascuna d’aquestes seccions hi apliquem una metodologia diferent per tal d’obtenir informació específica. Amb l'estudi de la polarització del moviment de la partícula sísmica en l’anàlisi del senyal sísmic produït per l’inici del moviment de l’allau de neu (secció SON), és possible identificar l'àrea des d'on es generen les primeres vibracions (78% de taxa d’èxit). Analitzant el senyal sísmic corresponent al pas de l’allau per sobre el sensor sísmic (secció SOV), caracteritzem el tipus de flux i identifiquem les regions en el cos de l’allau a partir de l’evolució del moviment de la partícula sísmica i l’evolució del contingut en freqüències. L'elaboració d'aquesta tesi també ens ha portat a homogeneïtzar i automatitzat els passos en el processament de dades sísmiques per a l’estudi de les allaus, creant una base de dades amb més de 420 esdeveniments sísmics al lloc experimental de Vallée de la Sionne (2013-2020). Tot i que trobem algunes limitacions, considerem que queda demostrada la contribució en nous enfocaments per a l’estudi del senyal sísmic produït per fonts sísmiques en moviment

Classifying seismic waveforms from scratch: a case study in the alpine environment

Nowadays, an increasing amount of seismic data is collected by daily observatory routines. The basic step for successfully analyzing those data is the correct detection of various event types. However, the visually scanning process is a time-consuming task. Applying standard techniques for detection like the STA/LTA trigger still requires the manual control for classification. Here, we present a useful alternative. The incoming data stream is scanned automatically for events of interest. A stochastic classifier, called hidden Markov model, is learned for each class of interest enabling the recognition of highly variable waveforms. In contrast to other automatic techniques as neural networks or support vector machines the algorithm allows to start the classification from scratch as soon as interesting events are identified. Neither the tedious process of collecting training samples nor a time-consuming configuration of the classifier is required. An approach originally introduced for the volcanic task force action allows to learn classifier properties from a single waveform example and some hours of background recording. Besides a reduction of required workload this also enables to detect very rare events. Especially the latter feature provides a milestone point for the use of seismic devices in alpine warning systems. Furthermore, the system offers the opportunity to flag new signal classes that have not been defined before. We demonstrate the application of the classification system using a data set from the Swiss Seismological Survey achieving very high recognition rates. In detail we document all refinements of the classifier providing a step-by-step guide for the fast set up of a well-working classification syste

Extraction of Pertinent Subsets from Time-Frequency Representations for Detection and Recognition Purposes

International audienceA time-frequency representation can highlight non-stationarities in a signal. We propose to extract subsets from the Time-Frequency Representation (TFR) for classification or recognition purposes. We developed two approaches. The first one is developed for TFRs obtained from the Short Time Fourier Transform or the gliding Minimum Variance method. The extraction of compact subsets is viewed as a segmentation of the TFR, which is performed by morphological filtering and Watershed segmentation. The second approach is developed when the TFR has been obtained using parametric estimators. We consider a hybrid estimator, the ARCAP method, and use a Kalman filter trajectory tracker to extract spectral lines. The proposed methods are illustrated by examples on natural signals : dolphin whistle acoustical signals, cavitation signals and seismic signals produced by snow avalanches

Hva kontrollerer kalving av breer? Fra observasjoner til prediksjoner

This thesis addresses the process of iceberg calving at the front of tidewater glaciers and tries to clarify what controls the calving of glaciers, from observations in the field to modeling and predictions. Iceberg calving is the detachment of ice from a parent glacier and it makes the glacier very sensitive to its local environment. In turn, calving at a glacier front has a strong impact on the glacier dynamics and can trigger and/or enhance glacier instabilities, acceleration and glacier retreat, making the calving process a crucial factor in glacier dynamics and hence in sea level rise. This thesis is based on field observations, collected throughout 4 years at the front of Kronebreen, Svalbard. A special emphasis has been given to trying various observation techniques: ground-based RADAR, direct observations, seismic monitoring, terrestrial photogrammetry and remote sensing. Using ground-based RADAR we were able to automatically detect 92% of the largest calving events. The percentage detected by seismic monitoring is lower (about 10%) but the technique allows for finer distinction between different calving types and glacier-related seismic events. Seismic equipment also requires less maintenance, less technical expertise and less funding, and can be left in the field for several months. Terrestrial photogrammetry is a very useful tool that can provide glacier dimensions and a continuous monitoring of the general conditions at the front. Finally, direct observations are recommended for the study of calving because it can provide, when used together with terrestrial photogrammetry, both qualitative and quantitative data. The qualitative aspect provides key information for understanding the calving process but is especially hard to obtain with technical methods. The question of seasonal calving variations is also addressed and we show that glacial seismic activity is highly variable throughout the year with recurrent increased activity in autumn, while velocity is low. However this thesis focuses on explaining very short-term variations: the individual calving events. Individual calving events have received so far very little attention in the field and no attention in modeling studies. This thesis was inspired by other studies of complex natural processes in which individual events are all equally considered, large and small, and which emphasize the value of understanding a process at the individual scale, for example the study of earthquakes or forest fires. We first show that general spatial patterns in calving activity can be explained by glacier characteristics like longitudinal stretching rate, which themselves are very linked to the glacier geometry. We then created a simple calving model with the object of understanding what controls the size and timing of calving events. Our simple model, focussing solely on the interplay between calving and its impact on the front stability, manages to reproduce the size and timing distribution of calving events as observed in the field. This result highlights the role of calving on front stability and on calving itself. Front stability is shown to be crucial in the control of calving. Implications of this new finding are that the size distribution of calving depends on the glacier stability: a glacier becoming unstable will produce a higher proportion of large calving events. Beyond a critical glacier stability, calving can become self-sustained and ongoing, leading to very rapid glacier retreat. We propose that the characteristics of the calving event sizes distribution indicate how close a glacier is to rapid retreat. One main point of this thesis is to show the importance of studying calving events at an individual scale to gain more understanding of the process.Denne avhandlingen omhandler kalvingsprosessen i fronten av en tidevannsbre og den forsøker å klargjøre hva som kontrollerer kalving av breer, ved hjelp av feltobservasjoner, modellering og prediksjon. Kalving av isfjell skjer når is brekker av fra en isbre, og kalving gjør breer svært sensitive til det lokale miljøet. Motsatt har også kalvingen ved brefronten en stor innflytelse på breens dynamikk, kalvingen kan initiere eller forsterke ustabilitet, akselerasjon eller tilbaketrekking av breen, hvilket gjør kalvingsprosessen til en sentral faktor for isdynamikken, og for havnivået. Denne avhandlingen er basert på feltobservasjoner som er samlet gjennom fire år ved fronten av Kronebreen på Svalbard. Det er blitt lagt spesielt vekt på å prøve ut forskjellige observasjonsteknikker, bakkebasert RADAR, direkte observasjoner, seismisk monitorering, terrestrisk fotogrammetri, og fjernanalyse. Ved hjelp av bakkebasert RADAR kunne vi detektere 92% av de storste kalvingsepisodene. Prosentandelen for seismisk monitorering er mye lavere, ca 10%, men denne monitoreringen tillater finere distinksjon av forskjellige kalvingsformer og brerelaterte seismiske episoder. Seismisk utstyr krever også mindre ettersyn, mindre teknisk ekspertise og lavere finansiering, og utstyret kan være utplassert i felt uten tilsyn i flere måneder. Terrestrisk fotogrammetri er et svært nyttig verktøy som kan fortelle om breens dimensjoner og som muliggjør en kontinuerlig monitorering av generelle forhold ved fronten. Tilsutt anbefales direkte observasjoner for å studere kalving, fordi disse i kombinasjon med terrestrisk fotogrammetri kan gi både kvalitative og kvantitative data. Det kvalitative aspektet gir essensiell informasjon for forståelsen av kalvingsprosessen, men er spesielt vanskelig å oppnå ved teknologiske metoder. Spørsmålet om sesongbaserte kalvingsvariasjoner er også undersøkt og vi viser at kalvingsaktiviteten er svært variabel gjennom året, med gjentagende økning i aktivitet på høsten når også hastigheten er på sitt laveste. Allikevel fokuserer denne avhandlingen på å forklare de svart raske variasjonene, nemlig individuelle kalvingshendelser. Så langt har det blitt viet svært lite oppmerksomhet mot individuelle kalvingshendelser i felt, og ingen oppmerksomhet innen modelleringsstudier. Denne avhandlingen er inspirert av studier av komplekse prosesser hvor individuelle hendelser er vurdert likeverdige, store som små, og som vektlegger verdien av å forstå prosessen på en skala på individuelt nivå, for eksempel for studier av jordskjelv. Vi viser først at generelle romlige monstre i kalvingsaktivitet kan forklares ved brekarakteristikker som longitudinell tøynings rate (stretching rate), som igjen er knyttet til breens geometri. Vi har laget en enkel kalvingsmodell hvor intensjonen er å forstå hva som kontrollerer størrelse og tidspunkt for kalvingshendelsen. Vår modell, som fokuserer kun på interaksjon mellom kalving og dennes innflytelse på frontstabiliteten, greier å reprodusere størrelses- og tidsfordeling av kalvingshendelser som observert i felt. Dette resultatet fremhever kalvingens rolle på frontstabiliteten og på kalvingen selv. Det viser seg at frontstabiliteten er en essensiell styringsmekanisme for kalvingen. Konsekvensene av dette nye funnet er at størrelsesfordelingen av kalvingshendelsene avhenger av breens stabilitet; en bre som blir ustabil produserer høyere proporsjon av større kalvingshendelser. Over en kritisk brestabilitet vil kalvingen bli selvopprettholdende og vedvarende, hvilket vil medføre en svart rask tilbaketrekning av brefronten. Vi fremsetter en påstand om at karakteristikken av fordelingen av størrelsene på kalvingshendelsene indikerer hvor nært forestående en rask tilbaketrekning er for breen. Et hovedpoeng ved denne avhandlingen er å vise hvor viktig det er å studere kalvingshendelser på en skala på individuelt nivå for å oppnå en bedre forståelse av prosessen.GLACIODY

Passive seismic investigations for landslide hazard study in rock masses

La valutazione della pericolosità da frana e la gestione del relativo rischio sono sempre stati temi ampiamente studiati nella comunità scientifica data la presenza di insediamenti popolati così come siti turistici e di interesse culturale minacciati da processi di frana. Nell’ultimo decennio, le tecniche geofisiche sono state integrate in approcci multidisciplinari per studiare processi di instabilità gravitativa e progettare sistemi di monitoraggio dedicati alla gestione di infrastrutture. Nella presente tesi di Dottorato di Ricerca, una metodologia sperimentale è stata testata in due casi di ammassi rocciosi coinvolti in fenomeni di frana per valutare quanto gli approcci di sismica passiva possano essere applicati a: i) studiare la suscettibilità da frana e produrre una zonazione della pericolosità da frana; ii) valutare la pericolosità da frana (in termini di probabilità di occorrenza); iii) gestire il rischio da frana. I processi di instabilità gravitativa avvengono a differente scala e in un diverso ambiente naturale nei due casi di studio scelti: i) una falesia rocciosa in ambiente costiero sull’isola di Malta (caso di studio Selmun); ii) un versante roccioso in area montuosa nel Centro Italia (caso di studio Peschiera). La metodologia sperimentale applicata in questa tesi di Dottorato di Ricerca impiega due differenti approcci di sismica passiva: i) analisi di rumore sismico ambientale effettuate con misure a stazione singola; ii) monitoraggio sismometrico operato attraverso sensori in configurazione di array/rete (permanente o temporanea). Il Promontorio di Selmun, situato nella costa Nord-Ovest di Malta (Mar Mediterraneo Centrale), è coinvolto in un processo di frana legato alla successione geologica dell’area: la sovrapposizione di un calcare (roccia rigida) su un’argilla plastica induce un lateral spreading associato a caduta, scivolamento e/o ribaltamento di blocchi rocciosi di varie dimensioni dal bordo della placca di calcare. L’analisi delle misure di rumore sismico ambientale ha permesso di ottenere notevoli risultati riguardo il livello di stabilità delle diverse zone instabili e, quindi, di valutare la loro differente suscettibilità da frana nel quadro di una zonazione di pericolosità da frana. In aggiunta, è stato ottenuto il principale moto proprio di un ampio blocco di roccia instabile ed è stato effettuato nel dominio del tempo uno studio preliminare di specifici parametri di misure di rumore sismico ambientale di lunga durata effettuate in zone stabili e instabili. D’altra parte, l’installazione di un array a geometria SNS ha permesso di individuare e localizzare alcuni eventi microsismici originati dal margine instabile della placca calcarea. Il Versante delle Sorgenti del Peschiera, localizzato nell’Appennino Centrale (Italia Centrale) a circa 70 km a Nord-Est di Roma, è coinvolto in un fenomeno di creep in ammasso roccioso associato ad una dissoluzione carsica profonda. Le misure di rumore sismico ambientale hanno evidenziato la diversa risposta sismica delle varie zone del versante interessato dal complesso processo di frana. Dato che il versante delle Sorgenti del Peschiera ospita un importante impianto di drenaggio di approvvigionamento di acqua per la città di Roma, una rete accelerometrica è stata installata nel 2008 ed un array SNS è stato aggiunto nel 2014. L’array SNS ha registrato centinaia di eventi microsismici originati nel versante e legati al suo processo di instabilità. Tali eventi sono stati distinti in due diversi tipi: i) rotture legate alla fratturazione dell’ammasso roccioso, con durata da 1 a qualche secondo; ii) collassi, con durata minore di 1 s e tipica forma d’onda da impatto. In questa tesi, 397 eventi (16 rotture e 381 collassi) sono stati caratterizzati con il software NanoseismicSuite in termini di magnitudo locale ML ed ipocentro. Mentre le rotture sono risultate distribuite nell’intero versante, i collassi si sono focalizzati in due diversi cluster spaziali sotto il livello di falda, ad una profondità in cui il carsismo produce cavità. I cluster sono stati trattati come due distinte sorgenti microsismogeniche ed una curva frequenza-magnitudo degli eventi è stata prodotta per ognuna, per descrivere l’attitudine a produrre eventi di diverso valore di magnitudo. È stata poi sviluppata una procedura automatizzata di analisi rapida degli eventi registrati della rete accelerometrica. Infine, una matrice di pericolosità da frana è stata implementata per entrambi i casi di studio in base alla frequenza statistica degli eventi occorsi (i valori delle misure di rumore sismico per il caso di studio di Selmun e i valori di ML dei collassi per il caso di studio del Peschiera) e la loro probabilità di eccedenza in un periodo fissato, fornendo un utile contributo nella gestione del relativo rischio da frana. In conclusione, la presente tesi di Dottorato di Ricerca evidenzia come la sismica passiva possa essere considerata un utile strumento per investigare e monitorare processi di instabilità gravitativa dato che ha consentito di raggiungere i diversi obiettivi iniziali: valutare la suscettibilità da frana, stimarne la pericolosità ed, infine, implementare uno strumento che possa contribuire alla gestione del rischio connesso.Assessment of landslide hazard and managing the related risk have always been widely studied topics in the scientific community due to the presence of populated settlements as well as tourist and cultural heritage sites threated by slope instability processes. In the last decade, geophysical techniques have been integrated in multidisciplinary approaches to study gravity-induced slope instability processes as well as to design monitoring systems devoted to infrastructure management. In the here-presented Ph.D. thesis, an experimental methodology was tested in two case studies of rock masses involved in landslide processes for evaluating as passive seismic approaches can be applied to: i) study the landslide susceptibility and produce a landslide hazard zonation; ii) assess the landslide hazard (in terms of probability of occurrence); iii) manage the landslide risk. For the two case studies, the gravity-induced slope instability processes occur at different scale and in a different natural environment: i) one rock cliff slope in coastal environment on the island of Malta (Selmun case study); ii) one rock slope in mountainous area in Central Italy (Peschiera case study). The experimental methodology applied in this work employed two passive seismic approaches: i) seismic ambient noise analysis carried out by single-station measurements; ii) seismic monitoring operated through seismic array/network (permanent or temporary) of sensors. The Selmun Promontory, located in the North Western coast of Malta (Central Mediterranean Sea), is involved in a landslide process due to the geological setting of the area: the over-position of a limestone (i.e. stiff rock) on a plastic clay induces a lateral spreading phenomenon associated to falls, slides and/or topples of different-size rock blocks from the limestone plateau edge. The seismic ambient noise measurement analysis allowed to obtain remarkable outputs in terms of stability level of the several unstable zones and, therefore, to evaluate their different landslide susceptibility in the framework of a landslide hazard zonation. In addition, the main eigenmode frequency of an unstable large rock block was obtained and a preliminary study of specific parameters was carried out in the time domain on long seismic noise measurements carried out in stable and unstable zones. On the other hand, the installation of an array having the SNS geometry allowed to detect and locate few microseismic events produced by the unstable limestone plateau edge. The Peschiera Spring Slope, located in Central Apennines (Central Italy) at about 70 km North East from Rome, is involved in a rock mass creep phenomenon associated to a deep karst dissolution. The seismic ambient noise measurements evidenced the different seismic response of the different zones of the slope involved in the complex landslide process. Since the Peschiera Spring Slope hosts an important drainage plant that provides water to the city of Rome, an accelerometric network was installed in 2008 and a nanoseismic SNS array was added in 2014. The SNS array recorded hundreds of microseismic events originated within the slope and related to its instability process. Such events were distinguished in two different types: i) failures related to rock mass fracturing, with a duration from 1 to few seconds; ii) collapses, with a duration less than 1 s and a typical waveform of impact. In this Ph.D. thesis, 397 events (i.e. 16 failures and 381 collapses) were characterised by NanoseismicSuite software in terms of local magnitude ML and hypocentre. While the failures resulted distributed into the whole slope, the collapses focused in two different spatial clusters below the groundwater level, at a depth in which karst processes produce cavities. The clusters were treated as two distinct microseismic sources and a frequency-magnitude curve of events was produced for each one, for describing the attitude to produce events having different values of magnitude. Then, an automated procedure for quickly analysing events recorded by the accelerometric network was developed. Finally, a landslide hazard matrix was implemented for the both case studies based on the statistic frequency of the occurred events (i.e. values of long seismic noise for the Selmun case study and ML values of collapses for the Peschiera case study) and their probability of exceedance in a fixed period, giving an useful contribution for managing the related landslide risk. In conclusion, the here-presented Ph.D. thesis evidences as passive seismic can be considered as a useful tool for investigating and monitoring gravity-induced slope instability processes since it allows to achieve the different initial objectives, i.e. evaluate the landslide susceptibility, assess its hazard and, finally, implement a tool for contributing to manage the related risk

A Study of Types of Sensors used in Remote Sensing

Of late, the science of Remote Sensing has been gaining a lot of interest and attention due to its wide variety of applications. Remotely sensed data can be used in various fields such as medicine, agriculture, engineering, weather forecasting, military tactics, disaster management etc. only to name a few. This article presents a study of the two categories of sensors namely optical and microwave which are used for remotely sensing the occurrence of disasters such as earthquakes, floods, landslides, avalanches, tropical cyclones and suspicious movements. The remotely sensed data acquired either through satellites or through ground based- synthetic aperture radar systems could be used to avert or mitigate a disaster or to perform a post-disaster analysis

Development and Application of Tools for Avalanche Forecasting, Avalanche Detection, and Snowpack Characterization

Avalanche formation is a complex interaction between the snowpack, weather, and terrain. However, detailed observations typically can only be made at a single point and must be extrapolated over the slope or regional scale. This study aims to provide avalanche forecasters with tools to evaluate the snowpack, avalanche hazard, and avalanche occurrence when manual observations are not feasible. Avalanches that occur within the new storm snow are a prevalent problem for the avalanche forecasters with the Idaho Transportation Department (ITD) along Highway 21. We have implemented a real time SNOw Slope Stability (SNOSS) model that provides an index to the stability of that layer. SNOSS has been run real time starting during the winter of 2011/2012 with model results outputted to a webpage for easy viewing by avalanche forecasters. To further improve the accuracy of SNOSS, the model was evaluated with a large database of avalanches from the Utah Department of Transportation (UDOT). Using weather data and SNOSS results, the probability of an avalanche day producing a natural direct action avalanche was calculated using a Balanced Random Forest (BRF). In the future, we hope that the BRF can provide a probability of an avalanche occurrence given the current weather and snowpack conditions that can be utilized by avalanche forecasters in their normal operations. The concern for avalanche forecasters with highway operations is the threat of an avalanche releasing and hitting a highway. Infrasound generated by an avalanche moving downhill can be detected and tracked using array processing techniques. This will allow avalanche forecasters to evaluate the avalanche hazard more effectively by determining when and where avalanches have occurred. An avalanche detection system has been developed to detect avalanches in near real time using infrasound arrays. The system processes the infrasound data on-site, automatically detects events, and classifies the events using multiple neural networks. If an avalanche has been detected, the system will transmit the necessary information over satellite to be viewed by avalanche forecasters on a webpage

Characterization of geohazards via seismic and acoustic waves

Thesis (Ph.D.) University of Alaska Fairbanks, 2023Earth processes, such as large landslides and volcanic eruptions, occur globally and can be hazardous to life and property. Geophysics -- the quantitative study of Earth processes and properties -- is used to monitor and rapidly respond to these geohazards. In particular, seismoacoustics, which is the joint study of seismic waves in the solid Earth and acoustic waves in Earth's atmosphere, has been proven effective for a variety of geophysical monitoring tasks. Typically, the acoustic waves studied are infrasonic: They have frequencies less than 20 hertz, which is below the threshold of human hearing. In this dissertation, we use seismic and acoustic waves and techniques to characterize geohazards, and we examine the propagation of the waves themselves to better understand how seismoacoustic energy is transformed on its path from a given source to the measurement location. Chapter 1 provides a broad overview of seismoacoustics tailored to this dissertation. In Chapter 2, we use seismic and acoustic waves to reconstruct the dynamics of two very large, and highly similar, ice and rock avalanches occurring in 2016 and 2019 on Iliamna Volcano (Alaska). We determine their trajectories using seismic data from distant stations, demonstrating the feasibility of remote seismic landslide characterization. Chapter 3 details the application of machine learning to a rich volcano infrasound dataset consisting of thousands of explosions recorded at Yasur Volcano (Vanuatu) over six days in 2016. We automatically generate a labeled catalog of infrasound waveforms associated to two different locations in Yasur's summit crater, and use this catalog to test different strategies for transforming the waveforms prior to classification model input. In Chapter 4, we use the coupling of atmospheric waves into the Earth to leverage a dense network of about 900 seismometers around Mount Saint Helens volcano (Washington state) as a quasi-infrasound network. We use buried explosions from a 2014 experiment as sources of infrasound. The dense spatial wavefield measurements permit detailed examination of the effects of wind and topography on infrasound propagation. Finally, in Chapter 5 we conclude with some discussion of future work and additional seismoacoustic topics