Detailed mapping and granulometric analyses of the 1992 Cerro Negro tephra blanket reveal remarkable departures from the expected distribution of tephra. Isomass maps show that the major axis of dispersion for the eruption was to the SW of the cone and that the coarser-grained particles, ranging from -4.0 -- 1.0 f, were deposited primarily along the major axis of dispersion with deposits thinning off of the axis. Comparable isomass maps for finer-grained particles, 1.5 - 3.5 f, show that these particles were primarily deposited along the edges of the deposit, off of the major axis of dispersion. Advection-diffusion models for tephra fallout currently widely used in volcanology do not account for this deposition pattern. Rather, it appears that interaction between the wind field, which developed a strong cross flow during the eruption, and the ascending tephra plume resulted in the formation of turbulent structure in the plume. Particles with a settling velocity greater than ~1-2m/s (diameter >0.5 mm) were able to overcome the turbulent structure and settled in a manner predicted by the advection-diffusion equation. Those with lower settling velocities were caught up in turbulent structure and deposited off of the major axis of dispersion, near the edges of the overall tephra blanket. Thus, this data set provides the first estimate of the strength of such turbulent structures in advecting plumes, and illustrates the limitations of the typical advection-diffusion models in describing some transport processes.

How people pereceive the risks associated with natural hazards contributes to their willingness to take protective action. Such action may be constrained by prevailing socio-economic and place-specific conditions that restrict or inform the choice of protective measures available to the individual. Vulnerability to the impacts of extreme geophysical events increases when the range of alternatives is limited or misinformed. Many evacuees from a potentially violent volcanic eruption in Ecuador returned to their home town of Banos while it was still under an evacuation order in 2000 and considered to be a high risk area by officials. The research examined four main questions: (1) What economic conditions confronted Baños evacuees? (2) What political or other social events occurred while they were evacuated that limited their perceived range of options? (3) What information was available about prior eruptions of the volcano and other local natural hazards? and (4) What were the characteristics of the economic base of Baños? These questions were investigated using data from interviews with evacuees, government and non-governmental officials, census and other statistical information, scholarly texts and newspaper reports. The research suggests that economic conditions made it extremely difficult for people to relocate to other communities. When a violent eruption did not occur immediately, and few direct impacts of the eruptions were experienced in Baños, many people chose to return home in an effort to reestablish themselves economically. These people perceived the volcano hazard in Baños to be far less threatening than the economic destitution associated with evacuation. This perception may have been influenced by factors other than the socio-economic context, including efforts of political leaders and tourist business owners to effect the town's economic recovery. These efforts included an aggressive publicity campaign that minimized the risk posed by the volcano. Besides encouraging tourists to return, the campaign also encouraged evacuees to do so. Finally, among some residents, religious beliefs may have contributed to perceptions that they would not be harmed in the event of an explosive eruption.

Les îles du bassin caribéen figurent parmi les territoires dans le monde ayant la particularité d’être exposés à tous les types de risque naturel à l’exception du risque d’avalanche. Pourtant, le bilan global quant à leur prise en compte effective reste peu satisfaisant : En effet on constate des lacunes tant au niveau de l’information des populations qu’au niveau des moyens « administratifs et techniques » de réponse au risque. Le risque volcanique en particulier, bien que concernant onze territoires dans les petites Antilles, est relativement « éclipsé » par les autres risques dans les agendas gouvernementaux. Or, les « poudrières » de la Caraïbe sont pour la plupart actives. De plus, du fait de leur exiguïté et de la concentration de populations et d’infrastructures aux abords des volcans ; les territoires insulaires ont une vulnérabilité accrue. Des manifestations violentes peuvent entraîner, comme l’ont montré les cas de la Montagne Pelée en Martinique (1902) et plus récemment celui de la Soufrière Hills à Montserrat (1995 à nos jours), un bilan humain particulièrement lourd. Surtout, même en tempérant le risque de perte de vies humaines grâce à la prévision, une crise volcanique majeure reste synonyme de désastre économique. Le caractère exceptionnel des manifestations volcaniques suffit-il à expliquer ce bilan ? Cette interrogation première nous amène à questionner les mécanismes caractérisant la gestion du risque volcanique dans les Caraïbes insulaires. Notre étude porte ainsi sur les deux crises qui ont été les plus débattues en matière de retour d’expérience : celle de la Soufrière de Guadeloupe en 1976 et celle de la Soufrière Hills de Montserrat, qui a connu son pic en 1997. La comparaison des politiques publiques de gestion des crises étudiées nous permet d’identifier les facteurs orientant la stratégie des autorités compétentes en amont et en aval des crises. / The islands of the Caribbean basin are among the territories in the world having the distinction of being exposed to all types of natural hazard except avalanche risk. However, the overall assessment of their effective consideration remains unsatisfactory: Indeed, there are gaps in both the information of the population and the level of "administrative and technical" means of response to risk. Volcanic risk in particular, although affecting eleven territories in the Lesser Antilles, is relatively "overshadowed" by other risks in government agendas. However, the "powder keg" of the Caribbean are mostly active. Moreover, because of their small size and the concentration of populations and infrastructures around volcanoes; island territories have increased vulnerability. Violent demonstrations can lead, as has been shown in the cases of Mount Pelee in Martinique (1902) and more recently that of the Soufrière Hills in Montserrat (1995 to the present day), a particularly heavy human toll. Above all, even with the risk of loss of life due to the forecast, a major volcanic crisis is synonymous with economic disaster.Is the exceptional character of volcanic events enough to explain this assessment? This first interrogation leads us to question the mechanisms characterizing the volcanic risk management in the insular Caribbean.Our study thus focuses on the two crises that have been the most debated in terms of feedback: that of Soufrière Guadeloupe in 1976 and that of Soufrière Hills Montserrat, which peaked in 1997. The comparison of public crisis management policies studied allows us to identify the factors guiding the strategy of the competent authorities upstream and downstream of crises.

The purpose of this research is to better understand how residents of communities located on the flanks of Kilauea, Hawai'i view the hazards associated with volcanic events taking into account hazard proximity, cultural beliefs, municipal trust, and evacuation planning. The study was conducted in the lower Puna district, an area with a rapidly growing population but limited infrastructure. Data were collected though a questionnaire survey undertaken at venues throughout the district, including grocery markets, bakeries, farmers markets, the public pool, and other gathering places. Overall, the results indicated that people understand the natural hazards of the place but are generally not concerned about the potential impacts of these hazards on their livelihoods; few could determine whether or not they lived in a lava zone, the impacts on health, and the need for evacuation planning. Cultural considerations appear to play major role and many residents believe that Madam Pele, Goddess of Fire, has a stake in the events of Kilauea. Both hazard understanding and cultural belief systems varied by gender, age, income, and education. When compared to findings from earlier studies within the lower Puna district, it was noted that opinions have shifted over time and that belief in Pele had strengthened. This study demonstrated that understanding the opinions and patterns of belief within communities must be ongoing and municipal planning must be altered over time to accommodate evolving needs and beliefs of a community to obtain optimum community support.

Andesitic volcanoes are notorious for their rapid and unpredictable changes in eruptive style between and during volcanic events, a feature normally attributed to shallow crustal and intra-edifice magmatic processes. Using the example of eruptions during the last 1000 yrs at Mt. Taranaki (the Maero Eruptive Period), deposit sequences were studied to (1) understand lava dome formation and destruction, (2) interpret the causes of rapid shifts from extrusive to explosive eruption styles, and (3) to build a model of crustal magmatic processes that impact on eruption style. A new detailed reconstruction of this period identifies at least 10 eruptive episodes characterised by extrusive, lava dome- and lava flow-producing events and one sub- Plinian eruption. To achieve this, a new evaluation procedure was developed to purge glass datasets of contaminated mineral-glass analyses by using compositional diagrams of mineral incompatible-compatible elements. Along with careful examination of particle textures, this procedure can be broadly applied to build a higher degree of resolution in any tephrostratigraphic record. Geochemical contrasts show that the products of the latest Mt. Taranaki eruption, the remnant summit dome (Pyramid Dome) was not formed during the Tahurangi eruptive episode but extruded post-AD1755. Its inferred original maximum volume of 4.9×106 m3 (DRE) was formed by simultaneous endogenous and exogenous dome growth within days. Magma ascent and extrusion rates are estimated at =0.012 ms-1 and =6 m3s-1, respectively, based on hornblende textures. Some of the Maero-Period dome effusions were preceded by a vent-clearing phase producing layers of scattered lithic lapilli around the edifice [Newall Ash (a), Mangahume Lapilli, Pyramid Lapilli]. The type of dome failure controlled successive eruptive phases in most instances. The destruction of a pressurised dome either caused instantaneous but short-lived magmatic fragmentation (Newall and Puniho episodes), or triggered a directed blast-explosion (Newall episode), or initiated sustained magmatic fragmentation (Burrell Episode). The transition from dome effusion to a sustained, sub- Plinian eruption during the Burrell Lapilli (AD1655) episode was caused by unroofing a conduit of stalled magma, vertically segregated into three layers with different degrees of vesiculation and crystallisation. The resultant ejecta range from brown, grey and black coloured vesicular clasts to dense grey lithics. Bulk compositional variation of erupted clasts can be modelled by fractionation of hornblende, plagioclase, clinopyroxene, and Fe-Ti oxides. Pre-eruption magma ascent for the Maero Period events is assumed to begin at depths of c.9.5 km.

Graduation date: 2002 / Best scan available for black and white figures.

The Altiplano-Puna Volcanic Complex in the Central Andes is one of the youngest large silicic volcanic fields (LSVFs) in the world, erupting over 13,000 km³ of material during multiple supereruptions from 11 to 1 Ma. Understanding the timescales over which magma is stored in the crust prior to eruption is crucial to understanding the development of LSVFs such as the APVC. The residence time of a magma is defined as the time between magma formation and its eruption. While the eruption age of a volcanic system is generally well constrained through ⁴⁰Ar/³⁹Ar dating of sanidine and biotite crystals, determining the time of magma formation offers a bigger challenge. U-Pb dating of zircon—an early crystallizing, ubiquitous phase in silicic systems—is a commonly used method for determining the timing of magma formation. U-Pb zircon ages were collected for 16 ignimbrites representing the temporal and spatial distribution of the APVC. Zircon crystallization histories show significant overlap between eruptive centers of similar age separated by as much as 200 km. Ignimbrites erupted from the same multicyclic caldera show little relationship. This suggests that ignimbrites may share a deeper, regional source. Timescales of zircon crystallization for individual ignimbrites range from ~400 ka to more than 1 Ma, with little correlation with age or erupted volume. Ignimbrites with longer crystallization timescales frequently exhibit a stepped age distribution and highly variable U contents, suggesting that these ignimbrites likely formed in a very crystalline, low melt fraction environment while ignimbrites with short crystallization times and constrained U concentrations crystallized in high melt fraction systems. Zircon crystallization histories record periods of continuous zircon crystallization in the APVC that extend over 1.5-2 Ma pulses and correlate well with eruptive pulses recognized by previous studies. Overall, zircon crystallization histories of the magmas feeding ignimbrite eruptions in the APVC record long timescales of magmatic activity from a shared regional source, likely the Altiplano-Puna Magma Body currently detectable underlying the APVC. / Graduation date: 2012

About 7,000 years ago two major tephra-falls blanketed the Pacific Northwest in volcanic ash. These two tephra-falls, identified as the Llao and climatic tephra-falls, were a part of the eruptive events that led up to the collapse of Mount Mazama to form Crater Lake in the southern Oregon Cascades. The tephra-falls occurred about 200 years apart at around 7,000 years B.P. and 6,800 years B.P. for the Llao and climatic eruptions respectively. The effects of the tephra-falls on the flora, fauna, and people of the period have been characterized by different researchers as ranging from minimal to catastrophic. In an attempt to better understand the affects of these two events on the flora, fauna, and people, a model is presented to help organize the various lines of research into a coherent whole and to suggest profitable areas of research which have not yet been completed. The model is based on ecological and anthropological theory with a strong reliance on analogy with modern ecosystems and volcanic hazards research. The model makes use of the ecosystem concept as the framework for the interaction of the abiotic, or nonliving habitat, with the biotic, or living system. The biotic organisms are adapted to the characteristics of the abiotic habitat and in many respects the composition, frequencies, and distributions of biotic organisms are determined by their tolorance levels to these characteristics. Tephra-falls act as environmental disturbances which change the abiotic habitat of the ecosystem. Therefore, any changes caused by such a disturbance in the abiotic characteristics that are not optimal or are outside of the tolorance limits of the biotic (flora and fauna) components should cause changes in the composition, distribution, and frequency of organisms within the ecosystem. The changes brought about by the tephra-falls may be described by successional and evolutionary processes through analysis of pollen and faunal remains, population demography as described by mortality profiles, and research into the reaction of specific flora and fauna within adaptational types to the properties of tephra-falls and the tephra as a soil body. The state factors used to describe the abiotic component of the ecosystem are: time, distribution, material properties, climate, and geomorphology. The state factor of time involves the determination of the occurrence in time of the event(s), the duration of the event(s), the season of occurrence of the event(s), and the residence time of tephra in the ecosystem. This state factor is used to define the specific point in time and duration of the effects of the tephra-fall(s) for individual ecosystems. The state factor of distribution describes the aerial extent and thickness of the air-fall deposits. This state factor determines the extent of the initial disturbance. The state factor of climate describes the specific components of rainfall, wind, and temperature which control ecosystem composition and development, and the changes to the climate which may have occurred due to volcanic aerosols associated with the eruption. The state factor of geomorphology describes the location of tephra and nontephra bodies across the landscape and through time as the tephra is reworked by wind, water, and gravity from the initial air-fall positions. The determination of the long term distribution of the tephra is important in determining post-event influences on ecosystems as described by the material properties of the tephra. It is argued that most people were not greatly harmed by the Mazama tephra-fall events themselves, but instead may have been greatly affected by a loss of food resources during and after the events. Changes in food resource availability and exploitation locations due to the tephra-falls may have resulted in changes in both settlement and subsistence activities. Changes in settlement and subsistence activities may be seen in a corresponding change in differential frequencies of functional tool types across space and time. The kind and amount of expected changes in settlement and subsistence systems are linked to distance from the source of the tephra, the stability and compostion of pre-disturbance ecosystems, the types and intensity of resource exploitation, and the amount of variability in subsistence and settlement traits which were available to the sociocultural system. / Graduation date: 1988

Für den Flugverkehr als Teil eines regional und global verdichteten Infrastruktursystems sind Naturgefahren wie Vulkanausbrüche gleichbedeutend mit Risiken. Die Kommunikation von Risiken verläuft im Spannungsfeld von wirtschaftlichen und staatlichen Akteuren einerseits und Medien und Zivilgesellschaft andererseits. Demgegenüber stehen Modelle diskursiver Risikoregulierung als Instrumente öffentlicher Aushandlungsprozesse. Diskutiert werden Einflussfaktoren auf Entscheidungen im Kontext von Risikodiskursen. Dabei wird insbesondere die Funktionslogik der Medien untersucht. Am Beispiel der Aschewolke des Eyjafjallajökull 2010 wird die Phänomenkonstellation von Akteuren und Diskurspositionen illustriert und der Verlauf einer medialen Risikoentwicklung nachgezeichnet.

Aufgrund seiner nahezu kontinuierlichen eruptiven Aktivität zählt der Merapi zu den gefährlichsten Vulkanen der Welt. Der Merapi befindet sich im Zentralteil der dicht bevölkerten Insel Java (Indonesien). Selbst kleinere Ausbrüche des Merapi stellen deswegen eine große Gefahr für die ansässige Bevölkerung in der Umgebung des Vulkans dar. Die am Merapi beobachtete enge Korrelation zwischen seismischer und vulkanischer Aktivität erlaubt es, mit Hilfe der Überwachung der seismischen Aktivität Veränderungen des Aktivitätszustandes des Merapi zu erkennen. Ein System zur automatischen Detektion und Klassifizierung seismischer Ereignisse liefert einen wichtigen Beitrag für die schnelle Analyse der seismischen Aktivität. Im Falle eines bevorstehenden Ausbruchszyklus bedeutet dies ein wichtiges Hilfsmittel für die vor Ort ansässigen Wissenschaftler.<br /> In der vorliegenden Arbeit wird ein Mustererkennungsverfahren verwendet, um die Detektion und Klassifizierung seismischer Signale vulkanischen Urprunges aus den kontinuierlich aufgezeichneten Daten in Echtzeit zu bewerkstelligen. Der hier verwendete A nsatz der hidden Markov Modelle (HMM) wird motiviert durch die große Ähnlichkeit von seismischen Signalen vulkanischen Ursprunges und Sprachaufzeichnungen und den großen Erfolg, den HMM-basierte Erkennungssysteme in der automatischen Spracherkennung erlangt haben. <br /> Für eine erfolgreiche Implementierung eines Mustererkennungssytems ist es notwendig, eine geeignete Parametrisierung der Rohdaten vorzunehmen. Basierend auf den Erfahrungswerten seismologischer Observatorien wird ein Vorgehen zur Parametrisierung des seismischen Wellenfeldes auf Grundlage von robusten Analyseverfahren vorgeschlagen. Die Wellenfeldparameter werden pro Zeitschritt in einen reell-wertigen Mustervektor zusammengefasst. Die aus diesen Mustervektoren gebildete Zeitreihe ist dann Gegenstand des HMM-basierten Erkennungssystems. Um diskrete hidden Markov Modelle (DHMM) verwenden zu können, werden die Mustervektoren durch eine lineare Transformation und nachgeschaltete Vektor Quantisierung in eine diskrete Symbolsequenz überführt. Als Klassifikator kommt eine Maximum-Likelihood Testfunktion zwischen dieser Sequenz und den, in einem überwachten Lernverfahren trainierten, DHMMs zum Einsatz.<br /> Die am Merapi kontinuierlich aufgezeichneten seismischen Daten im Zeitraum vom 01.07. und 05.07.1998 sind besonders für einen Test dieses Klassifikationssystems geeignet. In dieser Zeit zeigte der Merapi einen rapiden Anstieg der Seismizität kurz bevor dem Auftreten zweier Eruptionen am 10.07. und 19.07.1998. Drei der bekannten, vom Vulkanologischen Dienst in Indonesien beschriebenen, seimischen Signalklassen konnten in diesem Zeitraum beobachtet werden. Es handelt sich hierbei um flache vulkanisch-tektonische Beben (VTB, h < 2.5 km), um sogenannte MP-Ereignisse, die in direktem Zusammenhang mit dem Wachstum des aktiven Lavadoms gebracht werden, und um seismische Ereignisse, die durch Gesteinslawinen erzeugt werden (lokaler Name: Guguran).<br /> Die spezielle Geometrie des digitalen seismischen Netzwerkes am Merapi besteht aus einer Kombination von drei Mini-Arrays an den Flanken des Merapi. Für die Parametrisierung des Wellenfeldes werden deswegen seismische Array-Verfahren eingesetzt. Die individuellen Wellenfeld Parameter wurden hinsichtlich ihrer Relevanz für den Klassifikationsprozess detailliert analysiert. Für jede der drei Signalklassen wurde ein Satz von DHMMs trainiert. Zusätzlich wurden als Ausschlussklassen noch zwei Gruppen von Noise-Modellen unterschieden.<br /> Insgesamt konnte mit diesem Ansatz eine Erkennungsrate von 67 % erreicht werden. Im Mittel erzeugte das automatische Klassifizierungssystem 41 Fehlalarme pro Tag und Klasse. Die Güte der Klassifikationsergebnisse zeigt starke Variationen zwischen den individuellen Signalklassen. Flache vulkanisch-tektonische Beben (VTB) zeigen sehr ausgeprägte Wellenfeldeigenschaften und, zumindest im untersuchten Zeitraum, sehr stabile Zeitmuster der individuellen Wellenfeldparameter. Das DHMM-basierte Klassifizierungssystem erlaubte für diesen Ereignistyp nahezu 89% richtige Entscheidungen und erzeugte im Mittel 2 Fehlalarme pro Tag.<br /> Ereignisse der Klassen MP und Guguran sind mit dem automatischen System schwieriger zu erkennen. 64% aller MP-Ereignisse und 74% aller Guguran-Ereignisse wurden korrekt erkannt. Im Mittel kam es bei MP-Ereignissen zu 87 Fehlalarmen und bei Guguran Ereignissen zu 33 Fehlalarmen pro Tag. Eine Vielzahl der Fehlalarme und nicht detektierten Ereignisse entstehen jedoch durch eine Verwechslung dieser beiden Signalklassen im automatischen Erkennnungsprozess. Dieses Ergebnis konnte aufgrund der ähnlichen Wellenfeldeigenschaften beider Signalklassen erklärt werden, deren Ursache vermutlich in den bekannt starken Einflüssen des Mediums entlang des Wellenausbreitungsweges in vulkanischen Gebieten liegen. <br /> Insgesamt ist die Erkennungsleistung des entwickelten automatischen Klassifizierungssystems als sehr vielversprechend einzustufen. Im Gegensatz zu Standardverfahren, bei denen in der Seismologie üblicherweise nur der Startzeitpunkt eines seismischen Ereignisses detektiert wird, werden in dem untersuchten Verfahren seismische Ereignisse in ihrer Gesamtheit erfasst und zudem im selben Schritt bereits klassifiziert. / Merapi volcano is one of the most active and dangerous volcanoes of the earth. Located in central part of Java island (Indonesia), even a moderate eruption of Merapi poses a high risk to the highly populated area. Due to the close relationship between the volcanic unrest and the occurrence of seismic events at Mt. Merapi, the monitoring of Merapi's seismicity plays an important role for recognizing major changes in the volcanic activity. An automatic seismic event detection and classification system, which is capable to characterize the actual seismic activity in near real-time, is an important tool which allows the scientists in charge to take immediate decisions during a volcanic crisis. <br /> In order to accomplish the task of detecting and classifying volcano-seismic signals automatically in the continuous data streams, a pattern recognition approach has been used. It is based on the method of hidden Markov models (HMM), a technique, which has proven to provide high recognition rates at high confidence levels in classification tasks of similar complexity (e.g. speech recognition). Any pattern recognition system relies on the appropriate representation of the input data in order to allow a reasonable class-decision by means of a mathematical test function. Based on the experiences from seismological observatory practice, a parametrization scheme of the seismic waveform data is derived using robust seismological analysis techniques. The wavefield parameters are summarized into a real-valued feature vector per time step. The time series of this feature vector build the basis for the HMM-based classification system. In order to make use of discrete hidden Markov (DHMM) techniques, the feature vectors are further processed by applying a de-correlating and prewhitening transformation and additional vector quantization. The seismic wavefield is finally represented as a discrete symbol sequence with a finite alphabet. This sequence is subject to a maximum likelihood test against the discrete hidden Markov models, learned from a representative set of training sequences for each seismic event type of interest.<br /> A time period from July, 1st to July, 5th, 1998 of rapidly increasing seismic activity prior to the eruptive cycle between July, 10th and July, 19th, 1998 at Merapi volcano is selected for evaluating the performance of this classification approach. Three distinct types of seismic events according to the established classification scheme of the Volcanological Survey of Indonesia (VSI) have been observed during this time period. Shallow volcano-tectonic events VTB (h < 2.5 km), very shallow dome-growth related seismic events MP (h < 1 km) and seismic signals connected to rockfall activity originating from the active lava dome, termed Guguran.<br /> The special configuration of the digital seismic station network at Merapi volcano, a combination of small-aperture array deployments surrounding Merapi's summit region, allows the use of array methods to parametrize the continuously recorded seismic wavefield. The individual signal parameters are analyzed to determine their relevance for the discrimination of seismic event classes. For each of the three observed event types a set of DHMMs has been trained using a selected set of seismic events with varying signal to noise ratios and signal durations. Additionally, two sets of discrete hidden Markov models have been derived for the seismic noise, incorporating the fact, that the wavefield properties of the ambient vibrations differ considerably during working hours and night time. <br /> A total recognition accuracy of 67% is obtained. The mean false alarm (FA) rate can be given by 41 FA/class/day. However, variations in the recognition capabilities for the individual seismic event classes are significant. Shallow volcano-tectonic signals (VTB) show very distinct wavefield properties and (at least in the selected time period) a stable time pattern of wavefield attributes. The DHMM-based classification performs therefore best for VTB-type events, with almost 89% recognition accuracy and 2 FA/day. <br /> Seismic signals of the MP- and Guguran-classes are more difficult to detect and classify. Around 64% of MP-events and 74% of Guguran signals are recognized correctly. The average false alarm rate for MP-events is 87 FA/day, whereas for Guguran signals 33 FA/day are obtained. However, the majority of missed events and false alarms for both MP and Guguran events are due to confusion errors between these two event classes in the recognition process. <br /> The confusion of MP and Guguran events is interpreted as being a consequence of the selected parametrization approach for the continuous seismic data streams. The observed patterns of the analyzed wavefield attributes for MP and Guguran events show a significant amount of similarity, thus providing not sufficient discriminative information for the numerical classification. The similarity of wavefield parameters obtained for seismic events of MP and Guguran type reflect the commonly observed dominance of path effects on the seismic wave propagation in volcanic environments.<br /> The recognition rates obtained for the five-day period of increasing seismicity show, that the presented DHMM-based automatic classification system is a promising approach for the difficult task of classifying volcano-seismic signals. Compared to standard signal detection algorithms, the most significant advantage of the discussed technique is, that the entire seismogram is detected and classified in a single step.