@phdthesis{Šustr2020,
  author    = {Šustr, David},
  title     = {Molecular diffusion in polyelectrolyte multilayers},
  doi       = {10.25932/publishup-48903},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-489038},
  school      = {Universit{\"a}t Potsdam},
  pages     = {106},
  year      = {2020},
  abstract  = {Research on novel and advanced biomaterials is an indispensable step towards their applications in desirable fields such as tissue engineering, regenerative medicine, cell culture, or biotechnology. The work presented here focuses on such a promising material: polyelectrolyte multilayer (PEM) composed of hyaluronic acid (HA) and poly(L-lysine) (PLL). This gel-like polymer surface coating is able to accumulate (bio-)molecules such as proteins or drugs and release them in a controlled manner. It serves as a mimic of the extracellular matrix (ECM) in composition and intrinsic properties. These qualities make the HA/PLL multilayers a promising candidate for multiple bio-applications such as those mentioned above. The work presented aims at the development of a straightforward approach for assessment of multi-fractional diffusion in multilayers (first part) and at control of local molecular transport into or from the multilayers by laser light trigger (second part). The mechanism of the loading and release is governed by the interaction of bioactives with the multilayer constituents and by the diffusion phenomenon overall. The diffusion of a molecule in HA/PLL multilayers shows multiple fractions of different diffusion rate. Approaches, that are able to assess the mobility of molecules in such a complex system, are limited. This shortcoming motivated the design of a novel evaluation tool presented here. The tool employs a simulation-based approach for evaluation of the data acquired by fluorescence recovery after photobleaching (FRAP) method. In this approach, possible fluorescence recovery scenarios are primarily simulated and afterwards compared with the data acquired while optimizing parameters of a model until a sufficient match is achieved. Fluorescent latex particles of different sizes and fluorescein in an aqueous medium are utilized as test samples validating the analysis results. The diffusion of protein cytochrome c in HA/PLL multilayers is evaluated as well. This tool significantly broadens the possibilities of analysis of spatiotemporal FRAP data, which originate from multi-fractional diffusion, while striving to be widely applicable. This tool has the potential to elucidate the mechanisms of molecular transport and empower rational engineering of the drug release systems. The second part of the work focuses on the fabrication of such a spatiotemporarily-controlled drug release system employing the HA/PLL multilayer. This release system comprises different layers of various functionalities that together form a sandwich structure. The bottom layer, which serves as a reservoir, is formed by HA/PLL PEM deposited on a planar glass substrate. On top of the PEM, a layer of so-called hybrids is deposited. The hybrids consist of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) -based hydrogel microparticles with surface-attached gold nanorods. The layer of hybrids is intended to serve as a gate that controls the local molecular transport through the PEM-solution-interface. The possibility of stimulating the molecular transport by near-infrared (NIR) laser irradiation is being explored. From several tested approaches for the deposition of hybrids onto the PEM surface, the drying-based approach was identified as optimal. Experiments, that examine the functionality of the fabricated sandwich at elevated temperature, document the reversible volume phase transition of the PEM-attached hybrids while sustaining the sandwich stability. Further, the gold nanorods were shown to effectively absorb light radiation in the tissue- and cell-friendly NIR spectral region while transducing the energy of light into heat. The rapid and reversible shrinkage of the PEM-attached hybrids was thereby achieved. Finally, dextran was employed as a model transport molecule. It loads into the PEM reservoir in a few seconds with the partition constant of 2.4, while it spontaneously releases in a slower, sustained manner. The local laser irradiation of the sandwich, which contains the fluorescein isothiocyanate tagged dextran, leads to a gradual reduction of fluorescence intensity in the irradiated region. The release system fabricated employs renowned photoresponsivity of the hybrids in an innovative setting. The results of the research are a step towards a spatially-controlled on-demand drug release system that paves the way to spatiotemporally controlled drug release. The approaches developed in this work have the potential to elucidate the molecular dynamics in ECM and to foster engineering of multilayers with properties tuned to mimic the ECM. The work aims at spatiotemporal control over the diffusion of bioactives and their presentation to the cells.},
  language  = {en}
}
@phdthesis{Šedova2022,
  author    = {Šedov{\´a}, Barbora},
  title     = {Heterogeneous effects of weather and climate change on human migration},
  doi       = {10.25932/publishup-53673},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-536733},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 284},
  year      = {2022},
  abstract  = {While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.},
  language  = {en}
}
@phdthesis{Oeztuerk2018,
  author    = {{\"O}zt{\"u}rk, Ugur},
  title     = {Learning more to predict landslides},
  doi       = {10.25932/publishup-42643},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426439},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 104},
  year      = {2018},
  abstract  = {Landslides are frequent natural hazards in rugged terrain, when the resisting frictional force of the surface of rupture yields to the gravitational force. These forces are functions of geological and morphological factors, such as angle of internal friction, local slope gradient or curvature, which remain static over hundreds of years; whereas more dynamic triggering events, such as rainfall and earthquakes, compromise the force balance by temporarily reducing resisting forces or adding transient loads. This thesis investigates landslide distribution and orientation due to landslide triggers (e.g. rainfall) at different scales (6-4∙10^5 km^2) and aims to link rainfall movement with the landslide distribution. It additionally explores the local impacts of the extreme rainstorms on landsliding and the role of precursory stability conditions that could be induced by an earlier trigger, such as an earthquake. Extreme rainfall is a common landslide trigger. Although several studies assessed rainfall intensity and duration to study the distribution of thus triggered landslides, only a few case studies quantified spatial rainfall patterns (i.e. orographic effect). Quantifying the regional trajectories of extreme rainfall could aid predicting landslide prone regions in Japan. To this end, I combined a non-linear correlation metric, namely event synchronization, and radial statistics to assess the general pattern of extreme rainfall tracks over distances of hundreds of kilometers using satellite based rainfall estimates. Results showed that, although the increase in rainfall intensity and duration positively correlates with landslide occurrence, the trajectories of typhoons and frontal storms were insufficient to explain landslide distribution in Japan. Extreme rainfall trajectories inclined northwestwards and were concentrated along some certain locations, such as coastlines of southern Japan, which was unnoticed in the landslide distribution of about 5000 rainfall-triggered landslides. These landslides seemed to respond to the mean annual rainfall rates. Above mentioned findings suggest further investigation on a more local scale to better understand the mechanistic response of landscape to extreme rainfall in terms of landslides. On May 2016 intense rainfall struck southern Germany triggering high waters and landslides. The highest damage was reported at the Braunsbach, which is located on the tributary-mouth fan formed by the Orlacher Bach. Orlacher Bach is a ~3 km long creek that drains a catchment of about ~6 km^2. I visited this catchment in June 2016 and mapped 48 landslides along the creek. Such high landslide activity was not reported in the nearby catchments within ~3300 km^2, despite similar rainfall intensity and duration based on weather radar estimates. My hypothesis was that several landslides were triggered by rainfall-triggered flash floods that undercut hillslope toes along the Orlacher Bach. I found that morphometric features such as slope and curvature play an important role in landslide distribution on this micro scale study site (<10 km^2). In addition, the high number of landslides along the Orlacher Bach could also be boosted by accumulated damages on hillslopes due karst weathering over longer time scales. Precursory damages on hillslopes could also be induced by past triggering events that effect landscape evolution, but this interaction is hard to assess independently from the latest trigger. For example, an earthquake might influence the evolution of a landscape decades long, besides its direct impacts, such as landslides that follow the earthquake. Here I studied the consequences of the 2016 Kumamoto Earthquake (MW 7.1) that triggered some 1500 landslides in an area of ~4000 km^2 in central Kyushu, Japan. Topography, i.e. local slope and curvature, both amplified and attenuated seismic waves, thus controlling the failure mechanism of those landslides (e.g. progressive). I found that topography fails in explaining the distribution and the preferred orientation of the landslides after the earthquake; instead the landslides were concentrated around the northeast of the rupture area and faced mostly normal to the rupture plane. This preferred location of the landslides was dominated mainly by the directivity effect of the strike-slip earthquake, which is the propagation of wave energy along the fault in the rupture direction; whereas amplitude variations of the seismic radiation altered the preferred orientation. I suspect that the earthquake directivity and the asymmetry of seismic radiation damaged hillslopes at those preferred locations increasing landslide susceptibility. Hence a future weak triggering event, e.g. scattered rainfall, could further trigger landslides at those damaged hillslopes.},
  language  = {en}
}
@phdthesis{Oenel2008,
  author    = {{\"O}nel, Hakan},
  title     = {Electron acceleration in a flare plasma via coronal circuits},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29035},
  school      = {Universit{\"a}t Potsdam},
  year      = {2008},
  abstract  = {The Sun is a star, which due to its proximity has a tremendous influence on Earth. Since its very first days mankind tried to "understand the Sun", and especially in the 20th century science has uncovered many of the Sun's secrets by using high resolution observations and describing the Sun by means of models. As an active star the Sun's activity, as expressed in its magnetic cycle, is closely related to the sunspot numbers. Flares play a special role, because they release large energies on very short time scales. They are correlated with enhanced electromagnetic emissions all over the spectrum. Furthermore, flares are sources of energetic particles. Hard X-ray observations (e.g., by NASA's RHESSI spacecraft) reveal that a large fraction of the energy released during a flare is transferred into the kinetic energy of electrons. However the mechanism that accelerates a large number of electrons to high energies (beyond 20 keV) within fractions of a second is not understood yet. The thesis at hand presents a model for the generation of energetic electrons during flares that explains the electron acceleration based on real parameters obtained by real ground and space based observations. According to this model photospheric plasma flows build up electric potentials in the active regions in the photosphere. Usually these electric potentials are associated with electric currents closed within the photosphere. However as a result of magnetic reconnection, a magnetic connection between the regions of different magnetic polarity on the photosphere can establish through the corona. Due to the significantly higher electric conductivity in the corona, the photospheric electric power supply can be closed via the corona. Subsequently a high electric current is formed, which leads to the generation of hard X-ray radiation in the dense chromosphere. The previously described idea is modelled and investigated by means of electric circuits. For this the microscopic plasma parameters, the magnetic field geometry and hard X-ray observations are used to obtain parameters for modelling macroscopic electric components, such as electric resistors, which are connected with each other. This model demonstrates that such a coronal electric current is correlated with large scale electric fields, which can accelerate the electrons quickly up to relativistic energies. The results of these calculations are encouraging. The electron fluxes predicted by the model are in agreement with the electron fluxes deduced from the measured photon fluxes. Additionally the model developed in this thesis proposes a new way to understand the observed double footpoint hard X-ray sources.},
  language  = {en}
}
@phdthesis{Zoeller1999,
  author    = {Z{\"o}ller, Gert},
  title     = {Analyse raumzeitlicher Muster in Erdbebendaten},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0000122},
  school      = {Universit{\"a}t Potsdam},
  year      = {1999},
  abstract  = {Die vorliegende Arbeit besch{\"a}ftigt sich mit der Charakterisierung von Seismizit{\"a}t anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss dar{\"u}ber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus f{\"u}r die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen h{\"a}ufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die M{\"o}glichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird h{\"a}ufig als Vorl{\"a}uferphaenomen f{\"u}r starke Erdbeben gedeutet. Es wird eine neue Methode pr{\"a}sentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen erm{\"o}glicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erh{\"a}lt man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz daf{\"u}r nicht hoch genug, um eine Vorhersage im Sinne einer Aussage {\"u}ber den Ort, die Zeit und die St{\"a}rke eines zu erwartenden Hauptbebens zu erm{\"o}glichen.},
  language  = {en}
}
@phdthesis{Zurell2011,
  author    = {Zurell, Damaris},
  title     = {Integrating dynamic and statistical modelling approaches in order to improve predictions for scenarios of environmental change},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-56845},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species' occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species' distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species' distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this 'virtual ecologist' approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species' response to altered environmental conditions and which should hence be considered when trying to project species' distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species' response to environmental change, identify key challenges for future research and discuss emerging developments.},
  language  = {en}
}
@phdthesis{Zuo2017,
  author    = {Zuo, Zhe},
  title     = {From unstructured to structured: Context-based named entity mining from text},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412576},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 112},
  year      = {2017},
  abstract  = {With recent advances in the area of information extraction, automatically extracting structured information from a vast amount of unstructured textual data becomes an important task, which is infeasible for humans to capture all information manually. Named entities (e.g., persons, organizations, and locations), which are crucial components in texts, are usually the subjects of structured information from textual documents. Therefore, the task of named entity mining receives much attention. It consists of three major subtasks, which are named entity recognition, named entity linking, and relation extraction. These three tasks build up an entire pipeline of a named entity mining system, where each of them has its challenges and can be employed for further applications. As a fundamental task in the natural language processing domain, studies on named entity recognition have a long history, and many existing approaches produce reliable results. The task is aiming to extract mentions of named entities in text and identify their types. Named entity linking recently received much attention with the development of knowledge bases that contain rich information about entities. The goal is to disambiguate mentions of named entities and to link them to the corresponding entries in a knowledge base. Relation extraction, as the final step of named entity mining, is a highly challenging task, which is to extract semantic relations between named entities, e.g., the ownership relation between two companies. In this thesis, we review the state-of-the-art of named entity mining domain in detail, including valuable features, techniques, evaluation methodologies, and so on. Furthermore, we present two of our approaches that focus on the named entity linking and relation extraction tasks separately. To solve the named entity linking task, we propose the entity linking technique, BEL, which operates on a textual range of relevant terms and aggregates decisions from an ensemble of simple classifiers. Each of the classifiers operates on a randomly sampled subset of the above range. In extensive experiments on hand-labeled and benchmark datasets, our approach outperformed state-of-the-art entity linking techniques, both in terms of quality and efficiency. For the task of relation extraction, we focus on extracting a specific group of difficult relation types, business relations between companies. These relations can be used to gain valuable insight into the interactions between companies and perform complex analytics, such as predicting risk or valuating companies. Our semi-supervised strategy can extract business relations between companies based on only a few user-provided seed company pairs. By doing so, we also provide a solution for the problem of determining the direction of asymmetric relations, such as the ownership_of relation. We improve the reliability of the extraction process by using a holistic pattern identification method, which classifies the generated extraction patterns. Our experiments show that we can accurately and reliably extract new entity pairs occurring in the target relation by using as few as five labeled seed pairs.},
  language  = {en}
}
@phdthesis{Zuhr2023,
  author    = {Zuhr, Alexandra},
  title     = {Proxy signal formation in palaeoclimate archives},
  doi       = {10.25932/publishup-58286},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-582864},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xx, 167},
  year      = {2023},
  abstract  = {Throughout the last ~3 million years, the Earth's climate system was characterised by cycles of glacial and interglacial periods. The current warm period, the Holocene, is comparably stable and stands out from this long-term cyclicality. However, since the industrial revolution, the climate has been increasingly affected by a human-induced increase in greenhouse gas concentrations. While instrumental observations are used to describe changes over the past ~200 years, indirect observations via proxy data are the main source of information beyond this instrumental era. These data are indicators of past climatic conditions, stored in palaeoclimate archives around the Earth. The proxy signal is affected by processes independent of the prevailing climatic conditions. In particular, for sedimentary archives such as marine sediments and polar ice sheets, material may be redistributed during or after the initial deposition and subsequent formation of the archive. This leads to noise in the records challenging reliable reconstructions on local or short time scales. This dissertation characterises the initial deposition of the climatic signal and quantifies the resulting archive-internal heterogeneity and its influence on the observed proxy signal to improve the representativity and interpretation of climate reconstructions from marine sediments and ice cores. To this end, the horizontal and vertical variation in radiocarbon content of a box-core from the South China Sea is investigated. The three-dimensional resolution is used to quantify the true uncertainty in radiocarbon age estimates from planktonic foraminifera with an extensive sampling scheme, including different sample volumes and replicated measurements of batches of small and large numbers of specimen. An assessment on the variability stemming from sediment mixing by benthic organisms reveals strong internal heterogeneity. Hence, sediment mixing leads to substantial time uncertainty of proxy-based reconstructions with error terms two to five times larger than previously assumed. A second three-dimensional analysis of the upper snowpack provides insights into the heterogeneous signal deposition and imprint in snow and firn. A new study design which combines a structure-from-motion photogrammetry approach with two-dimensional isotopic data is performed at a study site in the accumulation zone of the Greenland Ice Sheet. The photogrammetry method reveals an intermittent character of snowfall, a layer-wise snow deposition with substantial contributions by wind-driven erosion and redistribution to the final spatially variable accumulation and illustrated the evolution of stratigraphic noise at the surface. The isotopic data show the preservation of stratigraphic noise within the upper firn column, leading to a spatially variable climate signal imprint and heterogeneous layer thicknesses. Additional post-depositional modifications due to snow-air exchange are also investigated, but without a conclusive quantification of the contribution to the final isotopic signature. Finally, this characterisation and quantification of the complex signal formation in marine sediments and polar ice contributes to a better understanding of the signal content in proxy data which is needed to assess the natural climate variability during the Holocene.},
  language  = {en}
}
@phdthesis{Zou2007,
  author    = {Zou, Yong},
  title     = {Exploring recurrences in quasiperiodic systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-16497},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments.},
  language  = {en}
}
@phdthesis{Zorn2020,
  author    = {Zorn, Edgar Ulrich},
  title     = {Monitoring lava dome growth and deformation with photogrammetric methods and modelling},
  doi       = {10.25932/publishup-48360},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-483600},
  school      = {Universit{\"a}t Potsdam},
  pages     = {IX, 167},
  year      = {2020},
  abstract  = {Lava domes are severely hazardous, mound-shaped extrusions of highly viscous lava and commonly erupt at many active stratovolcanoes around the world. Due to gradual growth and flank oversteepening, such lava domes regularly experience partial or full collapses, resulting in destructive and far-reaching pyroclastic density currents. They are also associated with cyclic explosive activity as the complex interplay of cooling, degassing, and solidification of dome lavas regularly causes gas pressurizations on the dome or the underlying volcano conduit. Lava dome extrusions can last from days to decades, further highlighting the need for accurate and reliable monitoring data. This thesis aims to improve our understanding of lava dome processes and to contribute to the monitoring and prediction of hazards posed by these domes. The recent rise and sophistication of photogrammetric techniques allows for the extraction of observational data in unprecedented detail and creates ideal tools for accomplishing this purpose. Here, I study natural lava dome extrusions as well as laboratory-based analogue models of lava dome extrusions and employ photogrammetric monitoring by Structure-from-Motion (SfM) and Particle-Image-Velocimetry (PIV) techniques. I primarily use aerial photography data obtained by helicopter, airplanes, Unoccupied Aircraft Systems (UAS) or ground-based timelapse cameras. Firstly, by combining a long time-series of overflight data at Volc{\´a}n de Colima, M{\´e}xico, with seismic and satellite radar data, I construct a detailed timeline of lava dome and crater evolution. Using numerical model, the impact of the extrusion on dome morphology and loading stress is further evaluated and an impact on the growth direction is identified, bearing important implications for the location of collapse hazards. Secondly, sequential overflight surveys at the Santiaguito lava dome, Guatemala, reveal surface motion data in high detail. I quantify the growth of the lava dome and the movement of a lava flow, showing complex motions that occur on different timescales and I provide insight into rock properties relevant for hazard assessment inferred purely by photogrammetric processing of remote sensing data. Lastly, I recreate artificial lava dome and spine growth using analogue modelling under controlled conditions, providing new insights into lava extrusion processes and structures as well as the conditions in which they form. These findings demonstrate the capabilities of photogrammetric data analyses to successfully monitor lava dome growth and evolution while highlighting the advantages of complementary modelling methods to explain the observed phenomena. The results presented herein further bear important new insights and implications for the hazards posed by lava domes.},
  language  = {en}
}