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The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
3D from 2D touch
(2013)
While interaction with computers used to be dominated by mice and keyboards, new types of sensors now allow users to interact through touch, speech, or using their whole body in 3D space. These new interaction modalities are often referred to as "natural user interfaces" or "NUIs." While 2D NUIs have experienced major success on billions of mobile touch devices sold, 3D NUI systems have so far been unable to deliver a mobile form factor, mainly due to their use of cameras. The fact that cameras require a certain distance from the capture volume has prevented 3D NUI systems from reaching the flat form factor mobile users expect. In this dissertation, we address this issue by sensing 3D input using flat 2D sensors. The systems we present observe the input from 3D objects as 2D imprints upon physical contact. By sampling these imprints at very high resolutions, we obtain the objects' textures. In some cases, a texture uniquely identifies a biometric feature, such as the user's fingerprint. In other cases, an imprint stems from the user's clothing, such as when walking on multitouch floors. By analyzing from which part of the 3D object the 2D imprint results, we reconstruct the object's pose in 3D space. While our main contribution is a general approach to sensing 3D input on 2D sensors upon physical contact, we also demonstrate three applications of our approach. (1) We present high-accuracy touch devices that allow users to reliably touch targets that are a third of the size of those on current touch devices. We show that different users and 3D finger poses systematically affect touch sensing, which current devices perceive as random input noise. We introduce a model for touch that compensates for this systematic effect by deriving the 3D finger pose and the user's identity from each touch imprint. We then investigate this systematic effect in detail and explore how users conceptually touch targets. Our findings indicate that users aim by aligning visual features of their fingers with the target. We present a visual model for touch input that eliminates virtually all systematic effects on touch accuracy. (2) From each touch, we identify users biometrically by analyzing their fingerprints. Our prototype Fiberio integrates fingerprint scanning and a display into the same flat surface, solving a long-standing problem in human-computer interaction: secure authentication on touchscreens. Sensing 3D input and authenticating users upon touch allows Fiberio to implement a variety of applications that traditionally require the bulky setups of current 3D NUI systems. (3) To demonstrate the versatility of 3D reconstruction on larger touch surfaces, we present a high-resolution pressure-sensitive floor that resolves the texture of objects upon touch. Using the same principles as before, our system GravitySpace analyzes all imprints and identifies users based on their shoe soles, detects furniture, and enables accurate touch input using feet. By classifying all imprints, GravitySpace detects the users' body parts that are in contact with the floor and then reconstructs their 3D body poses using inverse kinematics. GravitySpace thus enables a range of applications for future 3D NUI systems based on a flat sensor, such as smart rooms in future homes. We conclude this dissertation by projecting into the future of mobile devices. Focusing on the mobility aspect of our work, we explore how NUI devices may one day augment users directly in the form of implanted devices.
In soils and sediments there is a strong coupling between local biogeochemical processes and the distribution of water, electron acceptors, acids and nutrients. Both sides are closely related and affect each other from small scale to larger scales. Soil structures such as aggregates, roots, layers or macropores enhance the patchiness of these distributions. At the same time it is difficult to access the spatial distribution and temporal dynamics of these parameter. Noninvasive imaging techniques with high spatial and temporal resolution overcome these limitations. And new non-invasive techniques are needed to study the dynamic interaction of plant roots with the surrounding soil, but also the complex physical and chemical processes in structured soils. In this study we developed an efficient non-destructive in-situ method to determine biogeochemical parameters relevant to plant roots growing in soil. This is a quantitative fluorescence imaging method suitable for visualizing the spatial and temporal pH changes around roots. We adapted the fluorescence imaging set-up and coupled it with neutron radiography to study simultaneously root growth, oxygen depletion by respiration activity and root water uptake. The combined set up was subsequently applied to a structured soil system to map the patchy structure of oxic and anoxic zones induced by a chemical oxygen consumption reaction for spatially varying water contents. Moreover, results from a similar fluorescence imaging technique for nitrate detection were complemented by a numerical modeling study where we used imaging data, aiming to simulate biodegradation under anaerobic, nitrate reducing conditions.
Gegenstand der Dissertation ist die größen- und eigenschaftsoptimierte Synthese und Charakterisierung von anorganischen Nanopartikeln in einer geeigneten Polyelektrolytmodifizierten Mikroemulsion. Das Hauptziel bildet dabei die Auswahl einer geeigneten Mikroemulsion, zur Synthese von kleinen, stabilen, reproduzierbaren Nanopartikeln mit besonderen Eigenschaften. Die vorliegende Arbeit wurde in zwei Haupteile gegliedert. Der erste Teil befasst sich mit der Einmischung von unterschiedlichen Polykationen (lineares Poly (diallyldimethylammoniumchlorid) (PDADMAC) und verzweigtes Poly (ethylenimin) (PEI)) in verschiedene, auf unterschiedlichen Tensiden (CTAB - kationisch, SDS - anionisch, SB - zwitterionisch) basierenden, Mikroemulsionssysteme. Dabei zeigt sich, dass das Einmischen der Polykationen in die Wassertröpfchen der Wasser-in-Öl (W/O) Mikroemulsion prinzipiell möglich ist. Der Einfluss der verschiedenen Polykationen auf das Phasenverhalten der W/O Mikroemulsion ist jedoch sehr unterschiedlich. In Gegenwart des kationischen Tensids führen die repulsiven Wechselwirkungen mit den Polykationen zu einer Destabilisierung des Systems, während die ausgeprägten Wechselwirkungen mit dem anionischen Tensid in einer deutlichen Stabilisierung des Systems resultieren. Für das zwitterionische Tensid führen die moderaten Wechselwirkungen mit den Polykationen zu einer partiellen Stabilisierung. Der zweite Teil der Arbeit beschäftigt sich mit dem Einsatz der unterschiedlichen, Polyelektrolyt- modifizierten Mikroemulsionen als Templatphase für die Herstellung verschiedener, anorganischer Nanopartikel. Die CTAB-basierte Mikroemulsion erweist sich dabei als ungeeignet für die Herstellung von CdS Nanopartikeln, da zum einen nur eine geringe Toleranz gegenüber den Reaktanden vorhanden ist (Destabilisierungseffekt) und zum anderen das Partikelwachstum durch den Polyelektrolyt-Tensid-Film nicht ausreichend begrenzt wird. Zudem zeigt sich, dass eine Abtrennung der Partikel aus der Mikroemulsion nicht möglich ist. Die SDS-basierten Mikroemulsionen, erweisen sich als geeignete Templatphase zur Synthese kleiner anorganischer Nanopartikel (3 – 20 nm). Sowohl CdS Quantum Dots, als auch Gold Nanopartikel konnten erfolgreich in der Mikroemulsion synthetisiert werden, wobei das verzweigte PEI einen interessanten Templat-Effekt in der Mikroemulsion hervorruft. Als deutlicher Nachteil der SDS-basierten Mikroemulsionen offenbaren sich die starken Wechselwirkungen zwischen dem Tensid und den Polyelektrolyten während der Aufarbeitung der Nanopartikel aus der Mikroemulsion. Dabei erweist sich die Polyelektrolyt-Tensid-Komplexbildung als hinderlich für die Redispergierung der CdS Quantum Dots in Wasser, so dass Partikelaggregation einsetzt. Die SB-basierten Mikroemulsionen erweisen sich als günstige Templatphase für die Bildung von größen- und eigenschaftenoptimierten Nanopartikeln (< 4 nm), wobei insbesondere eine Modifizierung mit PEI als ideal betrachtet werden kann. In Gegenwart des verzweigten PEI gelang es erstmals ultrakleine, fluoreszierende Gold Cluster (< 2 nm) in einer SB-basierten Mikroemulsion als Templatphase herzustellen. Als besonderer Vorteil der SB-basierten Mikroemulsion zeigen sich die moderaten Wechselwirkungen zwischen dem zwitterionischen Tensid und den Polyelektrolyten, welche eine anschließende Abtrennung der Partikel aus der Mikroemulsion unter Erhalt der Größe und ihrer optischen Eigenschaften ermöglichen. In der redispergierten wässrigen Lösung gelang somit eine Auftrennung der PEI-modifizierten Partikel mit Hilfe der asymmetrischer Fluss Feldflussfraktionierung (aF FFF). Die gebildeten Nanopartikel zeigen interessante optische Eigenschaften und können zum Beispiel erfolgreich zur Modifizierung von Biosensoren eingesetzt werden.
Water management and environmental protection is vulnerable to extreme low flows during streamflow droughts. During the last decades, in most rivers of Central Europe summer runoff and low flows have decreased. Discharge projections agree that future decrease in runoff is likely for catchments in Brandenburg, Germany. Depending on the first-order controls on low flows, different adaption measures are expected to be appropriate. Small catchments were analyzed because they are expected to be more vulnerable to a changing climate than larger rivers. They are mainly headwater catchments with smaller ground water storage. Local characteristics are more important at this scale and can increase vulnerability. This thesis mutually evaluates potential adaption measures to sustain minimum runoff in small catchments of Brandenburg, Germany, and similarities of these catchments regarding low flows. The following guiding questions are addressed: (i) Which first-order controls on low flows and related time scales exist? (ii) Which are the differences between small catchments regarding low flow vulnerability? (iii) Which adaption measures to sustain minimum runoff in small catchments of Brandenburg are appropriate considering regional low flow patterns? Potential adaption measures to sustain minimum runoff during periods of low flows can be classified into three categories: (i) increase of groundwater recharge and subsequent baseflow by land use change, land management and artificial ground water recharge, (ii) increase of water storage with regulated outflow by reservoirs, lakes and wetland water management and (iii) regional low flow patterns have to be considered during planning of measures with multiple purposes (urban water management, waste water recycling and inter-basin water transfer). The question remained whether water management of areas with shallow groundwater tables can efficiently sustain minimum runoff. Exemplary, water management scenarios of a ditch irrigated area were evaluated using the model Hydrus-2D. Increasing antecedent water levels and stopping ditch irrigation during periods of low flows increased fluxes from the pasture to the stream, but storage was depleted faster during the summer months due to higher evapotranspiration. Fluxes from this approx. 1 km long pasture with an area of approx. 13 ha ranged from 0.3 to 0.7 l\s depending on scenario. This demonstrates that numerous of such small decentralized measures are necessary to sustain minimum runoff in meso-scale catchments. Differences in the low flow risk of catchments and meteorological low flow predictors were analyzed. A principal component analysis was applied on daily discharge of 37 catchments between 1991 and 2006. Flows decreased more in Southeast Brandenburg according to meteorological forcing. Low flow risk was highest in a region east of Berlin because of intersection of a more continental climate and the specific geohydrology. In these catchments, flows decreased faster during summer and the low flow period was prolonged. A non-linear support vector machine regression was applied to iteratively select meteorological predictors for annual 30-day minimum runoff in 16 catchments between 1965 and 2006. The potential evapotranspiration sum of the previous 48 months was the most important predictor (r²=0.28). The potential evapotranspiration of the previous 3 months and the precipitation of the previous 3 months and last year increased model performance (r²=0.49, including all four predictors). Model performance was higher for catchments with low yield and more damped runoff. In catchments with high low flow risk, explanatory power of long term potential evapotranspiration was high. Catchments with a high low flow risk as well as catchments with a considerable decrease in flows in southeast Brandenburg have the highest demand for adaption. Measures increasing groundwater recharge are to be preferred. Catchments with high low flow risk showed relatively deep and decreasing groundwater heads allowing increased groundwater recharge at recharge areas with higher altitude away from the streams. Low flows are expected to stay low or decrease even further because long term potential evapotranspiration was the most important low flow predictor and is projected to increase during climate change. Differences in low flow risk and runoff dynamics between catchments have to be considered for management and planning of measures which do not only have the task to sustain minimum runoff.
For the first time the transcriptional reprogramming of distinct root cortex cells during the arbuscular mycorrhizal (AM) symbiosis was investigated by combining Laser Capture Mirodissection and Affymetrix GeneChip® Medicago genome array hybridization. The establishment of cryosections facilitated the isolation of high quality RNA in sufficient amounts from three different cortical cell types. The transcript profiles of arbuscule-containing cells (arb cells), non-arbuscule-containing cells (nac cells) of Rhizophagus irregularis inoculated Medicago truncatula roots and cortex cells of non-inoculated roots (cor) were successfully explored. The data gave new insights in the symbiosis-related cellular reorganization processes and indicated that already nac cells seem to be prepared for the upcoming fungal colonization. The mycorrhizal- and phosphate-dependent transcription of a GRAS TF family member (MtGras8) was detected in arb cells and mycorrhizal roots. MtGRAS shares a high sequence similarity to a GRAS TF suggested to be involved in the fungal colonization processes (MtRAM1). The function of MtGras8 was unraveled upon RNA interference- (RNAi-) mediated gene silencing. An AM symbiosis-dependent expression of a RNAi construct (MtPt4pro::gras8-RNAi) revealed a successful gene silencing of MtGras8 leading to a reduced arbuscule abundance and a higher proportion of deformed arbuscules in root with reduced transcript levels. Accordingly, MtGras8 might control the arbuscule development and life-time. The targeting of MtGras8 by the phosphate-dependent regulated miRNA5204* was discovered previously (Devers et al., 2011). Since miRNA5204* is known to be affected by phosphate, the posttranscriptional regulation might represent a link between phosphate signaling and arbuscule development. In this work, the posttranscriptional regulation was confirmed by mis-expression of miRNA5204* in M. truncatula roots. The miRNA-mediated gene silencing affects the MtGras8 transcript abundance only in the first two weeks of the AM symbiosis and the mis-expression lines seem to mimic the phenotype of MtGras8-RNAi lines. Additionally, MtGRAS8 seems to form heterodimers with NSP2 and RAM1, which are known to be key regulators of the fungal colonization process (Hirsch et al., 2009; Gobbato et al., 2012). These data indicate that MtGras8 and miRNA5204* are linked to the sym pathway and regulate the arbuscule development in phosphate-dependent manner.
Die Expansion des renalen Tubulointerstitiums aufgrund einer Akkumulation zellulärer Bestandteile und extrazellulärer Matrix ist eine charakteristische Eigenschaft der chronischen Nierenerkrankung (CKD) und führt zu einer Progression der Erkrankung in Richtung eines terminalen Nierenversagens. Die Fibroblasten Proliferation und ihre Transformation hin zum sekretorischen Myofibroblasten-Phänotyp stellen hierbei Schlüsselereignisse dar. Signalprozesse, die zur Induktion der Myofibroblasten führen, werden aktiv beforscht um anti-fibrotische Therapieansätze zu identifizieren. Das anti-inflammatorische Protein Annexin A1 und sein Rezeptor Formyl-Peptid Rezeptor 2 (FPR2) wurden in verschiedenen Organsystemen mit der Regulation von Fibroblastenaktivität in Verbindung gebracht, jedoch wurden ihre Expression und Funktion bei renalen fibrotischen Erkrankungen bisher nicht untersucht. Ziel der aktuellen Studie war daher die Untersuchung der renalen Annexin A1- und FPR2-Expression in einem Tiermodell des chronischen Nierenversagens, sowie die Charakterisierung der funktionellen Rolle von Annexin A1 in der Regulation des Fibroblasten Phänotyps und ihrer Syntheseleistung. Dazu wurden neugeborene Sprague-Dawley Ratten in den ersten zwei Wochen ihres Lebens entweder mit Vehikel oder mit einem Angiotensin II Typ I Rezeptor Antagonisten behandelt und ohne weitere Intervention bis zu einem Alter von 11 Monaten (CKD Ratten) gehalten. Die Regulation und Lokalisation von Annexin A1 und FPR2 wurden mit Hilfe von Real-Time PCR und Immunhistochemie erfasst. Annexin A1- und FPR2-exprimierende Zellen wurden weiter durch Doppelimmunfluoreszenzfärbungen charakterisiert. Gefärbt wurde mit Antikörpern gegen endotheliale Zellen (rat endothelial cell antigen), Makrophagen (CD 68), Fibroblasten (CD73) und Myofibroblasten (alpha-smooth muscle actin (α-sma)). Zellkulturstudien wurden an immortalisierten renalen kortikalen Fibroblasten aus Wildtyp- und Annexin A1-defizienten Mäusen, sowie an etablierten humanen und murinen renalen Fibrolasten durchgeführt. Eine Überexpression von Annexin A1 wurde durch eine stabile Transfektion erreicht. Die Expression von Annexin A1, α-sma und Kollagen 1α1 wurde durch Real-Time PCR, Western Blot und Immuhistochemie erfasst. Die Sekretion des Annexin A1 Proteins wurde nach TCA-Fällung des Zellkulturüberstandes im Western Blot untersucht. Wie zu erwarten zeigten die CKD Ratten eine geringere Anzahl an Nephronen mit deutlicher glomerulären Hypertrophie. Der tubulointerstitielle Raum war durch fibrilläres Kollagen, aktivierte Fibroblasten und inflammatorische Zellen expandiert. Parallel dazu war die mRNA Expression von Annexin A1 und Transforming growth factor beta (TGF-β) signifikant erhöht. Die Annexin A1-Lokalisation mittels Doppelimmunfluorsezenz identifizierte eine große Anzahl von CD73-positiven kortikalen Fibroblasten und eine Subpopulation von Makrophagen als Annexin A1-positiv. Die Annexin A1-Menge in Myofibroblasten und renalen Endothelien war gering. FPR2 konnte in der Mehrzahl der renalen Fibroblasten, in Myofibroblasten, in einer Subpopulation von Makrophagen und in renalen Epithelzellen nachgewiesen werden. Eine Behandlung der murinen Fibroblasten mit dem pro-fibrotischen Zytokin TGF-β führte zu einem parallelen Anstieg der α-sma-, Kollagen 1α1- und Annexin A1-Biosynthese und zu einer gesteigerten Sekretion von Annexin A1. Eine Überexpression von Annexin A1 in murinen Fibroblasten reduzierte das Ausmaß der TGF-β induzierten α-sma- und Kollagen 1α1-Biosynthese. Fibroblasten aus Annexin A1-defizienten Mäusen zeigten einen starken Myofibroblasten-Phänotyp mit einer gesteigerten Expression an α-sma und Kollagen 1α1. Der Einsatz eines Peptidantagonisten des FPR2 (WRW4) resultierte in einer Stimulation der α-sma-Biosynthese, was die Vermutung nahe legte, dass Annexin A1 FPR2-vermittelt anti-fibrotische Effekte hat. Zusammenfassend zeigen diese Ergebnisse, dass renale kortikale Fibroblasten eine Hauptquelle des Annexin A1 im renalen Interstitium und einen Ansatzpunkt für Annexin A1-Signalwege in der Niere darstellen. Das Annexin A1/FPR2-System könnte daher eine wichtige Rolle in der Kontrolle des Fibroblasten Phänotyp und der Fibroblasten Aktivität spielen und daher einen neuen Ansatz für die anti-fibrotischen pharmakologischen Strategien in der Behandlung des CKD darstellen.
Even though quite different in occurrence and consequences, from a modeling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding: uncertainty about the modeling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Nevertheless deterministic approaches are still widely used in natural hazard assessments, holding the risk of underestimating the hazard with disastrous effects. The all-round probabilistic framework of Bayesian networks constitutes an attractive alternative. In contrast to deterministic proceedings, it treats response variables as well as explanatory variables as random variables making no difference between input and output variables. Using a graphical representation Bayesian networks encode the dependency relations between the variables in a directed acyclic graph: variables are represented as nodes and (in-)dependencies between variables as (missing) edges between the nodes. The joint distribution of all variables can thus be described by decomposing it, according to the depicted independences, into a product of local conditional probability distributions, which are defined by the parameters of the Bayesian network. In the framework of this thesis the Bayesian network approach is applied to different natural hazard domains (i.e. seismic hazard, flood damage and landslide assessments). Learning the network structure and parameters from data, Bayesian networks reveal relevant dependency relations between the included variables and help to gain knowledge about the underlying processes. The problem of Bayesian network learning is cast in a Bayesian framework, considering the network structure and parameters as random variables itself and searching for the most likely combination of both, which corresponds to the maximum a posteriori (MAP score) of their joint distribution given the observed data. Although well studied in theory the learning of Bayesian networks based on real-world data is usually not straight forward and requires an adoption of existing algorithms. Typically arising problems are the handling of continuous variables, incomplete observations and the interaction of both. Working with continuous distributions requires assumptions about the allowed families of distributions. To "let the data speak" and avoid wrong assumptions, continuous variables are instead discretized here, thus allowing for a completely data-driven and distribution-free learning. An extension of the MAP score, considering the discretization as random variable as well, is developed for an automatic multivariate discretization, that takes interactions between the variables into account. The discretization process is nested into the network learning and requires several iterations. Having to face incomplete observations on top, this may pose a computational burden. Iterative proceedings for missing value estimation become quickly infeasible. A more efficient albeit approximate method is used instead, estimating the missing values based only on the observations of variables directly interacting with the missing variable. Moreover natural hazard assessments often have a primary interest in a certain target variable. The discretization learned for this variable does not always have the required resolution for a good prediction performance. Finer resolutions for (conditional) continuous distributions are achieved with continuous approximations subsequent to the Bayesian network learning, using kernel density estimations or mixtures of truncated exponential functions. All our proceedings are completely data-driven. We thus avoid assumptions that require expert knowledge and instead provide domain independent solutions, that are applicable not only in other natural hazard assessments, but in a variety of domains struggling with uncertainties.
Systems of Systems (SoS) have received a lot of attention recently. In this thesis we will focus on SoS that are built atop the techniques of Service-Oriented Architectures and thus combine the benefits and challenges of both paradigms. For this thesis we will understand SoS as ensembles of single autonomous systems that are integrated to a larger system, the SoS. The interesting fact about these systems is that the previously isolated systems are still maintained, improved and developed on their own. Structural dynamics is an issue in SoS, as at every point in time systems can join and leave the ensemble. This and the fact that the cooperation among the constituent systems is not necessarily observable means that we will consider these systems as open systems. Of course, the system has a clear boundary at each point in time, but this can only be identified by halting the complete SoS. However, halting a system of that size is practically impossible. Often SoS are combinations of software systems and physical systems. Hence a failure in the software system can have a serious physical impact what makes an SoS of this kind easily a safety-critical system. The contribution of this thesis is a modelling approach that extends OMG's SoaML and basically relies on collaborations and roles as an abstraction layer above the components. This will allow us to describe SoS at an architectural level. We will also give a formal semantics for our modelling approach which employs hybrid graph-transformation systems. The modelling approach is accompanied by a modular verification scheme that will be able to cope with the complexity constraints implied by the SoS' structural dynamics and size. Building such autonomous systems as SoS without evolution at the architectural level --- i. e. adding and removing of components and services --- is inadequate. Therefore our approach directly supports the modelling and verification of evolution.
Die automatisierte Objektidentifikation stellt ein modernes Werkzeug in den Geoinformationswissenschaften dar (BLASCHKE et al., 2012). Um bei thematischen Kartierungen untereinander vergleichbare Ergebnisse zu erzielen, sollen aus Sicht der Geoinformatik Mittel für die Objektidentifikation eingesetzt werden. Anstelle von Feldarbeit werden deshalb in der vorliegenden Arbeit multispektrale Fernerkundungsdaten als Primärdaten verwendet. Konkrete natürliche Objekte werden GIS-gestützt und automatisiert über große Flächen und Objektdichten aus Primärdaten identifiziert und charakterisiert. Im Rahmen der vorliegenden Arbeit wird eine automatisierte Prozesskette zur Objektidentifikation konzipiert. Es werden neue Ansätze und Konzepte der objektbasierten Identifikation von natürlichen isolierten terrestrischen Oberflächenformen entwickelt und implementiert. Die Prozesskette basiert auf einem Konzept, das auf einem generischen Ansatz für automatisierte Objektidentifikation aufgebaut ist. Die Prozesskette kann anhand charakteristischer quantitativer Parameter angepasst und so umgesetzt werden, womit das Konzept der Objektidentifikation modular und skalierbar wird. Die modulbasierte Architektur ermöglicht den Einsatz sowohl einzelner Module als auch ihrer Kombination und möglicher Erweiterungen. Die eingesetzte Methodik der Objektidentifikation und die daran anschließende Charakteristik der (geo)morphometrischen und morphologischen Parameter wird durch statistische Verfahren gestützt. Diese ermöglichen die Vergleichbarkeit von Objektparametern aus unterschiedlichen Stichproben. Mit Hilfe der Regressionsund Varianzanalyse werden Verhältnisse zwischen Objektparametern untersucht. Es werden funktionale Abhängigkeiten der Parameter analysiert, um die Objekte qualitativ zu beschreiben. Damit ist es möglich, automatisiert berechnete Maße und Indizes der Objekte als quantitative Daten und Informationen zu erfassen und unterschiedliche Stichproben anzuwenden. Im Rahmen dieser Arbeit bilden Thermokarstseen die Grundlage für die Entwicklungen und als Beispiel sowie Datengrundlage für den Aufbau des Algorithmus und die Analyse. Die Geovisualisierung der multivariaten natürlichen Objekte wird für die Entwicklung eines besseren Verständnisses der räumlichen Relationen der Objekte eingesetzt. Kern der Geovisualisierung ist das Verknüpfen von Visualisierungsmethoden mit kartenähnlichen Darstellungen.