Les données permettant de décrire des phénomènes spatio-temporels sont de plus en plus nombreuses. Ces nouvelles données peuvent alors être éloignées de celles habituellement observées pour l'étude de certains phénomènes. Leur analyse, selon une approche hypothético-déductive telle qu'elle est majoritairement effectuée en statistique et dans les SIG, peut ainsi passer sous silence certaines informations insoupçonnées, mais pertinentes, sur les dynamiques de ces phénomènes spatio-temporels.Il peut alors être intéressant de simplement donner à voir les données, pour observer ce qu'elles ont à montrer, avant de les analyser. Ce principe est celui de l'analyse exploratoire: le procédé est de permettre à un utilisateur d'effectuer une exploration libre des données, au moyen de représentations visuelles, afin de mettre en lumière des structures ou des relations insoupçonnées. Aujourd'hui, l'analyse exploratoire est notamment possible au moyen d'environnements de visualisation, intégrant différentes représentations graphiques et cartographiques interactives.Les environnements de visualisation sont majoritairement développés de manière ad hoc, dans le cadre d'une thématique particulière. Or l'émergence constante de nouvelles données incite à promouvoir des méthodes d'analyse applicables à des phénomènes de différentes natures. En fonction de la problématique dans laquelle s'insèrent ces derniers, les dynamiques sur lesquelles va se focaliser l'analyse diffèrent. Analyser un phénomène météorologique dans un but de prévision implique de s’intéresser aux récurrences cycliques du phénomène. Analyser l'évolution d'une population pour la mise en place de politiques publiques implique d’analyser ce phénomène sur le temps long et selon différentes zones de l’espace.Notre objectif est de proposer une méthode d'analyse exploratoire des phénomènes spatio-temporels et de leurs dynamiques, indépendante du thème traité. Pour cela, nous proposons un environnement de géovisualisation, GrAPHiST (Géovisualisation pour l'Analyse des PHenomenes Spatio-Temporels), permettant l'analyse de différentes dynamiques, selon différentes échelles spatiales et temporelles (linéaires ou cycliques). Développer cet environnement implique de s’interroger sur la modélisation du changement dans l’espace, la nature des dynamiques spatio-temporelles à étudier, et les outils visuels et interactifs permettant de les identifier.Ainsi, les contributions de notre recherche se situent à plusieurs niveaux :- une modélisation générique des phénomènes spatio-temporels, sous la forme de séries événementielles;- de nouvelles méthodes de représentations graphiques et interactives, autorisant la recherche et l'identification des dynamiques spatio-temporelles, notamment: l'introduction de diagrammes temporels interactifs permettant la recherche visuelle de récurrences cycliques dans les données spatio-temporelles; l'utilisation de règles de symbologie permettant la visualisation des relations entre les composantes temporelle et spatiale des phénomènes; de nouvelles méthodes de représentations des agrégats d'événements proches, permettant d'identifier des structures dans leur distribution spatio-temporelle;- la formalisation d’une approche d'analyse exploratoire des dynamiques spatio-temporelles, déclinée en plusieurs scénarios selon l’objectif poursuivi.Nous validons notre approche en l'appliquant à l'analyse de différents jeux de données. L'objectif est de vérifier la possibilité d'identifier des dynamiques, relatives au temps linéaire ou cyclique, au moyen de GrAPHiST, et d'illustrer le caractère générique de l'approche, ainsi que les opportunités d'analyse offertes par l'environnement. / Datasets allowing the description of spatio-temporal phenomena are becoming ever more numerous. These new data can be very different from those usually observed for studying spatio-temporal phenomena. An analysis through a hypothetico-deductive approach, like is mainly done in statistic and GIS domains, can ignore some unsuspected, but relevant, information about the dynamics of these spatio-temporal phenomena.It can be interesting then, to just present the data, to observe what they have to show, before analysing them. This is the principle of the exploratory data analysis: the process is to allow a user to freely explore data, through visual representations, in order to highlight unsuspected structures or relationships. Today, exploratory analysis is possible through visualization environments, which integrate different graphic or cartographic interactive representations.Visualization environments are mainly developed in an ad hoc manner, in the context of a particular thematic field. However, the constant appearance of new data encourages promoting analysis methods, which could be applied to several types of phenomena. According to the domain related to these phenomena, the analysis will be focused on different dynamics. Analysing a meteorological phenomenon, in a forecasting purpose, implies a focus on the cyclic recurrences of the phenomenon. Analysing the increase of a population, for the purpose of deciding public policies, implies an analysis of the phenomenon on a long-term, through different spatial areas.Our objective is to propose a method for the exploratory analysis of spatio-temporal phenomena and their dynamics, which would be independent of the topic. In order to achieve this, we propose a geovisualization environment, GrAPHiST (Géovisualisation pour l'Analyse des PHenomenes Spatio-Temporels; Geovisualization for spatio-temporal phenomena analysis), allowing the analysis of several dynamics, through different spatial and temporal (linear or cyclic) scales. Developing this environment implies to focus on how spatial changes are modelled, on the nature of the spatio-temporal dynamics we have to study, and on the visual and interactive tools, which allow the identification of these dynamics.So, the contributions of our research can be found at several levels:a generic modelling approach of spatio-temporal phenomena, in the form of event series;new graphical and interactive representation methods, which allow the searching and the identification of spatio-temporal dynamics, including: the introduction of interactive temporal diagrams, which allow the visual searching of cyclic recurrences in spatio-temporal data; the use of symbology rules, which allow the visualization of relationships between the spatial and temporal components of phenomena; new methods to represent aggregated closed events, which allow to identify structures in their spatio-temporal distribution;the formalization of an exploratory approach for the spatio-temporal dynamics analysis, divided into several scenarios, according to the purpose of the analysis.We validate our proposition by applying it to the analysis of several datasets. The objective is to verify the possibility to identify dynamics, related to linear or cyclic time, through the use of GrAPHiST, and to illustrate the generic aspect of the approach, as well as the analysis opportunities given by the environment.

Internet of things ger oss möjligheten att kunna identifiera, kontrollera och övervaka objekt över hela världen. För att mängden rådata som strömmar in ska kunna skapa mening och insikter till människan krävs det att den presenteras på rätt sätt. Studien undersöker därför om geovisualisering bättre kan möta människans kognitiva förmåga vid intag och tolkning av information. Geovisualisering innebär att rumslig data kan utforskas på en karta via en interaktiv display och är en länk mellan den mänskliga beslutsprocessen, interaktiva gränssnitt och data [21]. Mer forskning behövs inom området för att undersöka hur geovisualisering kan ta plats i system där stora datamängder behöver presenteras på ett överskådligt sätt och stödja beslutsprocesser. Studien syftar till att jämföra geovisualiseringar med ett befintligt system som tillhandahåller kontinuerlig uppdatering och övervakning av nätverkskameror genom utförande av användbarhetstester och intervjuer. Det som undersökts är om geovisualisering kan ge en ökad förståelse och bättre interaktion i ett utrymme som efterliknar den fysiska världen, samt undersöka potentiella problem för att hitta framtida förbättringar. Resultaten visade att navigering och informationsöverbelastning var återkommande problem under testerna av det befintliga systemet. För geovisualiseringarna visade resultaten det motsatta då de istället underlättade förståelsen för interaktion och information. Vissa problem identifierades dock för de framtagna geovisualiseringarna, som exempelvis dess begränsade interaktion och misstolkningar av objekt. Trots detta visade det sig vara fördelaktigt att placera ut enheter i deras verkliga miljö med hjälp av geovisualisering då det bidrog till en bättre översikt och förståelse av systemets sammanhang. / The Internet of Things gives us the ability to identify, control and monitor objects around the world. In order to get meaning and knowledge from the amount of raw data, it needs to be presented in the right way for people to get insights from it. The study therefore examines whether geovisualization can better meet human cognitive ability in  interpretation of information. Geovisualization means that spatial data can be explored on a map through an interactive display and is a link between the human decision-making process, interactive interfaces and data [21]. More research is needed in the area to investigate how geovisualization can take place in systems where large amounts of data needs to be presented and how it can support decision-making processes. The study aims to compare geovisualizations with an existing system that provides continuous updating and monitoring of network cameras by performing usability tests and interviews. Geovisualization has been investigated to see if it can contribute an increased understanding and better navigation in a space that mimics the physical world, as well as investigate potential problems to find future improvements. The results proved that navigation and information overload were recurring problems during the tests of the existing system. For the geovisualizations, the results proved the opposite as they instead facilitated the understanding of navigation and information. However, some problems were identified for the developed geovisualizations, such as its limited interaction and misinterpretations of objects. Despite this, it proved to be advantageous to place units in their real environment using geovisualization as it contributed to a better overview and understanding of the system's context.

The musiXplora is an interactive and multimodal tool for the domain of musicology, developed in a collaborative and interdisciplinary fashion. It serves as a research environment that, on the one hand, links large data collections on musicians, musical instruments, events and more, and, on the other hand, offers a set of visualizations which allow users to explore and analyze these data sets comprehensively. In this paper, we discuss our recent work to emphasize the relevance of geovisualizations in the musicological domain and provide detailed insights into how the musiXplora can be used to address geospatial research questions. We introduce two distinct use cases and discuss how musicologists can use the musiXplora’s geovisualizations as distant-reading tools. Thereby we demonstrate how the musiXplora can contribute to the confirmation of existing hypotheses and to the formulation of new ones.

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets.

Die vorliegende Masterarbeit behandelt den Entwurf und die exemplarische Umsetzung eines Arbeitsablaufs zur Aufbereitung von georeferenziertem Microblogging Content. Als beispielhafte Datenquelle wurde Twitter herangezogen. Darauf basierend, wurden Überlegungen angestellt, welche Arbeitsschritte nötig und mit welchen Mitteln sie am besten realisiert werden können. Dabei zeigte sich, dass eine ganze Reihe von Bausteinen aus dem Bereich des Data Mining und des Text Mining für eine Pipeline bereits vorhanden sind und diese zum Teil nur noch mit den richtigen Einstellungen aneinandergereiht werden müssen. Zwar kann eine logische Reihenfolge definiert werden, aber weitere Anpassungen auf die Fragestellung und die verwendeten Daten können notwendig sein. Unterstützt wird dieser Prozess durch verschiedenen Visualisierungen mittels Histogrammen, Wortwolken und Kartendarstellungen. So kann neues Wissen entdeckt und nach und nach die Parametrisierung der Schritte gemäß den Prinzipien des Geovisual Analytics verfeinert werden. Für eine exemplarische Umsetzung wurde nach der Betrachtung verschiedener Softwareprodukte die für statistische Anwendungen optimierte Programmiersprache R ausgewählt. Abschließend wurden die Software mit Daten von Twitter und Flickr evaluiert. / This Master's Thesis deals with the conception and exemplary implementation of a workflow for georeferenced Microblogging Content. Data from Twitter is used as an example and as a starting point to think about how to build that workflow. In the field of Data Mining and Text Mining, there was found a whole range of useful software modules that already exist. Mostly, they only need to get lined up to a process pipeline using appropriate preferences. Although a logical order can be defined, further adjustments according to the research question and the data are required. The process is supported by different forms of visualizations such as histograms, tag clouds and maps. This way new knowledge can be discovered and the options for the preparation can be improved. This way of knowledge discovery is already known as Geovisual Analytics. After a review of multiple existing software tools, the programming language R is used to implement the workflow as this language is optimized for solving statistical problems. Finally, the workflow has been tested using data from Twitter and Flickr.

Ecossistemas marinhos costeiros são explorados por diversas atividades, como a portuária e a pesqueira, gerando impactos ambientais, além de interferências entre elas, visto que, frequentemente, apresentam sobreposição espacial na área de atuação. A identificação e avaliação dos padrões espaço-temporais e interações entre essas atividades são de extrema importância para a realização de um manejo eficaz, considerando os diversos usos de forma integrada. Esta Tese visa avaliar espaçotemporalmente a variação da pesca de arrasto-duplo de pequeno porte, e na abundância de sua espécie alvo, o camarão-sete-barbas (Xiphopenaeus kroyeri), na região do Porto de Santos, SP, Brasil, e áreas adjacentes, durante um período de 6 anos (2009 a 2014). Modelos lineares generalizados foram aplicados aos dados de captura e esforço pesqueiro da espécie, e a partir dos coeficientes destes, foi calculada a captura-por-unidade-de-esforço (CPUE; kg/ dia de pesca) padronizada por célula de 1 milha náutica (MN) de lado e ano, a qual é representativa da abundância da espécie. Técnicas de semivariograma e krigagem foram utilizadas para avaliar a existência de dependência espacial nos dados e estimar os valores da CPUE em locais não amostrados. Geovisualizações tridimensionais interativas foram aplicadas para identificar padrões espaço-temporais na variação das áreas preferenciais das pescarias e da abundância da espécie. Foram ajustados modelos esféricos de semivariograma, os quais mostraram padrão de dependência espacial e foram utilizados para estimar a abundância da espécie nos vazios amostrais. Conclui-se que, durante o período analisado as operações de pesca de arrasto-duplo de pequeno porte, na área de interferência do porto de Santos, apresentaram padrões de variação espaço-temporal relacionados ás mudanças nas atividades portuárias. Por sua vez, não foi identificado um padrão na variação espaço-temporal da abundância de sua espécie alvo, o camarão-sete-barbas, na região. / Coastal marine ecosystems around the world are exploited by various activities, including serving as ports and supporting fishing, which create important environmental impacts. These activities can interfere with each other because they often have spatial overlap. Identify and evaluate the spatiotemporal patterns and interactions between the activities is of great importance for a coastal management that considers the different uses in a integrate way. This thesis aims to evaluate the spatiotemporal variability in small double-trawl fisheries, and in the abundance of its target species, the Seabob shrimp (Xiphopenaeus kroyeri), in a region with port activity and adjacent environmental protection areas, during a 6-year period (2009 to 2014). Generalized linear models were applied to the catch, and effort data and model coefficients were used to calculate the catch per unit effort (CPUE, kg/fishing day) standardized per square nautical mile and year. Semivariogram and kriging techniques were used to evaluate the existence of spatial dependence in the data and to estimate the standardized CPUE in unsampled areas. Interactive three-dimensional geovisualization were applied to identify spatiotemporal patterns in fishing operations and in the species abundance. Spherical isotropic semivariogram models that showed a pattern of spatial dependence were fitted and used to estimate the species abundance in unsampled areas. It is concluded that, during the analyzed period, the small double-trawl fisheries operations in the port of Santos presented spatiotemporal patterns that are related to changes in port activities. On the other hand, a spatiotemporal pattern variation on the abundance of its target species, the Seabob shrimp, was not identified in the region.

In recent years emotion-related applications like smartphone apps that document and analyse the emotions of the user, have become very popular. But research also can deal with human emotions in a very technology-driven approach. Thus space-related emotions are of interest as well which can be visualised cartographically and can be captured in different ways. The research project of this dissertation deals with the extraction of georeferenced emotions from the written language in the metadata of Flickr and Panoramio photos, thus from user-generated content, as well as with their modelling and visualisation. Motivation is the integration of an emotional component into location-based services for tourism since only factual information is considered thus far although places have an emotional impact. The metadata of those user-generated photos contain descriptions of the place that is depicted within the respective picture. The words used have affective connotations which are determined with the help of emotional word lists. The emotion that is associated with the particular word in the word list is described on the basis of the two dimensions ‘valence’ and ‘arousal’. Together with the coordinates of the respective photo, the extracted emotion forms a georeferenced emotion. The algorithm that was developed for the extraction of these emotions applies different approaches from the field of computer linguistics and considers grammatical special cases like the amplification or negation of words. The algorithm was applied to a dataset of Flickr and Panoramio photos of Dresden (Germany). The results are an emotional characterisation of space which makes it possible to assess and investigate specific features of georeferenced emotions. These features are especially related to the temporal dependence and the temporal reference of emotions on one hand; on the other hand collectively and individually perceived emotions have to be distinguished. As a consequence, a place does not necessarily have to be connected with merely one emotion but possibly also with several. The analysis was carried out with the help of different cartographic visualisations. The temporal occurrence of georeferenced emotions was examined detailed. Hence the dissertation focuses on fundamental research into the extraction of space-related emotions from georeferenced user-generated content as well as their visualisation. However as an outlook, further research questions and core themes are identified which arose during the investigations. This shows that this subject is far from being exhausted. / In den letzten Jahren sind emotionsbezogene Anwendungen, wie Apps, die die Emotionen des Nutzers dokumentieren und analysieren, sehr populär geworden. Ebenfalls in der Forschung sind Emotionen in einem sehr technologiegetriebenen Ansatz ein Thema. So auch ortsbezogene Emotionen, die sich somit kartographisch darstellen lassen und auf verschiedene Art und Weisen gewonnen werden können. Das Forschungsvorhaben der Dissertation befasst sich mit der Extraktion von georeferenzierten Emotionen aus geschriebener Sprache unter Verwendung von Metadaten verorteter Flickr- und Panoramio-Fotos, d.h. aus nutzergenerierten Inhalten, sowie deren Modellierung und Visualisierung. Motivation hierfür ist die Einbindung einer emotionalen Komponente in ortsbasierte touristische Dienste, da diese bisher nur faktische Informationen berücksichtigen, obwohl Orte durchaus eine emotionale Wirkung haben. Die Metadaten dieser nutzergenerierten Inhalte stellen Beschreibungen des auf dem Foto festgehaltenen Ortes dar. Die dafür verwendeten Wörter besitzen affektive Konnotationen, welche mit Hilfe emotionaler Wortlisten ermittelt werden. Die Emotion, die mit dem jeweiligen Wort in der Wortliste assoziiert wird, wird anhand der zwei Dimensionen Valenz und Erregung beschrieben. Die extrahierten Emotionen bilden zusammen mit der geographischen Koordinate des jeweiligen Fotos eine georeferenzierte Emotion. Der zur Extraktion dieser Emotionen entwickelte Algorithmus bringt verschiedene Ansätze aus dem Bereich der Computerlinguistik zum Einsatz und berücksichtigt ebenso grammatikalische Sonderfälle, wie Intensivierung oder Negation von Wörtern. Der Algorithmus wurde auf einen Datensatz von Flickr- und Panoramio-Fotos von Dresden angewendet. Die Ergebnisse stellen eine emotionale Raumcharakterisierung dar und ermöglichen es, spezifische Eigenschaften verorteter Emotionen festzustellen und zu untersuchen. Diese Eigenschaften beziehen sich sowohl auf die zeitliche Abhängigkeit und den zeitlichen Bezug von Emotionen, als auch darauf, dass zwischen kollektiv und individuell wahrgenommenen Emotionen unterschieden werden muss. Das bedeutet, dass ein Ort nicht nur mit einer Emotion verbunden sein muss, sondern möglicherweise auch mit mehreren. Die Auswertung erfolgte mithilfe verschiedener kartographischer Visualisierungen. Eingehender wurde das zeitliche Auftreten der ortsbezogenen Emotionen untersucht. Der Fokus der Dissertation liegt somit auf der Grundlagenforschung zur Extraktion verorteter Emotionen aus georeferenzierten nutzergenerierten Inhalten sowie deren Visualisierung. Im Ausblick werden jedoch weitere Fragestellungen und Schwerpunkte genannt, die sich im Laufe der Untersuchungen ergeben haben, womit gezeigt wird, dass dieses Forschungsgebiet bei Weitem noch nicht ausgeschöpft ist.

Ecossistemas marinhos costeiros são explorados por diversas atividades, como a portuária e a pesqueira, gerando impactos ambientais, além de interferências entre elas, visto que, frequentemente, apresentam sobreposição espacial na área de atuação. A identificação e avaliação dos padrões espaço-temporais e interações entre essas atividades são de extrema importância para a realização de um manejo eficaz, considerando os diversos usos de forma integrada. Esta Tese visa avaliar espaçotemporalmente a variação da pesca de arrasto-duplo de pequeno porte, e na abundância de sua espécie alvo, o camarão-sete-barbas (Xiphopenaeus kroyeri), na região do Porto de Santos, SP, Brasil, e áreas adjacentes, durante um período de 6 anos (2009 a 2014). Modelos lineares generalizados foram aplicados aos dados de captura e esforço pesqueiro da espécie, e a partir dos coeficientes destes, foi calculada a captura-por-unidade-de-esforço (CPUE; kg/ dia de pesca) padronizada por célula de 1 milha náutica (MN) de lado e ano, a qual é representativa da abundância da espécie. Técnicas de semivariograma e krigagem foram utilizadas para avaliar a existência de dependência espacial nos dados e estimar os valores da CPUE em locais não amostrados. Geovisualizações tridimensionais interativas foram aplicadas para identificar padrões espaço-temporais na variação das áreas preferenciais das pescarias e da abundância da espécie. Foram ajustados modelos esféricos de semivariograma, os quais mostraram padrão de dependência espacial e foram utilizados para estimar a abundância da espécie nos vazios amostrais. Conclui-se que, durante o período analisado as operações de pesca de arrasto-duplo de pequeno porte, na área de interferência do porto de Santos, apresentaram padrões de variação espaço-temporal relacionados ás mudanças nas atividades portuárias. Por sua vez, não foi identificado um padrão na variação espaço-temporal da abundância de sua espécie alvo, o camarão-sete-barbas, na região. / Coastal marine ecosystems around the world are exploited by various activities, including serving as ports and supporting fishing, which create important environmental impacts. These activities can interfere with each other because they often have spatial overlap. Identify and evaluate the spatiotemporal patterns and interactions between the activities is of great importance for a coastal management that considers the different uses in a integrate way. This thesis aims to evaluate the spatiotemporal variability in small double-trawl fisheries, and in the abundance of its target species, the Seabob shrimp (Xiphopenaeus kroyeri), in a region with port activity and adjacent environmental protection areas, during a 6-year period (2009 to 2014). Generalized linear models were applied to the catch, and effort data and model coefficients were used to calculate the catch per unit effort (CPUE, kg/fishing day) standardized per square nautical mile and year. Semivariogram and kriging techniques were used to evaluate the existence of spatial dependence in the data and to estimate the standardized CPUE in unsampled areas. Interactive three-dimensional geovisualization were applied to identify spatiotemporal patterns in fishing operations and in the species abundance. Spherical isotropic semivariogram models that showed a pattern of spatial dependence were fitted and used to estimate the species abundance in unsampled areas. It is concluded that, during the analyzed period, the small double-trawl fisheries operations in the port of Santos presented spatiotemporal patterns that are related to changes in port activities. On the other hand, a spatiotemporal pattern variation on the abundance of its target species, the Seabob shrimp, was not identified in the region.

Communicating science in three-dimensional (3D) multimedia is an immersive and interactive way to explore scientific processes (Signals and Communication Technology, 2019). Geovisualization is an emerging 3D multimedia method for visual analysis, synthesis, and presentation of geospatial, geologic, and geophysical data (MacEachren & Kraak, 2001). There is an identified need to develop scientific communication tools to further understand boreal peatland evolution, hydrogeology, ecology, and geochemistry (Bubier et al., 2003) since the International Union of Conservation of Nature asserts that peatlands are among the most valuable ecosystems on Earth, critical for preserving global biodiversity, providing drinking water, minimising flood risk, preventing wildfire, and mitigating climate change (Hama et al., 2000). The intention of this thesis is to communicate a novel approach to geovisualize boreal peatland architecture using Light Detection and Ranging (LiDAR) and Ground Penetrating Radar (GPR). GPR and LiDAR have been used to create 3D subsurface geovisualizations for archaeology (Kenady et al., 2018; Schultz & Martin, 2011) and resource geology (Corradini et al., 2020; Koyan & Tronicke, 2020) although application to peatland hydrogeology is uncommon. Point-source hydrogeological and geochemical data were integrated with 3D geological models to estimate carbon and nitrogen storage in an archetypal boreal peatland near Mariana Lakes, Alberta. Peatland geometry resembled a shallow lake basin with depths greatest in fens (>10 m) and thinnest in bogs (<2 m). Hydraulic conductivity was only a few meters per year and vertical groundwater movement was limited. Sequestered carbon and nutrients increased with depth. The average concentration of dissolved ammonium was 3 grams per cubic metre of peat (g/m3), 5g/m3of Total Kjeldahl Nitrogen, 60g/m3 of dissolved organic carbon and 200g/m3 of dissolved inorganic carbon. Tritium detection from atmospheric atomic weapons radionuclide fallout revealed that in deeper anaerobic peat (catotelm), tritium was absent, signifying groundwater was older than 50 years and not mixed with meteoric waters. Fen catotelm channels are likely acting as gravity-driven hydraulic traps (Tóth, 1999). / Graduate

In recent years emotion-related applications like smartphone apps that document and analyse the emotions of the user, have become very popular. But research also can deal with human emotions in a very technology-driven approach. Thus space-related emotions are of interest as well which can be visualised cartographically and can be captured in different ways. The research project of this dissertation deals with the extraction of georeferenced emotions from the written language in the metadata of Flickr and Panoramio photos, thus from user-generated content, as well as with their modelling and visualisation. Motivation is the integration of an emotional component into location-based services for tourism since only factual information is considered thus far although places have an emotional impact. The metadata of those user-generated photos contain descriptions of the place that is depicted within the respective picture. The words used have affective connotations which are determined with the help of emotional word lists. The emotion that is associated with the particular word in the word list is described on the basis of the two dimensions ‘valence’ and ‘arousal’. Together with the coordinates of the respective photo, the extracted emotion forms a georeferenced emotion. The algorithm that was developed for the extraction of these emotions applies different approaches from the field of computer linguistics and considers grammatical special cases like the amplification or negation of words. The algorithm was applied to a dataset of Flickr and Panoramio photos of Dresden (Germany). The results are an emotional characterisation of space which makes it possible to assess and investigate specific features of georeferenced emotions. These features are especially related to the temporal dependence and the temporal reference of emotions on one hand; on the other hand collectively and individually perceived emotions have to be distinguished. As a consequence, a place does not necessarily have to be connected with merely one emotion but possibly also with several. The analysis was carried out with the help of different cartographic visualisations. The temporal occurrence of georeferenced emotions was examined detailed. Hence the dissertation focuses on fundamental research into the extraction of space-related emotions from georeferenced user-generated content as well as their visualisation. However as an outlook, further research questions and core themes are identified which arose during the investigations. This shows that this subject is far from being exhausted.:Statement of Authorship I Acknowledgements II Abstract III Zusammenfassung V Table of Contents VII List of Figures XI List of Tables XIV List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Research Questions 3 1.3 Thesis Structure 4 1.4 Underlying Publications 4 2 State of the Art 6 2.1 Emotions 6 2.1.1 Definitions and Terms 6 2.1.2 Emotion Theories 7 2.1.2.1 James-Lange Theory 9 2.1.2.2 Two-Factor Theory 9 2.1.3 Structuring Emotions 9 2.1.3.1 Dimensional Approaches 10 2.1.3.2 Basic Emotions 11 2.1.3.3 Empirical Similarity Categories 12 2.1.4 Acquisition of Emotions 14 2.1.4.1 Verbal Procedures 14 2.1.4.2 Non-Verbal Procedures 14 2.1.5 Relation between Emotions and Places 15 2.1.6 Emotions in Language 17 2.1.7 Affect Analysis and Sentiment Analysis 20 2.2 User-Generated Content 22 2.2.1 Definition and Characterisation 22 2.2.2 Advantages and Disadvantages 23 2.2.3 Tagging 24 2.2.4 Inaccuracies 28 2.2.5 Flickr and Panoramio 29 2.2.5.1 Flickr 30 2.2.5.2 Panoramio 31 2.3 Related Work on Georeferenced Emotions 32 2.3.1 Emotional Data Resulting from Biometric Measurements 33 2.3.1.1 Bio Mapping 33 2.3.1.2 EmBaGIS 34 2.3.1.3 Ein emotionales Kiezportrait 35 2.3.2 Emotional Data Resulting from Empirical Surveys 35 2.3.2.1 EmoMap 35 2.3.2.2 WiMo 36 2.3.2.3 ECDESUP 37 2.3.2.4 Map of World Happiness 38 2.3.2.5 Emotional Study of Yeongsan River Basin 39 2.3.3 Emotional Data Resulting from User-Generated Content 40 2.3.3.1 Emography 40 2.3.3.2 Twittermood 40 2.3.3.3 Tweetbeat 42 2.3.3.4 Beautiful picture of an ugly place 42 2.3.4 Visualisation in the Related Work 43 3 Methods 45 3.1 Approach for Extracting Georeferenced Emotions from the Metadata of Flickr and Panoramio Photos 45 3.2 Implemented Algorithm 45 3.3 Grammatical Special Cases 47 3.3.1 Degree Words 48 3.3.2 Negation 52 3.3.2.1 Syntactic Negation in English Language 55 3.3.2.2 Syntactic Negation in German Language 57 3.3.3 Modification of Words Affected by Grammatical Special Cases 60 4 Visualisation and Analysis of Extracted Georeferenced Emotions 62 4.1 Data Basis 62 4.2 Density Maps 67 4.3 Inverse Distance Weight 71 4.4 3D Visualisation 73 4.5 Choropleth Mapping 74 4.6 Point Symbols 78 4.7 Impact of Considering Grammatical Special Cases 80 5 Investigation in Temporal Aspects 85 5.1 Annually Occurrence of Emotions 85 5.2 Periodic Events 87 5.3 Single Events 91 5.4 Dependence of Georeferenced Emotions on Different Periods of Time 93 5.4.1 Seasons 95 5.4.2 Months 96 5.4.3 Weekdays 98 5.4.4 Times of Day 99 5.5 Potentials and Limits of Temporal Analyses 99 6 Discussion 100 6.1 Evaluation 100 6.2 Weaknesses and Problems 102 7 Conclusions and Outlook 105 7.1 Answers to the Research Questions 105 7.2 Outlook and Future Work 107 8 Bibliography 112 Appendices XVI / In den letzten Jahren sind emotionsbezogene Anwendungen, wie Apps, die die Emotionen des Nutzers dokumentieren und analysieren, sehr populär geworden. Ebenfalls in der Forschung sind Emotionen in einem sehr technologiegetriebenen Ansatz ein Thema. So auch ortsbezogene Emotionen, die sich somit kartographisch darstellen lassen und auf verschiedene Art und Weisen gewonnen werden können. Das Forschungsvorhaben der Dissertation befasst sich mit der Extraktion von georeferenzierten Emotionen aus geschriebener Sprache unter Verwendung von Metadaten verorteter Flickr- und Panoramio-Fotos, d.h. aus nutzergenerierten Inhalten, sowie deren Modellierung und Visualisierung. Motivation hierfür ist die Einbindung einer emotionalen Komponente in ortsbasierte touristische Dienste, da diese bisher nur faktische Informationen berücksichtigen, obwohl Orte durchaus eine emotionale Wirkung haben. Die Metadaten dieser nutzergenerierten Inhalte stellen Beschreibungen des auf dem Foto festgehaltenen Ortes dar. Die dafür verwendeten Wörter besitzen affektive Konnotationen, welche mit Hilfe emotionaler Wortlisten ermittelt werden. Die Emotion, die mit dem jeweiligen Wort in der Wortliste assoziiert wird, wird anhand der zwei Dimensionen Valenz und Erregung beschrieben. Die extrahierten Emotionen bilden zusammen mit der geographischen Koordinate des jeweiligen Fotos eine georeferenzierte Emotion. Der zur Extraktion dieser Emotionen entwickelte Algorithmus bringt verschiedene Ansätze aus dem Bereich der Computerlinguistik zum Einsatz und berücksichtigt ebenso grammatikalische Sonderfälle, wie Intensivierung oder Negation von Wörtern. Der Algorithmus wurde auf einen Datensatz von Flickr- und Panoramio-Fotos von Dresden angewendet. Die Ergebnisse stellen eine emotionale Raumcharakterisierung dar und ermöglichen es, spezifische Eigenschaften verorteter Emotionen festzustellen und zu untersuchen. Diese Eigenschaften beziehen sich sowohl auf die zeitliche Abhängigkeit und den zeitlichen Bezug von Emotionen, als auch darauf, dass zwischen kollektiv und individuell wahrgenommenen Emotionen unterschieden werden muss. Das bedeutet, dass ein Ort nicht nur mit einer Emotion verbunden sein muss, sondern möglicherweise auch mit mehreren. Die Auswertung erfolgte mithilfe verschiedener kartographischer Visualisierungen. Eingehender wurde das zeitliche Auftreten der ortsbezogenen Emotionen untersucht. Der Fokus der Dissertation liegt somit auf der Grundlagenforschung zur Extraktion verorteter Emotionen aus georeferenzierten nutzergenerierten Inhalten sowie deren Visualisierung. Im Ausblick werden jedoch weitere Fragestellungen und Schwerpunkte genannt, die sich im Laufe der Untersuchungen ergeben haben, womit gezeigt wird, dass dieses Forschungsgebiet bei Weitem noch nicht ausgeschöpft ist.:Statement of Authorship I Acknowledgements II Abstract III Zusammenfassung V Table of Contents VII List of Figures XI List of Tables XIV List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Research Questions 3 1.3 Thesis Structure 4 1.4 Underlying Publications 4 2 State of the Art 6 2.1 Emotions 6 2.1.1 Definitions and Terms 6 2.1.2 Emotion Theories 7 2.1.2.1 James-Lange Theory 9 2.1.2.2 Two-Factor Theory 9 2.1.3 Structuring Emotions 9 2.1.3.1 Dimensional Approaches 10 2.1.3.2 Basic Emotions 11 2.1.3.3 Empirical Similarity Categories 12 2.1.4 Acquisition of Emotions 14 2.1.4.1 Verbal Procedures 14 2.1.4.2 Non-Verbal Procedures 14 2.1.5 Relation between Emotions and Places 15 2.1.6 Emotions in Language 17 2.1.7 Affect Analysis and Sentiment Analysis 20 2.2 User-Generated Content 22 2.2.1 Definition and Characterisation 22 2.2.2 Advantages and Disadvantages 23 2.2.3 Tagging 24 2.2.4 Inaccuracies 28 2.2.5 Flickr and Panoramio 29 2.2.5.1 Flickr 30 2.2.5.2 Panoramio 31 2.3 Related Work on Georeferenced Emotions 32 2.3.1 Emotional Data Resulting from Biometric Measurements 33 2.3.1.1 Bio Mapping 33 2.3.1.2 EmBaGIS 34 2.3.1.3 Ein emotionales Kiezportrait 35 2.3.2 Emotional Data Resulting from Empirical Surveys 35 2.3.2.1 EmoMap 35 2.3.2.2 WiMo 36 2.3.2.3 ECDESUP 37 2.3.2.4 Map of World Happiness 38 2.3.2.5 Emotional Study of Yeongsan River Basin 39 2.3.3 Emotional Data Resulting from User-Generated Content 40 2.3.3.1 Emography 40 2.3.3.2 Twittermood 40 2.3.3.3 Tweetbeat 42 2.3.3.4 Beautiful picture of an ugly place 42 2.3.4 Visualisation in the Related Work 43 3 Methods 45 3.1 Approach for Extracting Georeferenced Emotions from the Metadata of Flickr and Panoramio Photos 45 3.2 Implemented Algorithm 45 3.3 Grammatical Special Cases 47 3.3.1 Degree Words 48 3.3.2 Negation 52 3.3.2.1 Syntactic Negation in English Language 55 3.3.2.2 Syntactic Negation in German Language 57 3.3.3 Modification of Words Affected by Grammatical Special Cases 60 4 Visualisation and Analysis of Extracted Georeferenced Emotions 62 4.1 Data Basis 62 4.2 Density Maps 67 4.3 Inverse Distance Weight 71 4.4 3D Visualisation 73 4.5 Choropleth Mapping 74 4.6 Point Symbols 78 4.7 Impact of Considering Grammatical Special Cases 80 5 Investigation in Temporal Aspects 85 5.1 Annually Occurrence of Emotions 85 5.2 Periodic Events 87 5.3 Single Events 91 5.4 Dependence of Georeferenced Emotions on Different Periods of Time 93 5.4.1 Seasons 95 5.4.2 Months 96 5.4.3 Weekdays 98 5.4.4 Times of Day 99 5.5 Potentials and Limits of Temporal Analyses 99 6 Discussion 100 6.1 Evaluation 100 6.2 Weaknesses and Problems 102 7 Conclusions and Outlook 105 7.1 Answers to the Research Questions 105 7.2 Outlook and Future Work 107 8 Bibliography 112 Appendices XVI