This working paper outlines analytical pathways that could contribute to deepening the understanding of water inequalities in cities of the Global South. It brings together the status quo of research on water inequalities in Accra, the capital of Ghana, and studies on Environmental Justice. In doing so, it argues for the need to analytically distinguish between the terms ‘(in)equality’ and ‘(in)justice’. Studying everyday water practices and per- spectives on water (in)justice of different stakeholders would be a suitable entry point for an in-depth ethnographic study that analytically separates water inequalities and water injustices but considers their interlinkages. The working paper is based on a literature review conducted in 2015 in the scope of the WaterPower project.

In der kleinen ostfriesischen Kirchengemeinde W. hat sich im Jahr 1969 ein plötzlicher Todesfall ereignet. Fremdverschulden wird ausgeschlossen. Jemand, der die Hintergründe des Todesfalls aufklären will, stößt allenthalben auf – bisweilen gar aggressives – Schweigen. Eine Geschichte über individuelle und kollektive Schuld, lutherische Kirchenmusik und den Wert, den wir der Kultur und der Tradition beimessen. Ausgezeichnet mit dem Borsla-Preis 2019.

Global food security poses large challenges to a fast changing human society and has been a key topic for scientists, agriculturist, and policy makers in the 21st century. The United Nation predicts a total world population of 9.15 billion in 2050 and defines the provision of food security as the second major point in the UN Sustainable Development Goals. As the capacities of both, land and water resources, are finite and locally heavily overused, reducing agriculture’s environmental impact while meeting an increasing demand for food of a constantly growing population is one of the greatest challenges of our century. Therefore, a multifaceted solution is required, including approaches using geospatial data to optimize agricultural food production. The availability of precise and up-to-date information on vegetation parameters is mandatory to fulfill the requirements of agricultural applications. Direct field measurements of such vegetation parameters are expensive and time-consuming. On the contrary, remote sensing offers a variety of techniques for a cost-effective and non-destructive retrieval of vegetation parameters. Although not widely used, hyperspectral thermal infrared (TIR) remote sensing has demonstrated being a valuable addition to existing remote sensing techniques for the retrieval of vegetation parameters. This thesis examined the potential of TIR imaging spectroscopy as an important contribution to the growing need of food security. The main scientific question dealt with the extraction of vegetation parameters from imaging TIR spectroscopy. To this end, two studies impressively demonstrated the ability of extracting vegetation related parameters from leaf emissivity spectra: (i) the discrimination of eight plant species based on their emissivity spectra and (ii) the detection of drought stress in potato plants using temperature measures and emissivity spectra. The datasets used in these studies were collected using the Telops Hyper-Cam LW, a novel imaging spectrometer. Since this FTIR spectrometer presents some particularities, special attention was paid on the development of dedicated experimental data acquisition setups and on data processing chains. The latter include data preprocessing and the development of algorithms for extracting precise surface temperatures, reproducible emissivity spectra and, in the end, vegetation parameters. The spectrometer’s versatility allows the collection of airborne imaging spectroscopy datasets. Since the general availability of airborne TIR spectrometers is limited, the preprocessing and data extraction methods are underexplored compared to reflective remote sensing. This counts especially for atmospheric correction (AC) and temperature and emissivity separation (TES) algorithms. Therefore, we implemented a powerful simulation environment for the development of preprocessing algorithms for airborne hyperspectral TIR image data. This simulation tool is designed in a modular way and includes the image data acquisition and processing chain from surface temperature and emissivity to the final at-sensor radiance data. It includes a series of available algorithms for TES, AC as well as combined AC and TES approaches. Using this simulator, one of the most promising algorithms for the preprocessing of airborne TIR data – ARTEMISS – was significantly optimized. The retrieval error of the atmospheric water vapor during the atmospheric characterization was reduced. As a result, this improvement in atmospheric characterization accuracy enhanced the subsequent retrieval of surface temperatures and surface emissivities intensely. Although, the potential of hyperspectral TIR applications in ecology, agriculture, and biodiversity has been impressively demonstrated, a serious contribution to a global provision of food security requires the retrieval of vegetation related parameters with global coverage, high spatial resolution and at high revisit frequencies. Emerging from the findings in this thesis, the spectral configuration of a spaceborne TIR spectrometer concept was developed. The sensors spectral configuration aims at the retrieval of precise land surface temperatures and land surface emissivity spectra. Complemented with additional characteristics, i.e. short revisit times and a high spatial resolution, this sensor potentially allows the retrieval of valuable vegetation parameters needed for agricultural optimizations. The technical feasibility of such a sensor concept underlines the potential contribution to the multifaceted solution required for achieving the challenging goal of guaranteeing global food security in a world of increasing population. In conclusion, thermal remote sensing and more precisely hyperspectral thermal remote sensing has been presented as a valuable technique for a variety of applications contributing to the final goal of a global food security.

In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.

This dissertation deals with consistent estimates in household surveys. Household surveys are often drawn via cluster sampling, with households sampled at the first stage and persons selected at the second stage. The collected data provide information for estimation at both the person and the household level. However, consistent estimates are desirable in the sense that the estimated household-level totals should coincide with the estimated totals obtained at the person-level. Current practice in statistical offices is to use integrated weighting. In this approach consistent estimates are guaranteed by equal weights for all persons within a household and the household itself. However, due to the forced equality of weights, the individual patterns of persons are lost and the heterogeneity within households is not taken into account. In order to avoid the negative consequences of integrated weighting, we propose alternative weighting methods in the first part of this dissertation that ensure both consistent estimates and individual person weights within a household. The underlying idea is to limit the consistency conditions to variables that emerge in both the personal and household data sets. These common variables are included in the person- and household-level estimator as additional auxiliary variables. This achieves consistency more directly and only for the relevant variables, rather than indirectly by forcing equal weights on all persons within a household. Further decisive advantages of the proposed alternative weighting methods are that original individual rather than the constructed aggregated auxiliaries are utilized and that the variable selection process is more flexible because different auxiliary variables can be incorporated in the person-level estimator than in the household-level estimator. In the second part of this dissertation, the variances of a person-level GREG estimator and an integrated estimator are compared in order to quantify the effects of the consistency requirements in the integrated weighting approach. One of the challenges is that the estimators to be compared are of different dimensions. The proposed solution is to decompose the variance of the integrated estimator into the variance of a reduced GREG estimator, whose underlying model is of the same dimensions as the person-level GREG estimator, and add a constructed term that captures the effects disregarded by the reduced model. Subsequently, further fields of application for the derived decomposition are proposed such as the variable selection process in the field of econometrics or survey statistics.

Der vorliegende Sammelband geht auf die UniGR-Fachtagung Edu.GR - Europa leben lernen / Edu.GR - Apprendre à vivre l’Europe zurück, die am 20. September 2018 an der Universität Trier stattfand. Die Beiträge befassen sich aus unterschiedlichen Perspektiven – so aus Sicht der Bildungswissenschaften, der Fachdidaktiken, der Sozialwissenschaften und der Bildungspraxis – mit der Frage der Gestaltung Europas am Beispiel der Großregion. Vorgestellt und diskutiert werden neben Konzepten transnationaler Bildung auch empirische Analysen des Denkens und Handelns der Beteiligten in grenzregionalen (Aus-)Bildungskontexten sowie ausgewählte Beispiele transnationaler Bildungspraxis.

Thema dieser Dissertation ist das deutsche Selbstbildnis im 17. Jahrhundert. Ziel der Arbeit war es, das deutsche Selbstbildnis als eigene Gattung zu etablieren. Hierzu wurden die Selbstbildnisse deutscher Maler des 17. Jahrhunderts ausgewählt, gilt doch diese Zeit noch immer als ‚totes Jahrhundert‘. Grundlage der Untersuchung war eine Sammlung von 148 Objekten, die einer grundlegenden Analyse unterzogen wurden. Das früheste Selbstbildnis in dieser Sammlung stammt von 1600, das späteste wurde um 1700 angefertigt. Künstler aus dem gesamten Alten Reich, ob aus Schlesien und Böhmen, Nord-oder Süddeutschland oder aus den österreichischen wie schweizerischen Landen sind hier vertreten. Die Selbstbildnisse stammen von Malern in der gesamten breite ihrer Karriere. So sind gleichermaßen Selbstbildnisse von Gesellen wie Meistern, von Hofmalern bis hin zu Freimeistern vertreten. Besonders wichtig war es, nicht nur Selbstbildnisse im Gemälde oder Kupferstich in die Untersuchung aufzunehmen, sondern auch Stammbucheinträge. Die ausführliche Betrachtung und Gegenüberstellung der deutschen Selbstbildnisse mit denen ihrer europäischen Kollegen hat gezeigt, dass auch deutsche Maler den gängigen Darstellungstypen wie etwa dem virtuoso folgten. Aber die deutschen Maler imitierten nicht nur, sondern experimentierten und gingen mit ihren Vorbildern spielerisch um. Daneben folgten sie natürlich auch den Trends der Selbstinszenierung. Sie drückten in ihren Selbstbildnissen ihren Wunsch nach sozialer und gesellschaftlicher Emanzipation des gesamten Berufsstandes aus. So war das deutsche Selbstbildnis eigenständiger Ausdruck des Aufbruches deutscher Künstler in eine neue Zeit.

Die Trierer Quellen- und Studienhefte zur historisch-politischen Bildung veröffentlichen Ergebnisse aktueller Forschungsprojekte und Materialien für den historisch-politischen Unterricht aus der Arbeit des Arbeitsbereichs Didaktik der Gesellschaftswissenschaften.

This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.

L’apprentissage par le projet - plus que toute autre forme d’enseignement - permet aux élèves de participer de manière autonome à l’organisation des cours. Les apprenant(e)s ne s’exercent pas seulement dans l’action autonome et responsable, mais jouent, eux aussi, un rôle actif dans la société.