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The patterns, motivations, and consequences of the outmigration of young adults from rural areas is a classic topic in population geography. In our paper, we first take a critical look at statistical analyses and cartographic representations of migration patterns of young adults in rural areas using Central Germany "Central Germany" is frequently used as an umbrella term for the southern part of eastern Germany, i.e. the federal states of Saxony, Saxony-Anhalt, and Thuringia. as an example, stressing the shortcomings of quantitative analyses of residential mobility. We argue that migration is a complex social process, taking place as the result of the interplay of demographic, socio-structural, political, economic, and production-related factors involving the mobile individuals, as well as other actors, discourses, and practices. Following this, we discuss the emergence of cultures of (out-)migration in rural areas characterised by heightened mobility over longer periods of time and possible approaches to analyse such regional phenomena. We hence aim at a deepening of the concept of "culture of migration" and an expansion of the debate on motives and practices of migration to include psychological approaches, as well as a complex systems perspective. [ABSTRACT FROM AUTHOR]

Today's methods for data acquisition usually involve a considerable amount of manual work and, depending on the level of detail, must find a compromise between accuracy and workload. As a result, various typologies of building stocks have been developed. These typologies provide engineers and architects with rough descriptions for classifying buildings into certain periods and construction types. However, real-world applications lack objective decision-making, as these classifications are usually conducted by manual investigations of buildings. To overcome this subjective approach and to ensure the reproducibility of data acquisition, this paper proposes an image-based classification using Deep Learning (DL) methods. We present the acquisition of ground truth and describe the training and testing routines on a dataset of 5,307 images obtained in the city of Weimar (located in the Free State of Thuringia, Germany), a mid-sized city representative of eastern Germany. All building images are linked to an existing building typology, allowing a classification of buildings in ten predefined and acknowledged periods. These periods are ranging from pre-1859 to post-2002. As a benchmark, an expert human baseline is acquired, showing a lower prediction accuracy than the results obtained by DL methods. Our results highlight the potential for automation in image analysis and beneficial impacts for Building Energy Modeling (BEM) on urban scale. Thus, a trustworthy data acquisition regarding the building age holds benefits for various stakeholders in BEM (engineers, architects, policymakers as well as customers). • Two CNN-architectures (ResNet50 and AlexNet) are used for image-classification. • Extraction of annotated image-patches facilitates an enhancement of the image set. • Quantity of training images and applied optimizer significantly influence results. • CNN-based estimations successfully linked to existing and popular building typology. • Accuracies of CNN-based estimation of building age outperform the human baseline. [ABSTRACT FROM AUTHOR]

During the past twenty years, the emphasis of policy towards high-technology industry has shifted from national innovation systems to take account of globalisation and the formation of regional clusters. Support for high-technology sectors now takes place at a number of levels— regional, national, and international. However, the extent to which firms operate in these three arenas, and how relevant government action is for the needs and behaviour of firms in respect of these is open to question. The paper reports on a study into innovation in Germany and the United Kingdom, in a particular industry—opto-electronics—which has a highly global character, but is also characterised by concentrations of firms in clusters. The contrasting experiences of firms in two regions—Wales and Thuringia—and the different policy emphasis of the regional government provide a test for the relevance, appropriateness, and impact of government policies towards high-technology industry. By focusing on the experiences of innovating firms, the authors provide a conceptually rich understanding of innovation in terms of two processes, which are often conflated in public policy stimulating knowledge and technology transfer, and providing resource support. The paper concludes with a suggestion that support for innovation needs to be based around the twin concepts of redundancy and systems thinking, and a series of questions policymakers need to keep in mind are proposed. [ABSTRACT FROM AUTHOR]

The linkage of suicide and crisis was a prominent feature of Weimar Germany's cultural landscape. In films as different as Bertolt Brecht and Slatan Dudow's Kuhle Wampe or Walter Ruttmann's Berlin: Symphony of a Big City, suicide appears as a reaction to the darker aspects of urban modernity: an individual's answer to capitalist exploitation or personal drama in an otherwise smoothly functioning metropolis. In a number of contemporary novels the possibility of a suicide is disturbingly present. In Vicki Baum's Grand Hotel, one character asks himself, “My God, does everyone now have his tea cup of veronal ready?” Tales of suicide also surfaced in the tabloid press which presented them as human interest stories. Partisan papers supported their respective stances by tying individual actions to political narratives, a strategy pursued by both Nazis and Communists as well as liberal reformers. Even schools' reports on pupils who had taken their own lives and farewell notes themselves echoed a general feeling that suicide was a sign of the times. [ABSTRACT FROM AUTHOR]

This paper gives an introduction to composition, creation, and management of knowledge using a long-term research project as an example. The concept and first experiences for a web-based knowledge management system (KMS) of the regeneration process of the stream Ilm (Thuringia, Germany) are presented. From 1996 until 2005, this restoration ecology project investigated whether the river ecosystem can attain its natural state again and how the regeneration can be influenced. The web-based content management system iZone, with an emphasis on information retrieval and feedback, was used to support the process of storage, retrieval, and visualization of existing information, several Ph.D. studies, and expert knowledge in the concluding phase of the research project. The resulting KMS at the moment stores 90 entries from 35 project scientists. [ABSTRACT FROM AUTHOR]

This paper describes results of partial destratification of a large reservoir with complex morphology. In order to reduce phytoplankton growth by light limitation, the upper 20 m of the water column were destratified in the Bleiloch Reservoir (Thuringia, Germany). Temperatures, phytoplankton, and zooplankton were investigated before and during aeration to determine the effects of the partial destratification on plankton. The measure induced an increase of phytoplankton dynamics. Since 1991 nuisance cyanobacteria blooms increased in the hypertrophic Bleiloch reservoir (Thuringia, Federal Republic of Germany), as light conditions improved due to a reduction of coloured wastewaters supplied by a cellulose mill. Warm inflowing water formed an upper layer, which reached the bubble plume near the dam, and was only weakly affected by the deeper mixed water body. The water column stability decreased, which caused an overturn 2–3 weeks earlier, because the hypolimnion warmed up faster. These physical effects of the destratification delayed the seasonal succession of phytoplankton. Cyanobacteria were suppressed but diatoms and chlorophytes became more abundant. Copepods maintained higher population densities throughout the summer. During artificial mixing, the algal diversity increased, not only because k-strategists selected a stratified water column, but also because episodic thermal instability enabled r- and k-strategists to co-exist in a competitive environment. [ABSTRACT FROM AUTHOR]

Lidar remote sensing has proven to be a powerful tool for estimating ground elevation, canopy height, and additional vegetation parameters, which in turn are valuable information for the investigation of ecosystems. Spaceborne lidar systems, like the Global Ecosystem Dynamics Investigation (GEDI), can deliver these height estimates on a near global scale. This paper analyzes the accuracy of the first version of GEDI ground elevation and canopy height estimates in two study areas with temperate forests in the Free State of Thuringia, central Germany. Digital terrain and canopy height models derived from airborne laser scanning data are used as reference heights. The influence of various environmental and acquisition parameters (e.g., canopy cover, terrain slope, beam type) on GEDI height metrics is assessed. The results show a consistently high accuracy of GEDI ground elevation estimates under most conditions, except for areas with steep slopes. GEDI canopy height estimates are less accurate and show a bigger influence of some of the included parameters, specifically slope, vegetation height, and beam sensitivity. A number of relatively high outliers (around 9–13% of the measurements) is present in both ground elevation and canopy height estimates, reducing the estimation precision. Still, it can be concluded that GEDI height metrics show promising results and have potential to be used as a basis for further investigations. [ABSTRACT FROM AUTHOR]