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In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests. [ABSTRACT FROM AUTHOR]

The paper discusses the connection of the foundational economy approach, a contemporary concept in the public services discourse, with the notion of spatial justice. It argues that the economic relevance of the systems of the foundational economy are important for territorial development issues, too and that they are able to provide a substantial contribution to sustainable and just spatial development. First, the concept of spatial justice is introduced as a spatial planning policy interpretation of equal living conditions. Based on four sub-dimensions, it is shown that access to basic services for all people plays an elementary part in this. The concept shares this perspective with the foundational economy approach. The latter opens up a new perspective on public services and, in addition to the service provision, also emphasises the high significance of foundational economic systems for labour markets. Against this background, a descriptive-statistical evaluation of labour market data on the spatial distribution of the foundational economy at the district level in Bavaria is carried out. Overall, the paper addresses the uneven spatial distribution of the foundational economies and advocates better funding for municipalities in order to achieve spatial justice. [ABSTRACT FROM AUTHOR]

This paper argues that the judicial ordeal was the subject of a lively debate in the ninth century. Research on the medieval ordeal has mainly focused on opposition to the practice in the twelfth century, attaching little significance to earlier controversy. When Carolingian-era opinions of the ordeal are discussed, they are usually seen in terms of the later ordeal debate. Using as a case study the anonymous mid ninth-century Bavarian poem, the Song of Count Timo, this paper argues that the ninth-century ordeal debate revolved around Carolingian-era concerns, rather than twelfth-century ones. Thus, the Song of Count Timo opposed the ordeal because it saw it as undermining royal control of justice in the context of the political turbulence of the 830s. Examining the Carolingian-era ordeal debate on its own terms allows us to better understand the medieval ordeal, and also the law, politics and religious thought of the period. [ABSTRACT FROM AUTHOR]

Within this paper, a case study on the application of drone photogrammetry at the Second World War armament bunker Weingut I is presented. The aim of the project was the mapping of the preserved remains in advance to the installation of a memorial site. In particular, the preserved concrete arch and one of the ventilation shafts were mapped by this method in high quality. Therefore, even small details of the building structure as well as several damage spots needing remediation became visible. One important advantage of drone prospecting is an enhanced occupational safety and a cost and time reduction as no further manual resources are necessary. In areas without finalized clearing for Unexploded Ordnance, other manual survey method would be especially dangerous. By comparing the photogrammetric model of the bunker Weingut I with corresponding ALS Digital Surface Models (DSM) of varying resolution, the increase in information is shown. [ABSTRACT FROM AUTHOR]

Recent decades have witnessed a shift to spatial perspectives in flood risk management. It is recognized that flood protection has substantial implications for land-use plans and requires attention to the functional geographies of river basins, catchments and floodplains. It is against this background that managed retreat is increasingly identified as a viable cost-effective response to flood risk. Yet managed retreat is also a political act, involving the displacement of coastal and riverine communities. In this paper, we examine the spatial imaginaries underlying managed retreat and flood risk management through an in-depth case study of a displaced village on the Danube in Upper Bavaria, Germany. The paper provides insights into the challenges posed by diverging functional, administrative and political spatial imaginaries and how this divergence contributes to perceptions of injustice. We suggest that a shift to a more relational form of communicative planning may help to address this dilemma. [ABSTRACT FROM AUTHOR]

This paper examines the territorial development reforms in the federal state of Bavaria, Germany between 2008 and 2018 in light of the rise of austerity policies, introducing the concept of 'austere federalism' as a new state spatial process in the aftermath of the global financial crisis. Methodologically, the paper draws on the historical-materialist policy analysis and identifies three processes – municipalisation, competitisation, and responsibilisation – as key elements of a new hegemonic project. Our findings suggest that the years following the crisis saw a paradigm shift in spatial planning taking place, characterised by a carrot-and-stick policy of planning deregulation and austerity discipline. Rather than diminishing disparities, however, this shift runs the risk of exacerbating spatial inequality. [ABSTRACT FROM AUTHOR]

The available skid resistance, or friction, in a pavement surface is a vital parameter for functional evaluations of roads due to its relation with crashes. Therefore, highway administrations must collect friction data on their road network to provide safe roads to users. Additionally, a prediction model that can forecast the available skid resistance in each road segment is necessary for an efficient pavement management system (PMS). The aim of this paper is to develop a skid resistance prediction model for the bituminous pavements of the motorway network of federal state of Bavaria, in Germany, with information that is typically available in a PMS: the Annual Average Daily Traffic , the Annual Average Daily Heavy Traffic , and the number of lanes in each segment. Despite its simplicity, with 6410 road segments of 2 and 3 lanes of the Bavarian motorway network, the model achieves a determination coefficient (R2) of 0.405. If information about the surface layer material is added, R2 increases to 0.480. Consequently, apart from predicting the minimum available friction in each lane in a motorway, the study underlines the necessity that a PMS should contain the recommended elements and additional surface layer material, because the quality of the prediction improves. [ABSTRACT FROM AUTHOR]

In 1946, President Harry Truman sought to reform the German education system and appointed Bishop Aloisius Muench as the Catholic Liaison to assist the U.S. occupational forces. Simultaneously, Muench was appointed as the Vatican's official visitor to Germany. Using these roles, Muench influenced denazification and educational policies in Bavaria. Drawing on unused primary sources from Muench's personal correspondence, OMGUS files, the papers of Lucius Clay, the Christian Social Union Archives, the personal papers of Cardinal Michael von Faulhaber, and the files from the archives of the archdiocese of Munich and Freising, this article concludes that Muench played a key role in preserving Catholic schools in Bavaria. Muench's case proves that denazification policies were contested and formed by a coalition of secular and religious individuals. [ABSTRACT FROM AUTHOR]

The Ries impact is the most important cosmic event in the younger geological history of Europe. Its effects reach far beyond the area considered so far and are documented in manifold evidence. In this paper, the widely scattered reports in the literature are compiled and supported with investigations by the authors. Besides well‐known ejecta features like the Brockhorizont, Reuter's blocks, and moldavites, little known or forgotten indications, like a lechatelierite and β‐cristobalite occurrence in Bavaria and unusual sedimentation phenomena in northern Germany, are presented. The paleogeographic reconstruction shows that the Ries impact occurred on the southern side of the Neogene Central European mainland. Large parts of this erosional area were devastated by the impact. Pressure waves and thermal radiation had a lasting effect on the landscape within hundreds of kilometers around the impact site. Destruction of the vegetation cover by impact‐induced storms, wildfires, and heavy rainfall generated intense erosion. The adjacent sedimentation area to the north (Paleo‐North Sea) experienced an increased and short‐term supply of terrestrial debris to the marine environment. The stratigraphic coincidence of these exceptional sediments with the Ries event leads us to conclude that the distal effects of the impact are present here, which have so far received little or no attention in this context. The paper considers the different indications and sets them in a large‐scale context. [ABSTRACT FROM AUTHOR]

In the present paper, a flexible skew version of the scale mixture of normal family is introduced based on the transmuted record type, called TRT-SMN, which seems suitable for handling any skewness and kurtosis in real data sets. Several properties of the TRT-SMN family are provided, including the moment generating function and r-th moments. The parameters of the new family are estimated through the ECME algorithm. Further to the elegant properties of the proposed family, the paper considers, in the time series context, a first-order autoregressive process with TRT-SMN distributed innovations. Some Monte Carlo simulation experiments are executed to assess the consistency of the ECME estimates. To further motivate its purpose, the proposed process is applied to analyze the series of COVID-19 incidence in Bavaria. The proposed AR(1) with TRT-SMN innovations yields superior fitting criteria compared to AR(1) process with Gaussian innovations. [ABSTRACT FROM AUTHOR]

This paper publishes the sixty-nine surviving very personal letters that Reichsgraf von Rumford wrote to Viscountess Palmerston after they met in Milan in 1793. The letters draw attention to the private domestic spaces of science and the critical importance of the aristocracy in scientific developments, topics that have both received some discussion recently. They were, however, not written with the purpose of providing historical evidence, but as part of a decade-long friendship which the letters trace, revealing, among other things, Rumford's other amours. They also describe in some detail his thoughts about his activities as a member of the governing elite in Bavaria, his scientific and engineering researches (especially the writing and publication of his Essays), as well as what he would have termed his philanthropic efforts in Bavaria, Northern Italy, Britain, and Ireland. All this is framed within the context of the Revolutionary and Napoleonic wars that in so many ways, directly and indirectly, affected Palmerston's and Rumford's lives and work. [ABSTRACT FROM AUTHOR]

It has been widely demonstrated that pre‐ and post‐migration experiences can be highly traumatic for refugees. The purpose of this study was to assess the mediating effects of religious coping and sense of coherence on the association of negative dysfunctional situation appraisal and mental well‐being among refugees. Paper surveys were completed by 600 people representing various refugee groups (mostly from Mashreq Countries) in German Bavaria, aged 18–65. Mediation analysis revealed that negative religious coping and sense of coherence singly and serially mediated the relationship between negative dysfunctional situation appraisal and well‐being, whereas positive religious coping did not have statistically significant relationships with these variables. The data obtained suggest that the negative religious coping style and sense of coherence are two important targets for future experimental studies, and interventions on them may bring the synergistic effect on improving mental well‐being in refugees. [ABSTRACT FROM AUTHOR]

Formations of multiple satellites observe target areas on the Earth's surface from different perspectives, enabling construction of 3D surface maps by photogrammetric methods. The main objective of TOM (T elematics Earth O bservation M ission) is to monitor ash clouds during Volcanic Eruptions with a satellite formation consisting of three CubeSats. TOM is Bavaria's contribution to the multi-national T elematics I nternational M ission (TIM), composed of 7 satellites by partners from 4 continents. To achieve sufficient overlap of the images for the usage of photogrammetric methods, very precise and coordinated attitude control of the satellites is necessary. This paper presents a vision-based attitude control approach using image data to calculate the control input, also referred to as visual servoing. Thus, the cameras and data processing capacity onboard the CubeSats will be used for both image acquisition and attitude determination, eliminating the need for additional precise attitude sensors like star trackers. To perform visual servoing, highly distinctive features are identified and tracked in the images. The control input for reaction wheels is calculated from the movement of the features between consecutive images. To ensure that the images captured by the different satellites overlap sufficiently for photogrammetric processing, the satellites track the same target area based on feature data exchange directly between the satellites. Simulations of realistic scenarios based on the TOM project show the applicability of the presented attitude control approach. In a first step, a software-based Earth observation simulator generates the acquired images, demonstrating feasibility to compute and track features in satellite images to compute the AOCS (Attitude and Orbit Control System) input. In the second step, hardware-in-the-loop (HiL) simulations allow to realistically characterize the performance of this approach. This HiL environment utilizes two high-precision/high-dynamics turntables as 3-axis attitude simulators, where the satellites with their cameras are mounted, while the observation target is mounted on a mobile robot to simulate the relative orbit motion. • TOM is a CubeSat formation for the joint observation of volcanic ash clouds. • Observation from different perspectives enables the generation of 3D surface maps. • Visual servoing provides the required precise and coordinated attitude control. • The features to be tracked cooperatively are exchanged via inter-satellite link. • Software and hardware-in-the-loop simulations show the feasibility of the approach. [ABSTRACT FROM AUTHOR]

• A spatiotemporal risk prediction of wildlife-vehicle collisions (WVCs) is presented. • A Bavarian dataset of around 731,000 accidents over a period of 10 years (2010–2019) was used. • Heterogenous datasets of impact factors are pre-processed using GIS. • Different machine learning (ML) approaches are applied - random forest, feedforward neural networks, and support vector machine classifier to predict the risk of WVCs. • ML algorithms provide high risk prediction quality of over 86% (double-weighted sensitivity and single-weighted specificity rate). • Spatial transferability and temporal forecast of WVC prediction was verified. Introduction: The technology in the automotive industry is becoming increasingly safer in the age of automated driving, but the number of accidents is still high, especially in wildlife-vehicle collisions (WVCs). To better avoid these accidents, patterns involved in these accidents must be detected. Method : This paper presents a spatiotemporal risk prediction of WVCs, including various road and environmental characteristics. A process of data preparation using GIS automated by Python scripts was developed to enable a spatiotemporal link of diverse features for the subsequent predictive data analysis. Different machine learning (ML) approaches were applied- random forest (RF), feedforward neural networks (FNN), and support vector machine classifier (SVM) - including automated ML to predict the risk of WVCs. Therefore, a dataset of approximately 731,000 accidents reported to the police in Bavaria over a period of 10 years (2010–2019) was used. In addition, non-accidents were randomly generated in Python over time and space for the supervised ML processes. As the actual risk probability for WVCs and non-WVCs is not entirely known, the impact of different training ratios between accidents and non-accidents was tested on the risk prediction quality (RPQ) (25%, 50%, 75%, 90% WVCs) of the double-weighted sensitivity and single-weighted specificity rate. Results: The test yielded high mean values of RPQ as an indicator for a suitable WVC prediction. Both RF (86.6%) and FNN (86.7%) were identified as suitable choices for WVC risk prediction in terms of RPQ. The SVM yielded a lower prediction quality, even though acceptable results could be achieved within a shorter runtime. Practical Applications: Spatial transferability was verified since the algorithm was trained on the dataset of Bavaria (excluding Upper Bavaria) and successfully tested in Upper Bavaria. WVC forecasts were also proven through training with datasets from 2010-2017 and in prediction for 2018 and 2019. [ABSTRACT FROM AUTHOR]

Puqian Town, Heyuan City has beautiful natural environment and agricultural landscape and unique hot spring resources, so it is very suitable for the development of rural vacation industry. At present, there were only two vacation projects of Bavaria Manor and Ketianxia Hot Spring Resort in the town, and the radiation driving effect is not obvious. In this paper, literature research and interview methods were used to collect data. After 15 interviewees were effectively interviewed and hundreds of data were collected, the PEST theory model and balanced points card theory were used to measure the development factors of rural vacation in Puqian Town, Heyuan City. SWOT matrix matching analysis method was adopted to determine the development strategies of local rural vacation industry. [ABSTRACT FROM AUTHOR]

The present paper deals with new hyaenid material from the locality of Hammerschmiede (Bavaria, Germany). The described specimens are attributed to two forms: most of the specimens belong to the species Thalassictis montadai, whereas one I3 is attributed to a large bone-cracking hyena. The material comes from the layers HAM 5 (11.62 Ma) and HAM 6 (slightly younger than 11.44 Ma) of Hammerschmiede (base of Late Miocene). The species Thalassictis montadai is well-known from late Aragonian and early Vallesian localities of central and southern Europe and west Asia. The presented material enables us to make a short review of the state-of-the-art about the fossil record of this species and to discuss its intraspecific variability. A gradual replacement of Thalassictis montadai, Thalassictis robusta and Hyaenictitherium wongii in Europe is demonstrated, until the arrival of canids during the latest Miocene. Additionally, the upper incisor of the large hyaenid creates some interesting questions concerning the first appearance of the crocutoid hyenas in the fossil record and their dominance over the percrocutoids. [ABSTRACT FROM AUTHOR]

The growing share of fluctuating renewable electricity production within the German energy system causes the increasing necessity for flexible consumers, producers, and storage technologies to balance supply and demand. District heating networks with combined heat and power units, Power-to-Heat applications, and thermal energy storage capacities can serve as one of these flexible options. In this context, a simulation model of the district heating network of the rural community Dollnstein, Germany, was built. With the residual load of different regional areas (Germany, Bavaria, Eichstätt, Dollnstein) it is investigated, how the heat generators can operate in an electricity market beneficial way. Two different control algorithms were evaluated: Due to a correlation between the residual loads and the CO2 emissions of the electricity mix, the CO2 savings achieved by this control algorithm are determined. Another way to operate electricity market beneficial is to consider the current CO2 emissions of each region. The main outcomes of this paper are, that there is a high potential for sector coupling by shifting the operation times of a CHP and a heat pump according to the residual load. The electricity demand of the heat pump can be met in terms of low CO2 emissions of the electricity mix, while the CHP can replace electricity with high CO2 emissions. These results can be improved, by considering not the residual load but the current CO2 emissions in the control algorithm. [ABSTRACT FROM AUTHOR]

In this article, we describe in detail three seismic measurement campaigns based on refraction methods that we conducted at different sites in Bavaria, Germany. The measured data is published as an open data set. The particularity of this data set lies in its available ground truth information about each measurement site. Acquiring seismic data from sites with ground truth information is important for validation of seismic inversion algorithms. Since near-surface seismic field data with ground truth information is rather limited, we anticipate this data set to be a valuable contribution to the research community. For the measurements, three sites have been selected: (1) a gravel pit with a ground water layer, (2) a site above a highway tunnel and (3) a surface over underground tubes. The measurements have been conducted using line arrays of geophones, the Geode Seismograph from Geometrics Inc. and hammer strikes as seismic source. To obtain inversion results a travel time tomography based on first-arrivals within the software SeisImager is used. The inversion results show that we are able to image the ground water layer in the gravel pit, the highway tunnel and partly features of underground tubes. Furthermore, the results coincide with available ground truth information about the measurement sites. This paper summarizes the measurement campaigns and the respective data sets obtained through these campaigns. The data have been published by the authors as an open data set under the license CC BY 4.0 on figshare to make it available to the research community for validation of seismic data processing and inversion techniques. [ABSTRACT FROM AUTHOR]

Currently, numerous physician practices in industrial and emerging countries are being taken over by private equity firms and integrated into novel physician corporations. This involves private equity firms producing a global wealth chain (GWC) between their investors and the target asset, using offshore financial centres to facilitate tax‐avoiding reflux of capital. Moreover, they are opening up ambulatory health care as an asset for capital investment by overcoming previous market barriers to ambulatory health care via a legal construct. In this paper, we trace the spatial links of these finance‐side and sector‐specific corporate chains based on a capital flow analysis of private equity takeovers of Medical Care Centres (MCCs) in Bavaria, Germany. With our heuristics of a double‐layered GWC, which enables the extraction of value from the German health system, we contribute to the emerging GWC debate that aims to conceptualise the complex and often opaque spatialisations of financialisation processes. [ABSTRACT FROM AUTHOR]

While the swabian and franconian karsts of southern Germany have yielded rich and important neogene vertebrate faunas, the middle to late Miocene transition is still extremely underrepresented. This period is however key for the understanding of the European mammal evolution. A microtoid rodent Microtocricetus M2 is described and commented in this paper. The fossil discovered in the karst filling Petersbuch 69 is regarded herein such as derived and might be thus the youngest fossil of the genus in Germany. [ABSTRACT FROM AUTHOR]

In early medieval times, the people of the Baiuvarii inhabited large parts of modern Bavaria (Germany). Among other evidence, about 10,000 graves dating from this time provide evidence of an exceptional level of settlement activity. These graves were arranged predominately in multiple parallel rows, so‐called Reihengräber, whereby the bodies were placed in stretched, supine positions. Burials that deviate from this custom are rarely found. For this reason, the excavation of a male skeleton at the cemetery of Aying‐Großhelfendorf (seventh to eighth centuries) attracted particular attention. The skeleton with label number 115 was found in a prone position and appears to have sustained four separate instances of sharp force trauma. The grave included a number of metal grave goods including a spatha and an iron shield boss. One focus of the study was on the macroscopic examination of the violence‐related lesions found on skeleton 115. They were located on the femur, the humerus, the frontal bone, and the maxilla on the right side of the body. The shape of the lesions indicates the insertion of a heavy, sharp, or bladed instrument. There is no evidence of healing detectable, leading to the conclusion that the individual was most likely involved in fight with fatal outcome. Subsequently, the victim was buried in a prone position alongside 17 other individuals in an otherwise regular graveyard. A possible interpretation of this difference in burial treatment is the fear of the victim's dependents of an unexpected or violent death or an expression of foreign origin. The aim of the paper is to present the most likely interpretation of the evidence in correlation with the anthropological and archaeological data. [ABSTRACT FROM AUTHOR]

Background: As the vector-borne diseases tick-borne encephalitis (TBE) and Lyme borreliosis (LB) are common in Germany and transmitted by tick bites, the aim of this study was to assess differences in the number of tick bites in various professions and regions across southern Germany to evaluate the differences in tick-associated risk.Materials and Methods: The analysis is based on three cross-sectional studies that were conducted in 2016 and 2017 in two real-life settings and in one medical setting in Bavaria. All participants filled in a paper-based questionnaire about their history with tick bites. Only adult participants (≥ 18 years) were included in this study.Results: Overall, 3503 individuals (mean age 50.8 ± 15.2 years, median age 53.0 ± 12.2 years, 54.0% female) were included. Of these, 50% worked in an outdoor profession and 56% lived in environs. Around 70% of participants reported at least one previous tick bite. In comparison to indoor workers, forestry workers (OR = 2.50; 95% CI: 1.10-5.68) had the highest risk for a tick bite followed by farmers (OR = 1.22; 95% CI: 1.01-1.47). Furthermore, people living in rural areas (OR = 1.97, 95% CI:1.49-2.59) and environs (OR = 1.98, 95% CI: 1.54-2.55) were twice as likely to have a previous tick bite than people living in urban areas. In general, slightly more tick bites were reported by people living in eastern Bavaria.Conclusion: Rising numbers of TBE and LB indicate the need for further prevention strategies, which should focus on outdoor professions with a higher risk and people living in environs and rural areas. [ABSTRACT FROM AUTHOR]

When meteorological conditions deviate from the optimal range for human well-being, the risks of illness, injury, and death increase, and such impacts are feared in particular with more frequent and intense extreme weather conditions resulting from climate change. Thermal indices, such as the universal thermal climate index (UTCI), can better assess human weather-related stresses by integrating multiple weather components. This paper quantifies and compares the seasonal and spatial association of UTCI with mortality, morbidity, and road accidents in the federal state of Bavaria, Germany. Linear regression was applied to seasonally associate daily 56 million hospital admissions and 2.5 million death counts (1995–2015) as well as approximately 930,000 road accidents and 1.7 million people injured (2002–2015) with spatially interpolated same day- and lagged- (up to 14 days) average UTCI values. Additional linear regressions were performed stratifying by age, gender, region, and district. UTCI effects were clear in all three health outcomes studied: Increased UTCI resulted in immediate (1–2 days) rises in morbidity and even more strongly in mortality in summer, and lagged (up to 14 days) decreases in fall, winter, and spring. The strongest UTCI effects were found for road accidents where increasing UTCI led to immediate decreases in daily road accidents in winter but pronounced increases in all other seasons. Differences in UTCI effects were observed e.g. between in warmer north-western regions (Franconia, more districts with heat stress-related mortality, but hospital admissions for lung, heart and external reasons decreasing with summer heat stress), the touristic alpine regions in the south (immediate effect of increasing UTCI on road accidents in summer), and the colder south-eastern regions (increasing hospital admissions for lung, heart and external reasons in winter with UTCI). Districts with high percentages of elderly suffered from higher morbidity and mortality, particularly in winter. The influences of UTCI as well as the spatial and temporal patterns of this influence call for improved infrastructure planning and resource allocation in the health sector. [ABSTRACT FROM AUTHOR]

This paper analyzes the effectiveness and efficiency of the normatives' controlling against the operational and strategic controlling. The general focus in studies and focus of the controlling experts is mostly on the operational controlling. For the analysis of the normatives' controlling in Bavarian SMEs a primary research data set is used. The survey was aimed on Bavarian SME's in the machine building sector. We employ regression models for the assessment of significance of the influencing factors, which are causing the negation of the normatives' controlling. We use monthly hours worked in the normatives' controlling, percentage acceptance of the normatives' controlling, used normatives' controlling instruments and the number of employees working in the controlling department as the influencing factors. The empirical evidence shows significant results affecting Bavarian SME's - Acceptance (monthly capacity of the head of controlling department) was identified as a significant variable on a statistically significant level with the estimated coefficient of 0.217 in relation to the Hours (monthly hours of work capacity) of normatives' controlling departments, and Instruments (number of instruments used) were proved to significantly influence the Employees (number of employees in controlling department) with the coefficient of 2.099. With the growing importance of the ability of an organization to publicly demonstrate its success in reaching objectives and specifically in its societal impacts, the importance of setting normatives and their control will project into higher demands on the work capacity of the controlling departments. [ABSTRACT FROM AUTHOR]

• Soil reflectance composites were generated with Sentinel-2 L2A data. • A multi-channel CNN learning framework for soil organic carbon prediction is proposed. • A dual input deep learning architecture improves the predictions. • The framework produced results that can be interpreted. The Copernicus Sentinel-2 multispectral imagery data may be aggregated to extract large-scale, bare soil, reflectance composites, which enable soil mapping applications. In this paper, this approach was tested in the German federal state of Bavaria, to provide estimations for soil organic carbon (SOC). Different temporal ranges were considered for the generation of the composites, including multi-annual and seasonal ranges. A novel multi-channel convolutional neural network (CNN) is proposed. By leveraging the advantages of deep learning techniques, it utilizes complementary information from different spectral pre-treatment techniques. The SOC predictions indicated little dissimilarity amongst the different composites, with the best performance attained for the six-year composite containing only spring months (RMSE = 12.03 g C · kg−1, R2 = 0.64, RPIQ = 0.89). It has been demonstrated that these outcomes outperform other well-known machine learning techniques. An ablation analysis was accordingly performed to evaluate the interplay of the CNN's different components to disentangle the advantages of each aspect of the proposed framework. Finally, a DUal inPut deep LearnIng architecture, named DUPLICITE, is proposed, which concatenates deep spectral features derived from the CNN mentioned earlier, as well as topographical and environmental covariates through an artificial neural network (ANN) to exploit their complementarity. The proposed approach was demonstrated to provide an improvement in the overall prediction performance (RMSE = 11.60 gC · kg−1, R2 = 0.67, RPIQ = 0.92). [ABSTRACT FROM AUTHOR]

• We provide a UAV-based multispectral imagery approach objectifying FHM strategies. • A CNN was trained using 17,643 images of trees with health status and species labels. • Analysis was done at 235 plots distributed across Bavaria over three years. • The highly heterogenous dataset benefits model generalization and transferability. • We provide a pipeline to generate reference data and for DL image classification. Uncrewed Aerial Vehicles (UAVs) have emerged as a promising tool for complementing terrestrial surveys, offering unique advantages for forest health monitoring (FHM). UAVs have the potential to improve or even replace core tasks such as crown condition assessment, bridging the gap between ground-based surveys and traditional remote sensing platforms. However, present approaches have not yet fully exploited the very high temporal resolution and flexible and convenient utilization that UAVs offer even under cloudy skies. In this paper, we provide a standardized data pipeline to semi-automatically generate reference data and for monitoring forest health by merging ground-based and UAV-based data related to species-specific forest health. Furthermore, we investigated the potential of Convolutional Neural Networks (CNNs) to classify the main tree species and their crown conditions based on the reference data. Therefore, we acquired high resolution multispectral drone imagery of 235 different ICP large scale forest monitoring plots (Level-I plots) distributed across Bavaria for three consecutive years (2020–2022). Using this highly heterogeneous time-series dataset, encompassing diverse weather and lighting conditions, forest stand characteristics, and spatial distribution of study areas, we successfully classified five tree species, three genus level classes and dead trees, including the health status of the main tree species occurring in Germany. This way we managed to classify 14 distinct classes with an average macro F1-score of 0.61 using the EfficientNet CNN architecture. The highest class-specific F1-score apart from the class of dead trees (0.97) was achieved by the class of Picea abies healthy (0.80). If participating countries of the ICP Forests program adopt our approach to harmonize terrestrial and UAV-based monitoring, many ground-based tasks could be reduced or replaced, leading to significant time and cost savings. We provide standardized and open-source monitoring and analysis strategies that can be potentially extended throughout Europe. Our findings demonstrate that UAV monitoring and deep learning can modernize forest management for efficiency and sustainability. We recommend integrating drones with ground surveys in forest monitoring systems to take advantage of their benefits. [ABSTRACT FROM AUTHOR]

The aim of this paper is to explore and define the boundary of the zone of inland, mainly agricultural settlement in southern and western Bohemia, Czech Republic in the later prehistory, and to try to determine why such settlement appears not to have spread further into the Šumava foothills and mountains. With the help of predictive MaxEnt modelling – used in ecology to determine the degree of uncertainty in the geographic distribution of species – and using a comparison with data on soil productivity, we explore whether in later prehistory the agricultural settlement was limited by unsuitable natural conditions or by other factors. The boundaries of the territory suitable for agropastoral farming most probably moved in time with technological advances, increases in population density, and the changing preferences of inhabitants of the Bronze and Iron Ages. The margin of agricultural settlement in the foothills describes a line beyond which agriculture had become unprofitable; a similar boundary existed throughout the Early Middle Ages. At the same time, there was a good deal of contact across the mountains with Bavaria and Upper Austria, as is shown by archaeology both in the form of similarities between the prehistoric typo-chronological complexes and by finds of bronze and iron items along presumed routes of access. There were also montane sites (whose function is still unknown) situated beyond the margin of the agricultural zone, such as the recently discovered settlements on the Křemelná river. Apart from prospection, a wide range of other activities could have taken place, including those connected with communication and routes of access to Bavaria and Upper Austria, with which Šumava formed a common typo-chronological group. [ABSTRACT FROM AUTHOR]

Even in federal states with a strong tradition of school worship, such as Bavaria, the question arises as to whether school worship services are still up-to-date in view of increasing religious and ideological plurality or whether they should be developed further in the direction of alternative forms of celebration. This paper presents the results of a qualitative study in which perspectives of school parents on school services and alternative forms of religious school life were surveyed. It becomes clear that headmasters combine religious school services with the goal of promoting the school community; this is a challenge in that religious services can develop great integrative power, but at the same time usually exclude individuals. [ABSTRACT FROM AUTHOR]

The increase in the distribution and availability of images for personal use in the late Middle Ages raises the question of their potential historical value for understanding the societies that produced and made use of them. This paper exposes the effects and the historical meanings of some woodcut illustrations of disputations between Jews and Christians: the woodcuts were widespread during the 1470s and 1480s in Swabia and Bavaria and surrounding areas, and they are still familiar and continue to play a role in shaping perceptions of Jewish-Christian relations of that period. These images do not reflect actual events: rather they are misrepresentations of polemical anti-Jewish sermons, designed as fictitious scholarly discourses. Their historical value is not limited to their ability to expose hidden angles. They can guide us to a better understanding of the written sources and to find new meanings there. [ABSTRACT FROM AUTHOR]

Nachruf Prof. Dipl.‐Ing. Dr. Lutz Sparowitz verstorben Nachrichten Planer‐Geschichten „unsere Helden" Ehrendoktorwürde für Professor Dr.‐Ing. Jürgen Schnell SIVV‐Handbuch – Kapitel D „Schutzmaßnahmen" aktualisiert Baugenehmigung für die Errichtung des weltweit ersten Gebäudes aus Carbonbeton Klimaangepasstes Bauen im Wohnungsbau in Bayern 28. Bayerischer Ingenieuretag Call for Papers [ABSTRACT FROM AUTHOR]

Background: Patients with metastatic breast cancer (MBC) are treated with a palliative approach with focus on controlling for disease symptoms and maintaining high quality of life. Information on individual needs of patients and their relatives as well as on treatment patterns in clinical routine care for this specific patient group are lacking or are not routinely documented in established Cancer Registries. Thus, we developed a registry concept specifically adapted for these incurable patients comprising primary and secondary data as well as mobile-health (m-health) data. Methods: The concept for patient-centered "Breast cancer care for patients with metastatic disease" (BRE-4-MED) registry was developed and piloted exemplarily in the region of Main-Franconia, a mainly rural region in Germany comprising about 1.3 M inhabitants. The registry concept includes data on diagnosis, therapy, progression, patient-reported outcome measures (PROMs), and needs of family members from several sources of information including routine data from established Cancer Registries in different federal states, treating physicians in hospital as well as in outpatient settings, patients with metastatic breast cancer and their family members. Linkage with routine cancer registry data was performed to collect secondary data on diagnosis, therapy, and progression. Paper and online-based questionnaires were used to assess PROMs. A dedicated mobile application software (APP) was developed to monitor needs, progression, and therapy change of individual patients. Patient's acceptance and feasibility of data collection in clinical routine was assessed within a proof-of-concept study. Results: The concept for the BRE-4-MED registry was developed and piloted between September 2017 and May 2018. In total n = 31 patients were included in the pilot study, n = 22 patients were followed up after 1 month. Record linkage with the Cancer Registries of Bavaria and Baden-Württemberg demonstrated to be feasible. The voluntary APP/online questionnaire was used by n = 7 participants. The feasibility of the registry concept in clinical routine was positively evaluated by the participating hospitals. Conclusion: The concept of the BRE-4-MED registry provides evidence that combinatorial evaluation of PROMs, needs of family members, and raising clinical parameters from primary and secondary data sources as well as m-health applications are feasible and accepted in an incurable cancer collective. [ABSTRACT FROM AUTHOR]

In this paper, a simple yet interpretable, probabilistic model is proposed for the prediction of reported case counts of infectious diseases. A spatio-temporal kernel is derived from training data to capture the typical interaction effects of reported infections across time and space, which provides insight into the dynamics of the spread of infectious diseases. Testing the model on a one-week-ahead prediction task for campylobacteriosis and rotavirus infections across Germany, as well as Lyme borreliosis across the federal state of Bavaria, shows that the proposed model performs on-par with the state-of-the-art hhh4 model. However, it provides a full posterior distribution over parameters in addition to model predictions, which aides in the assessment of the model. The employed Bayesian Monte Carlo regression framework is easily extensible and allows for incorporating prior domain knowledge, which makes it suitable for use on limited, yet complex datasets as often encountered in epidemiology. [ABSTRACT FROM AUTHOR]

• Development of simulation model for meshed district heating networks. • Investigation of the replacement of a heating plant by a geothermal plant. • In winter, this causes 25% higher mass flows and 16% higher pressures at GT plant. • 42% of CO 2 emissions and 29% of primary energy consumptions can be saved annually. • Supply with 2 different temperatures cause pipe life service reduction of 39–49 %. The geothermal energy production is expanding. How can these systems best be integrated into existing structures? To answer this question, a simplified district heating network model was set up and applied as well as validated to an existing 2000 customer district heating network in Bavaria. The network is powered by gas-fired heating and cogeneration plants. A geothermal plant with a significantly lower supply temperature will replace a heating plant. This paper investigates the arising operating conditions due to the replacement. Therefore, profiles of temperature, mass flow and pressure are analyzed. Furthermore, potential damage caused by temperature changes, a reduction in the supply temperature of the cogeneration plant as well as resulting CO 2 emissions, primary energy consumption and necessary pumping power are examined. The results show that a geothermal plant with a lower supply temperature can be integrated into an existing district heating network, taking all operational restrictions into account. The resulting electricity demand for pumping in the network is approx. 5% higher than with a gas-fired heating plant. In return, annual savings of e.g. 116,000 tCO 2 as well as about 437 GWh primary energy can be achieved. [ABSTRACT FROM AUTHOR]

After the new Coronavirus disease (COVID-19) emerged in the end of January 2020 in Germany, a large number of individuals suffered from severe symptoms and eventually needed intensive care in hospitals. Due to the rapid spread of the disease, the number of deceased individuals increased as well, which is a motivation to prevent as many new infections as possible. Therefore, the knowledge about the current evolution of the virus spread is crucial to predict its future behavior and to react with suitable interventions. In this paper, the evolution of the COVID-19 pandemic in Germany is forecasted by a network-based inference method, in which the interactions of individuals are taken into account using a contact matrix. Then the results are compared to the predictions without considering a contact matrix as well as to the logistic regression, which shows the advantage of incorporating the contact matrix. Furthermore, the basic reproduction number of the pandemic in Germany using a neural network approach is estimated and used for further predictions of the evolution of COVID-19 in Germany. In order to mathematically model the different compartments of the population in the considered regions, the classical SIR model is employed. In this work, we deploy the LASSO (Least Absolute Shrinkage and Selection Operator) for the unknown parameter estimation. Furthermore, we calculate and illustrate the MAPE (Mean Absolute Percentage Error) of the estimations to show the accuracy of the predictions. The results include model parameter estimation and model validation, as well as the outbreak forecasting using network-informed algorithms. Our findings show that the network-inference based approach outperforms the logistic regression as well as the neural network approach and the SIR model calibration without a contact network. Furthermore according to the results, the network-inference based approach is particularly suitable for short- to mid-term predictions, even when there is not much information about the new disease. Moreover, the predictions based on the estimation of the reproduction number in Germany can yield more reliable results with increasing the availability of data, but could not outperform the network-inference based algorithm. • The evolution of the COVID-19 pandemic in Germany and Bavaria state is forecasted. • The approach takes into account the interactions of individuals via a contact matrix. • The Mean Absolute Percentage Error (MAPE) of the estimation is calculated. • The prediction results are compared with the true data, NNs and logistic regression. • The predictions outperform the results of estimations without contact matrix. • The network-based approach is suitable for short- to mid-term predictions. • The predictions are informative for decision-makers to set protective measures. [ABSTRACT FROM AUTHOR]

Digital Twins (DTs) provide a promising solution for the maintenance and operation of bridges, thanks to their ability to mirror physical/structural conditions. A bridge DT generally consists of a geometric-semantic model whose creation, however, requires extensive manual effort. This paper presents an automated framework to generate the parametric model of bridges from their segmented point clouds. Following the concept of reverse engineering with parametric modeling, Parametric Prototype Models (PPMs) are proposed as tools to extract parameter values from point clouds. A local and global optimization problem is defined to adjust and assemble PPMs into an integrated model. The proposed approach has been validated by applying it to the point cloud of bridge components as well as point clouds captured from six concrete bridges in Bavaria, Germany. The results show that the proposed approach can generate the parametric model of bridges with a mean absolute error (MAE) of 8.71 cm. • A reverse engineering approach is proposed for the parametric modeling of bridges. • Parametric Prototype Models (PPMs) are introduced to describe bridge point clouds. • Local and global optimization problems are defined to adjust and assemble PPMs. • Metaheuristic optimization algorithms are utilized to derive parameter values. • The method is validated with the point cloud of six bridges in Bavaria, Germany. [ABSTRACT FROM AUTHOR]

Elisabeth of Görlitz, granddaughter of Charles IV, married Anthony, Duke of Brabant. After his death at the Battle of Agincourt in 1415, she was forced to take care of her own well-being while being yet again embroiled in Luxembourg’s politics. This study will therefore focus on the period of time the young widow attempted to cope with her new life situation, maintain a good political and economic position and find a new husband. [ABSTRACT FROM AUTHOR]

The use of wood energy for renewable heat production in private households has grown considerably in central Europe in the past years. Residential wood combustion is Janus-faced with regard to air emissions. Besides yielding lower greenhouse gas emissions than the combustion of fossil fuels, wood combustion is associated with pollutant emissions that are harmful to human health. The heating systems have great potential for emission reduction due to the widespread combustion of wood in installations that are often overage. An emission control act aimed at heating system modernisation and emission load reduction has recently taken effect in Germany. This paper analyses the development of the particulate matter emission load from wood energy combustion in the case study area of Bavaria until 2035. It also evaluates the impact of the legal amendment. The emission load of prevalent heating systems is calculated based on two wood consumption scenarios, and the influence of the emission control act is analysed, taking into account retro-fitting and the replacement rates of old heating systems. The results show that particulate matter emissions could be reduced considerably and there is potential for an increase in the efficiency of resource use in the domestic heating sector. [ABSTRACT FROM AUTHOR]

The ongoing transition from a conventional energy supply towards an energy system based on renewable sources requires fundamental changes to the energy infrastructure. In particular, the move from centralized towards distributed power generation significantly increases the demand for ICT-based management and control. Today ICT-based energy management is mostly purely central, making the critical infrastructure of power supply sometimes inflexible and potentially vulnerable to (cyber-)attacks. Addressing these challenges, the future grid requires high automation and distributed intelligence on field level being able to work independently from a central system. Distribution grids are often sparsely monitored and a system wide upgrade of measuring technology is associated with high costs. However, information about load behavior at the nodes of a grid is essential for grid state identification and load forecasting. This paper shows the concept of load balancing and the related IT architecture for monitoring and control of distributed energy systems, where smart metering and smart home technologies play a key role in the smart grid of the future. Readers are invited to contribute to the research work and field laboratory of the University of Bayreuth, which is operated by an innovative utility company in Bavaria. [ABSTRACT FROM AUTHOR]

Acceptance plays an important role in the successful adoption of wind energy technology. This article identifies factors influencing the acceptance of wind energy and selects those factors which have the highest relevance for wind energy acceptance in Bavaria. We decided to analyze the Federal State of Bavaria in Germany as its current policy governance decelerates the building-up of wind turbines in this federal state. Using a qualitative approach, the results indicate that the perception of political processes, such as the recent enacting of the 10-H regulation in Bavaria, influences the acceptance towards wind energy, as trust and transparency in political processes are essential. In addition, the paper reveals the importance of the distributive justice, focusing in particular on the subitem envy, which can be considered on a neighboring or regional level. Additionally it reveals additional factors which are relevant for wind energy acceptance in the specific case of the analyzed federal state. [ABSTRACT FROM AUTHOR]

• Long-distance heat transport reduce the cost of heat supply by 15% • Cost of geothermal heat supply is competitive with other heat technologies. • Economic performance of geothermal systems increases with high full-load hours. • Geothermal energy can transition from a local to a regional use. • Geothermal district heating systems contribute to the low-carbon heat supply. Geothermal energy can play an important role in decarbonizing the heating sector, however, a limiting factor is that heat demand in urban areas does not usually coincide spatially with geological settings favorable to the extraction of geothermal energy. Long-distance heat transport could enable the direct use of geothermal resources even in areas with low or no geothermal potential. This paper proposes the cost-optimal coordinated deployment of geothermal heating plants together with heat transport and distribution networks to simultaneously supply geothermal heat to multiple urban areas. To this end, a holistic approach comprising the mapping of geothermal potential for direct-use, the estimation of district heating potential, and a two-step optimization model to calculate cost-optimal large-scale geothermal district heating systems, is presented and applied to the Free State of Bavaria in Germany. As a result, heat supply costs can be reduced by 15% if fewer geothermal wells are drilled in more geologically favorable areas at greater distances from heat sinks. Calculated levelized costs of heat without local distribution networks of 33–39 €/MWh show that geothermal energy could transition from a local to a regional use if utilized in in scenarios with high full-load hours. The proposed methodology can be adapted to develop expansion strategies for deep geothermal energy in other similar regions worldwide. [ABSTRACT FROM AUTHOR]

• New approaches to deposition analysis were developed to study a large data set of prehistoric settlement discard. • The archaeological context was studied as a compressed, synoptic record of the lifecycle of things. • Phases of the cultural biography of Bronze Age houses were identified including their use, intentional cremation, the burial of remains (burnt settlement refuse) and closing deposits. • Houses are explained as the central (albeit non-human) actors of hybrid actor-networks. • The actor's role of the houses was strengthened by their ontological status as living beings. This paper deals with the application of deposition analysis to an unusual type of features in the Late Bronze Age settlements in Central Europe. These are long narrow trenches (referred to as 'long pits' in this text) with characteristic standard form and alignment, as well as find contents, including high amounts of secondary-burned pottery fragments. In the context of prehistoric research, these features represent a relatively new phenomenon that has attracted attention in the last two decades due to new excavations in Bohemia and Bavaria. Based on the finds from Březnice (Czechia), the authors conclude that the long pits were connected with the closing rituals following the abandonment and burial of dwellings. Although no houses were directly documented on this site, their presence must be assumed, and their cultural biography can be reconstructed from the depositional characteristics of the accompanying finds. In order to fully understand the processes of deposition, the authors find it useful to focus not only on human agency but also on the relationships between the things themselves. This way, houses are understood as the central element of a hybrid actor-network. Their role may have been strengthened by their ontological status of living beings. [ABSTRACT FROM AUTHOR]

This paper evaluates a school reform in Bavaria that moved the timing of tracking in low- and middle-track schools from grade 6 to grade 4; students in high-track schools were not affected. To eliminate state-specific and school-type-specific shocks, I estimate a triple-differences model using three PISA waves. The results indicate that the reform reduced the performance of 15-year-old students both in low- and middle-track schools. Further evidence suggests that the share of very low-performing students increased in low-track schools. [ABSTRACT FROM AUTHOR]

This paper describes the ginkgoaleans (Ginkgoites) and conifers (Palissya, Stachyotaxus, Schizolepis) of the Rhaetian flora from Wüstenwelsberg, as well as a new species of the cycad Becklesia. The ginkgophyte leaf fragments are very abundant in certain levels ('Blätterkohle') whereas conifers are common in the main fossiliferous bed. The Wüstenwelsberg specimens extend the range for Ginkgoites taeniatus from the Hettangian to the Rhaetian and for the genus Becklesia from the Cretaceous to the Rhaetian. The other elements are typical for the Rhaetian floras of Bavaria and often also of the Northern Hemisphere. A comparison with other Northern Hemisphere plant assemblages demonstrates a high similarity with the Rhaetian floras from Jameson Land (Greenland) and Scania (Sweden) but significant differences to the Hettangian floras from adjacent areas in Franconia, especially at species and sometimes at generic level. A comparison with the microflora from the same sections shows a hidden diversity that is highest in small herbaceous plants (mosses, lycophytes, ferns) and in the conifers. Wüstenwelsberg reflects, thus, an articulated landscape with a high water and nutrients availability (stagnant water bodies and/or river systems) covered by a complex and multi-storeyed vegetation shown, among others, by the general abundance in hygrophytic spores and high diversity among the various plant groups. This must have corresponded to one of the humid episodes that characterized the generally warm and arid climate of the Rhaetian of Europe. • First Rhaetian record of Ginkgoites taeniatus. • Becklesia franconica n. sp. extends the stratigraphic range of Becklesia into the Rhaetian. • The Rhaetian flora from Bavaria differs markedly from the Hettangian one. • Comparison with the microflora evidences a hidden diversity among the macroflora. • A deltaic setting may be inferred for the Rhaetian Wüstenwelsberg area. [ABSTRACT FROM AUTHOR]

Storms can cause significant damage to forest areas, affecting biodiversity and infrastructure and leading to economic loss. Thus, rapid detection and mapping of windthrows are crucially important for forest management. Recent advances in computer vision have led to highly-accurate image classification algorithms such as Convolutional Neural Network (CNN) architectures. In this study, we tested and implemented an algorithm based on CNNs in an ArcGIS environment for automatic detection and mapping of damaged areas. The algorithm was trained and tested on a forest area in Bavaria, Germany.. It is a based on a modified U-Net architecture that was optimized for the pixelwise classification of multispectral aerial remote sensing data. The neural network was trained on labeled damaged areas from after-storm aerial orthophotos of a ca. 109 k m 2 forest area with RGB and NIR bands and 0.2-m spatial resolution. Around 10 7 pixels of labeled data were used in the process. Once the network is trained, predictions on further datasets can be computed within seconds, depending on the size of the input raster and the computational power used. The overall accuracy on our test dataset was 92 % . During visual validation, labeling errors were found in the reference data that somewhat biased the results because the algorithm in some instance performed better than the human labeling procedure, while missing areas affected by shadows. Our results are very good in terms of precision, and the methods introduced in this paper have several additional advantages compared to traditional methods: CNNs automatically detect high- and low-level features in the data, leading to high classification accuracies, while only one after-storm image is needed in comparison to two images for approaches based on change detection. Furthermore, flight parameters do not affect the results in the same way as for approaches that require DSMs and DTMs as the classification is only based on the image data themselves, and errors occurring in the computation of DSMs and DTMs do not affect the results with respect to the z component. The integration into the ArcGIS Platform allows a streamlined workflow for forest management, as the results can be accessed by mobile devices in the field to allow for high-accuracy ground-truthing and additional mapping that can be synchronized back into the database. Our results and the provided automatic workflow highlight the potential of deep learning on high-resolution imagery and GIS for fast and efficient post-disaster damage assessment as a first step of disaster management. [ABSTRACT FROM AUTHOR]

Most biogeochemical processes are regulated by soil structure, which can be studied at different scales. On a very small scale, soil microaggregates are considered to play an important role in soil functioning. Knowledge of their structure is therefore crucial for the understanding of many soil processes and functions, such as the storage and cycling of water, nutrients and organic matter. However, we know little about the microscale internal architecture of microaggregates, their formation and the mechanisms leading to the spatial organization of their various building units. The best method for structure analysis is computed microtomography, as this technique can provide detailed 3D (or even 4D) information on soil microstructure at high resolutions. In this paper, we introduce possibilities to study and quantify the 3D architecture of microaggregates using high resolution X-ray microtomography at a resolution of approx. 500 nm. Since texture is known to exert a strong influence on the (micro-) structure of the soil, we investigated microaggregates with three different clay contents (n = 20 for each clay content) from a toposequence in Scheyern, Bavaria, which were isolated from the soil with a novel dry separation approach.Our results show that aggregate volume, aggregate surface area and pore surface are similar across all clay contents. The content of macropores and maximal pore diameter also did not differ along this textural gradient. However, the total porosity of the microaggregates increased with clay content, as did pore surface normalized to aggregate volume. Further, the Euler number decreased with clay content, indicating a higher connectivity of the pore system. These findings show that with increasing clay/decreasing sand content, the pore architecture of the studied microaggregates changed and that samples with high clay content had a more connective pore system and a higher pore surface area per aggregate volume, which facilitates higher process rates and faster transport of oxygen, water and nutrients. Possible feedback mechanisms on microaggregate formation and stabilization are discussed. [ABSTRACT FROM AUTHOR]