@article{Brunn, author = {Brunn, Ansgar}, title = {Zwangsfreie Richtungsmessungen}, series = {zfv - Zeitschrift f{\"u}r Geod{\"a}sie, Geoinformation und Landmanagement}, volume = {149}, journal = {zfv - Zeitschrift f{\"u}r Geod{\"a}sie, Geoinformation und Landmanagement}, number = {1}, publisher = {Wißner-Verlag}, doi = {10.12902/zfv-0455-2023}, pages = {45 -- 51}, abstract = {Moderne, digitale, automatisierte Tachymeter bieten einen flexiblen Einsatz und erfordern gleichzeitig flexible Rechenverfahren. Einschr{\"a}nkungen der tradierten Auswerteverfahren in Bezug auf die Richtungsmessungen in den Zenit und in Richtung der Nullrichtung (Nullpunkt des Teilkreises) sind dabei nicht akzeptabel. Daher wird in diesem Beitrag ein neuer, auf Richtungsvektoren basierender Umgang mit Richtungsmessungen vorgeschlagen. Der direkte Vergleich des tradierten Verfahrens mit dem neuen Ansatz zeigt das neu gewonnene Potential, letztlich aber auch die Notwendigkeit, das Geod{\"a}tische Rechnen neu zu erfinden.}, language = {de} } @article{VahrenholdBrandmeierMueller, author = {Vahrenhold, Jan Richard and Brandmeier, Melanie and M{\"u}ller, Markus Sebastian}, title = {MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds}, series = {Remote Sensing}, volume = {17}, journal = {Remote Sensing}, number = {7}, publisher = {MDPI AG}, issn = {2072-4292}, doi = {https://doi.org/10.3390/rs17071304}, abstract = {Trees play a critical role in climate regulation, biodiversity, and carbon storage as they cover approximately 30\% of the global land area. Nowadays, Machine Learning (ML)is key to automating large-scale tree species classification based on active and passive sensing systems, with a recent trend favoring data fusion approaches for higher accuracy. The use of 3D Deep Learning (DL) models has improved tree species classification by capturing structural and geometric data directly from point clouds. We propose a fully Multimodal Tree Species Classification Network (MMTSCNet) that processes Light Detection and Ranging (LiDAR) point clouds, Full-Waveform (FWF) data, derived features, and bidirectional, color-coded depth images in their native data formats without any modality transformation. We conduct several experiments as well as an ablation study to assess the impact of data fusion. Classification performance on the combination of Airborne Laser Scanning (ALS) data with FWF data scored the highest, achieving an Overall Accuracy (OA) of nearly 97\%, a Mean Average F1-score (MAF) of nearly 97\%, and a Kappa Coefficient of 0.96. Results for the other data subsets show that the ALS data in combination with or even without FWF data produced the best results, which was closely followed by the UAV-borne Laser Scanning (ULS) data. Additionally, it is evident that the inclusion of FWF data provided significant benefits to the classification performance, resulting in an increase in the MAF of +4.66\% for the ALS data, +4.69\% for the ULS data under leaf-on conditions, and +2.59\% for the ULS data under leaf-off conditions. The proposed model is also compared to a state-of-the-art unimodal 3D-DL model (PointNet++) as well as a feature-based unimodal DL architecture (DSTCN). The MMTSCNet architecture outperformed the other models by several percentage points, depending on the characteristics of the input data.}, language = {en} } @article{MelnykBrunn, author = {Melnyk, Oleksander and Brunn, Ansgar}, title = {Analysis of Spectral Index Interrelationships for Vegetation Condition Assessment on the Example of Wetlands in Volyn Polissya, Ukraine}, series = {earth}, volume = {6}, journal = {earth}, number = {2}, doi = {10.3390/earth6020028}, pages = {21}, abstract = {The Cheremskyi Nature Reserve, situated in the Volyn region of Ukraine, constitutes a pivotal element of the European ecological network, distinguished by its distinctive mosaic of peatlands, bogs, and floodplain forests. This study utilizes Sentinel-2 satellite imagery and the Google Earth Engine (GEE) to assess the spatiotemporal patterns of various vegetation indices (NDVI, EVI, SAVI, MSAVI, GNDVI, NDRE, NDWI) from 2017 to 2024. The study aims to select the most suitable combination of vegetation spectral indices for future research. The analysis reveals significant negative trends in NDVI, SAVI, MSAVI, GNDVI, and NDRE, indicating a decline in vegetation health, while NDWI shows a positive trend, suggesting an increased vegetation water content. Correlation analysis underscores robust interrelationships among the indices, with NDVI and SAVI identified as the most significant through random forest feature importance analysis. Principal component analysis (PCA) further elucidates the primary axes of variability, emphasizing the complex interplay between vegetation greenness and moisture content. The findings underscore the utility of multi-index analyses in enhancing predictive capabilities for ecosystem monitoring and support targeted conservation strategies for the sustainable management of the Cheremskyi Nature Reserve.}, language = {en} } @article{SchueleinChristosKBolketal., author = {Sch{\"u}lein, Tim and Christos K., Georgantopoulos and Bolk, Lars and Herrmann, Volker and Wilhelm, Manfred}, title = {Thermo-Mechanical Degradation Kinetics of a High-Density Poly(Ethylene) Using a Closed-Cavity Rheometer}, series = {Journal of Applied Polymer Science}, volume = {142}, journal = {Journal of Applied Polymer Science}, number = {17}, doi = {10.1002/app.56784}, abstract = {Mechanical recycling of polymers is an essential aspect to achieve circular economy. High shear stress, excessive temperature, and long residence time during reprocessing cause thermo-mechanical degradation of the polymer. Therefore, it is important to understand and quantify this degradation kinetics. Common ways to simulate degradation are very time and material consuming and clear insights into the respective influence of temperature and shear stress on degradation are rare. Within this publication a method is developed using a commercially available, close-cavity rheometer to emulate processing conditions in a defined way. This allows monitoring and predicting the behavior of a high-density polyethylene (HDPE) and quantify degradation kinetics and changes in the polymer topology. HDPE is selected as a model polymer due to its large production and wide range of applications. Different treated samples are analyzed by various rheological methods. Additionally, molecular characterization is conducted. A kinetic model to predict the changes in the molecular weight as a function of in-phase shear stress, temperature and duration during treatment is presented. The calculated activation energy for the initiation reaction agrees with the activation energy for HDPE degradation from thermogravimetric analysis. This activation energy is lowered by in-phase shear stress, modified by a factor of 1.7 m3 mol-1.}, language = {en} } @article{Herrmann, author = {Herrmann, Volker}, title = {Internationalisierung als m{\"o}gliche L{\"o}sung f{\"u}r das Problem des Fachkr{\"a}ftemangels}, series = {Kautschuk Gummi Kunststoffe 77}, journal = {Kautschuk Gummi Kunststoffe 77}, pages = {8 -- 9}, language = {de} } @article{HerrmannFroschSchueleinetal., author = {Herrmann, Volker and Frosch, Stefan and Sch{\"u}lein, Tim and Grunert, Fabian and Blume, Anke}, title = {Sulfur Diffusion Studies Imitating Recycled Ground-Rubber-Containing Compounds}, series = {Polymers}, volume = {16}, journal = {Polymers}, number = {22}, doi = {10.3390/polym16223112}, abstract = {n-rubber properties of vulcanizates deteriorate in the presence of incorporated recycled ground rubber (GR). This behavior is partly explained by a possible diffusion of sulfur from the rubber matrix into the GR. Therefore, the sulfur concentration and, thus, the crosslink density in the matrix are reduced. This phenomenon was further investigated in this research work using two spatially resolved methods that supplement each other: the diffusion of soluble sulfur in GR-containing compounds was locally investigated via Micro X-Ray Fluorescence analysis. Viscoelastic properties were also determined spatially by the Micro Dynamic-Mechanical Indentation method. Combining the results of both methods, local concentrations of sulfur were related to local viscoelastic properties, revealing great differences in crosslink density at the interface between the GR and matrix material. In this way, it is shown that sulfur is capable of diffusing several mm, which locally doubles its concentration with respect to the sulfur content of the compound formulation. This, in turn, negatively impacts the homogeneity of crosslink density in both the matrix and GR, revealing a local increase in the elastic stiffness of 100 \%. In addition, it was found that the vulcanization characteristics of the used polymers determine the amount of sulfur diffusion and, thus, the change in viscoelastic properties.}, language = {en} } @article{SpeckenwirthBrandmeierPaczkowski, author = {Speckenwirth, S{\"o}nke and Brandmeier, Melanie and Paczkowski, Sebastian}, title = {TreeSeg - A Toolbox for Fully Automated Tree Crown Segmentation Based on High-Resolution Multispectral UAV Data}, series = {remote sensing}, volume = {16}, journal = {remote sensing}, number = {19}, publisher = {MDPI}, doi = {10.3390/rs16193660}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-57590}, pages = {17}, abstract = {Single-tree segmentation on multispectral UAV images shows significant potential for effective forest management such as automating forest inventories or detecting damage and diseases when using an additional classifier. We propose an automated workflow for segmentation on high-resolution data and provide our trained models in a Toolbox for ArcGIS Pro on our GitHub repository for other researchers. The database used for this study consists of multispectral UAV data (RGB, NIR and red edge bands) of a forest area in Germany consisting of a mix of tree species consisting of five deciduous trees and three conifer tree species in the matured closed canopy stage at approximately 90 years. Information of NIR and Red Edge bands are evaluated for tree segmentation using different vegetation indices (VIs) in comparison to only using RGB information. We trained Faster R-CNN, Mask R-CNN, TensorMask and SAM in several experiments and evaluated model performance on different data combinations. All models with the exception of SAM show good performance on our test data with the Faster R-CNN model trained on the red and green bands and the Normalized Difference Red Edge Index (NDRE) achieving best results with an F1-Score of 83.5\% and an Intersection over Union of 65.3\% on highly detailed labels. All models are provided in our TreeSeg toolbox and allow the user to apply the pre-trained models on new data.}, language = {en} } @article{HellBrandmeier, author = {Hell, Maximilian and Brandmeier, Melanie}, title = {Identifying Plausible Labels from Noisy Training Data for a Land Use and Land Cover Classification Application in Amaz{\^o}nia Legal}, series = {remote sensing}, volume = {26}, journal = {remote sensing}, number = {12}, doi = {10.3390/rs16122080}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-57532}, pages = {24}, abstract = {Most studies in the field of land use and land cover (LULC) classification in remote sensing rely on supervised classification, which requires a substantial amount of accurate label data. However, reliable data are often not immediately available, and are obtained through time-consuming manual labor. One potential solution to this problem is the use of already available classification maps, which may not be the true ground truth and may contain noise from multiple possible sources. This is also true for the classification maps of the MapBiomas project, which provides land use and land cover (LULC) maps on a yearly basis, classifying the Amazon basin into more than 24 classes based on the Landsat data. In this study, we utilize the Sentinel-2 data with a higher spatial resolution in conjunction with the MapBiomas maps to evaluate a proposed noise removal method and to improve classification results. We introduce a novel noise detection method that relies on identifying anchor points in feature space through clustering with self-organizing maps (SOM). The pixel label is relabeled using nearest neighbor rules, or can be removed if it is unknown. A challenge in this approach is the quantification of noise in such a real-world dataset. To overcome this problem, highly reliable validation sets were manually created for quantitative performance assessment. The results demonstrate a significant increase in overall accuracy compared to MapBiomas labels, from 79.85\% to 89.65\%. Additionally, we trained the L2HNet using both MapBiomas labels and the filtered labels from our approach. The overall accuracy for this model reached 93.75\% with the filtered labels, compared to the baseline of 74.31\%. This highlights the significance of noise detection and filtering in remote sensing, and emphasizes the need for further research in this area.}, language = {en} } @article{BrandmeierHessdoerferSiebenlistetal., author = {Brandmeier, Melanie and Heßd{\"o}rfer, Daniel and Siebenlist, Philipp and Meyer-Spelbrink, Adrian and Kraus, Anja}, title = {Time Series Analysis of Multisensor Data for Precision Viticulture}, series = {remote sensing}, volume = {16}, journal = {remote sensing}, number = {8}, publisher = {MDPI}, doi = {10.3390/rs16081419}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-57527}, pages = {18}, abstract = {In the context of climate change, vineyard monitoring to better understand spatiotemporal patterns of grapevine development is of utter importance for precision viticulture. We present a time series analysis of hyperspectral in situ and multispectral UAV data for different irrigation systems in Lower Franconia and correlate results with sensor data for soil moisture, temperature, and precipitation. Analysis of Variance (ANOVA) and a Tukey's HSD test were performed to see whether Vegetation Indices (VIs) are significantly different with respect to irrigation systems as well as topographic position in the vineyard. Correlation between in situ measurements and UAV data for selected VIs is also investigated for upscaling analysis. We find significant differences with respect to irrigation, as well as for topographic position for most of the VIs investigated, highlighting the importance of adapted water management. Correlation between in situ and UAV data is significant only for some indices (NDVI and CIRedEdge, 𝑟2 of 0.33 and 0.49, respectively), while shallow soil moisture patterns correlate well with in situ-derived VIs such as the CIRedEdge and RG index (𝑟2 of 0.34 and 0.46).}, language = {en} } @article{BrunnUhlMelnyketal., author = {Brunn, Ansgar and Uhl, Anna and Melnyk, Oleksandr and Melnyk, Yuliia and Manko, Pavlo and Fesyuk, Vasyl}, title = {Remote sensing monitoring of changes in forest cover in the Volyn region}, series = {Visnyk of V. N. Karazin Kharkiv National University, series "Geology. Geography. Ecology}, journal = {Visnyk of V. N. Karazin Kharkiv National University, series "Geology. Geography. Ecology}, number = {60}, publisher = {V. N. Karazin Kharkiv National University}, doi = {10.26565/2410-7360-2024-60-19}, pages = {272 -- 283}, abstract = {This article highlights the significance of forest cover as an important indicator of the state of the environment. It discusses the findings of the Food and Agriculture Organization of the United Nations (FAO) Forest Resources Assessment (FRA) 2020 report, which states that the world's forest area has decreased by 178 million hectares since 1990. The case study of Volyn region shows how cloud processing and vegetation classification can help quantify forest dynamics from 2000 to 2020, allowing local authorities and decision makers to monitor and analyze trends in near real time. Overall, this work provides insights into the importance of monitoring forest dynamics and the potential for remote sensing technology to facilitate this process}, language = {en} } @article{AnwanderBrandmeierPaczkowskietal., author = {Anwander, Julia and Brandmeier, Melanie and Paczkowski, Sebastian and Neubert, Tarek and Paczkowska, Marta}, title = {Evaluating Different Deep Learning Approaches for Tree Health Classification Using High-Resolution Multispectral UAV Data in the Black Forest, Harz Region, and G{\"o}ttinger Forest}, series = {Remote Sensing}, volume = {16}, journal = {Remote Sensing}, number = {3}, doi = {10.3390/rs16030561}, pages = {561 -- 561}, abstract = {We present an evaluation of different deep learning and machine learning approaches for tree health classification in the Black Forest, the Harz Mountains, and the G{\"o}ttinger Forest on a unique, highly accurate tree-level dataset. The multispectral UAV data were collected from eight forest plots with diverse tree species, mostly conifers. As ground truth data (GTD), nearly 1500 tree polygons with related attribute information on the health status of the trees were used. This data were collected during extensive fieldwork using a mobile application and subsequent individual tree segmentation. Extensive preprocessing included normalization, NDVI calculations, data augmentation to deal with the underrepresented classes, and splitting the data into training, validation, and test sets. We conducted several experiments using a classical machine learning approach (random forests), as well as different convolutional neural networks (CNNs)—ResNet50, ResNet101, VGG16, and Inception-v3—on different datasets and classes to evaluate the potential of these algorithms for tree health classification. Our first experiment was a binary classifier of healthy and damaged trees, which did not consider the degree of damage or tree species. The best results of a 0.99 test accuracy and an F1 score of 0.99 were obtained with ResNet50 on four band composites using the red, green, blue, and infrared bands (RGBI images), while VGG16 had the worst performance, with an F1 score of only 0.78. In a second experiment, we also distinguished between coniferous and deciduous trees. The F1 scores ranged from 0.62 to 0.99, with the highest results obtained using ResNet101 on derived vegetation indices using the red edge band of the camera (NDVIre images). Finally, in a third experiment, we aimed at evaluating the degree of damage: healthy, slightly damaged, and medium or heavily damaged trees. Again, ResNet101 had the best performance, this time on RGBI images with a test accuracy of 0.98 and an average F1 score of 0.97. These results highlight the potential of CNNs to handle high-resolution multispectral UAV data for the early detection of damaged trees when good training data are available.}, language = {en} } @article{VetterKasangSousa, author = {Vetter, Mark and Kasang, Christa and Sousa, Arturo}, title = {Fight against neglected infectious diseases in Togo with Geographic Information Systems}, series = {Euro-Mediterranean Journal for Environmental Integration}, journal = {Euro-Mediterranean Journal for Environmental Integration}, language = {en} } @article{VetterAguilarAlbaGarciaBarronetal., author = {Vetter, Mark and Aguilar-Alba, M{\´o}nica and Garcia-Barron, Leoncio and Morales, Julia and Sousa, Arturo}, title = {Possible syndemics in Spain during the 20th century associated with autochthonous malaria}, series = {Euro-Mediterranean Journal for Environmental Integration}, journal = {Euro-Mediterranean Journal for Environmental Integration}, language = {de} } @article{FroschHerrmannGrunertetal., author = {Frosch, Stefan and Herrmann, Volker and Grunert, F. and Blume, A.}, title = {Quantification of sulfur distribution on rubber surfaces by means of μ-X-ray fluorescence analysis}, series = {Polymer Testing}, volume = {128}, journal = {Polymer Testing}, number = {108237}, doi = {10.1016/j.polymertesting.2023.108237}, abstract = {A homogeneous distribution of sulfur in a rubber compound is often desired. Spatially resolved imaging techniques are useful for evaluating the distribution of this crosslinking chemical. Typical measurement methods such as SEM (scanning electron microscopy) or TEM (transmission electron microscopy) have very high resolutions. However, the sample size or the maximum area to be investigated is limited, which makes it difficult to obtain a statistically reliable determination of sulfur homogeneity across the component or sample. In this work, an alternative measurement technique is therefore presented: the μ-XRF (μ-X-ray fluorescence analysis). With the help of this method, it is possible to scan surfaces of several cm2 and to show the distribution of different chemical elements. Its measuring principle has been known for decades but has hardly been used in the rubber industry so far. The main reason for this is that its quantification process for polymeric samples is more complex than for geologic or metallic samples, which are typically been investigated with μ-XRF to date. In this paper, this issue is addressed and a solution is presented: With the help of the fundamental parameter method, the determination of sulfur homogeneity and distribution on rubber surfaces becomes possible. This opens up a variety of further possibilities for the use of μ-XRF in the rubber industry: For example, it could be used in areas of tire production, recycling of end-of-life rubber, and beyond.}, language = {en} } @article{OlberdingVetter, author = {Olberding, Helge and Vetter, Mark}, title = {Dynamic 3D-Cartographic Symbols for VR Geovisualizations}, series = {KN - Journal of Cartography and Geographic Information}, volume = {73}, journal = {KN - Journal of Cartography and Geographic Information}, number = {4}, issn = {2524-4965}, doi = {10.1007/s42489-023-00153-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-53072}, pages = {265 -- 275}, abstract = {Geovisualizations that use a virtual reality headset can have a more immersive effect on users than when only a desktop application is viewed. However, to have an overview, a VR 3D map is usually viewed from a top-down perspective. On the other hand, the first-person perspective is used when the scenario is visualized as realistically as possible, and the ultimate goal is to feel present inside the 3D city. With the help of dynamic cartographic visualization methods, such as animated symbols appearing or a dynamic change of selected or complete visualization, it is possible to convey targeted information while being inside the 3D. For this purpose, techniques and ideas from cartography and video games were utilized and combined. The combination resulted in dynamically changeable symbol objects, which can be placed automatically using tables or building information, and dynamically changeable post-processing methods. Users can interactively select a predefined set of visualization methods and show/hide dynamic cartographic symbols in the running application via an interface. The study aims to develop cartographic visualization methods that can be technically used within a game engine for VR applications to improve spatial perception.}, language = {en} } @article{HartKnoblachMoeser, author = {Hart, Lukas and Knoblach, Stefan and M{\"o}ser, Michael}, title = {Automated pipeline reconstruction using deep learning \& instance segmentation}, series = {ISPRS Open Journal of Photogrammetry and Remote Sensing}, volume = {9}, journal = {ISPRS Open Journal of Photogrammetry and Remote Sensing}, publisher = {Elsevier}, doi = {10.1016/j.ophoto.2023.100043}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-53620}, pages = {19}, abstract = {BIM is a powerful tool for the construction industry as well as for various other industries, so that its use has increased massively in recent years. Laser scanners are usually used for the measurement, which, in addition to the high acquisition costs, also cause problems on reflective surfaces. The use of photogrammetric techniques for BIM in industrial plants, on the other hand, is less widespread and less automated. CAD software (for point cloud evaluation) contains at best automated reconstruction algorithms for pipes. Fittings, flanges or elbows require a manual reconstruction. We present a method for automated processing of photogrammetric images for modeling pipelines in industrial plants. For this purpose we use instance segmentation and reconstruct the components of the pipeline directly based on the edges of the segmented objects in the images. Hardware costs can be kept low by using photogrammetry instead of laser scanning. Besides the autmatic extraction and reconstruction of pipes, we have also implemented this for elbows and flanges. For object recognition, we fine-tuned different instance segmentation models using our own training data, while also testing various data augmentation techniques. The average precision varies depending on the object type. The best results were achieved with Mask R-CNN. Here, the average precision was about 40\%. The results of the automated reconstruction were examined with regard to the accuracy on a test object in the laboratory. The deviations from the reference geometry were in the range of a few millimeters and were comparable to manual reconstruction. In addition, further tests were carried out with images from a plant. Provided that the objects were correctly and completely recognized, a satisfactory reconstruction is possible with the help of our method.}, language = {en} } @article{SousaAguilarAlbaVetteretal., author = {Sousa, Arturo and Aguilar-Alba, M{\´o}nica and Vetter, Mark and Garc{\´i}a-Barr{\´o}n, Leoncio and Morales, Julia}, title = {Drivers of autochthonous and imported malaria in Spain and their relationship with meteorological variables}, series = {Euro-Mediterranean Journal for Environmental Integration}, volume = {6}, journal = {Euro-Mediterranean Journal for Environmental Integration}, number = {1}, issn = {2365-6433}, doi = {10.1007/s41207-021-00245-8}, pages = {33 -- 33}, language = {en} } @article{SousaAguilarAlbaVetteretal., author = {Sousa, Arturo and Aguilar-Alba, M{\´o}nica and Vetter, Mark and Garc{\´i}a-Barr{\´o}n, Leoncio and Morales, Julia}, title = {Spatiotemporal Distribution of Malaria in Spain in a Global Change Context}, series = {Atmosphere}, volume = {11}, journal = {Atmosphere}, number = {4}, issn = {2073-4433}, doi = {10.3390/atmos11040346}, pages = {346 -- 346}, abstract = {Malaria is one of the most cited vector-borne infectious diseases by climate change expert panels. Malaria vectors often need water sheets or wetlands to complete the disease life cycle. The current context of population mobility and global change requires detailed monitoring and surveillance of malaria in all countries. This study analysed the spatiotemporal distribution of death and illness cases caused by autochthonous and imported malaria in Spain during the 20th and 21st centuries using multidisciplinary sources, Geographic Information System (GIS) and geovisualisation. The results obtained reveal that, in the 20th and 21st centuries, malaria has not had a homogeneous spatial distribution. Between 1916 and 1930, 77\% of deaths from autochthonous malaria were concentrated in only 20\% of Spanish provinces; in 1932, 88\% of patients treated in anti-malarial dispensaries were concentrated in these same provinces. These last data reveal the huge potential that anti-malarial dispensaries could have as a tool to reconstruct historical epidemiology. Spanish autochthonous malaria has presented epidemic upsurge episodes, especially those of 1917-1922 and 1939-1944, influenced by armed conflict, population movement and damaged health and hygiene conditions. Although meteorological variables have not played a key role in these epidemic episodes, they contributed by providing suitable conditions for their intensification. After the eradication of autochthonous malaria in 1961, imported malaria cases began to be detected in 1973, reaching more than 700 cases per year at the end of the second decade of the 21st century. Therefore, consistent and detailed historical studies are necessary to better understand the drivers that have led to the decline and elimination of malaria in Europe and other temperate countries.}, language = {en} } @article{EdlerVetter, author = {Edler, Dennis and Vetter, Mark}, title = {The Simplicity of Modern Audiovisual Web Cartography: An Example with the Open-Source JavaScript Library leaflet.js}, series = {KN - Journal of Cartography and Geographic Information}, volume = {69}, journal = {KN - Journal of Cartography and Geographic Information}, number = {1}, issn = {2524-4957}, doi = {10.1007/s42489-019-00006-2}, pages = {51 -- 62}, language = {en} } @article{BrodovskiiKorovinChizhovaetal., author = {Brodovskii, Maksim and Korovin, Dmitrii and Chizhova, Maria and Brunn, Ansgar and Stilla, Uwe}, title = {Recognizing Separate Structural Elements of Churches Using Neural Network}, series = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, journal = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, abstract = {In this paper we develop a new approach to recognize structural elements of orthodox churches. We will work with 3D point clouds, received as a result of 3D point cloud acquisitions of churches, e.g. from laser scanning. Because of the large amount of points in such clouds, we have to use a projection (elevation) to decrease the calculation effort. To get meaningful images from the projection of the point cloud we do some prior segmentation of the 3D cloud. Images binary, with a predefined resolution that depends on the resolution of the 3D point cloud. To recognize elements we decide to use neural networks (Perceptron and Counter propagation neural networks) as they allow the automation of the process and have a broad range of methods to recognize images. For the subsequent 3D modeling we use analytic expressions, that describe each of the structural church elements. A further step is the deduction of those expressions that describe each of the recognized sectional views}, language = {en} } @article{RoederHeusingerBrunn, author = {R{\"o}der, Marius and Heusinger, Annett and Brunn, Ansgar}, title = {Konzeption und geometrische Bewertung der fl{\"a}chenhaften Berechnung von Digitalen Oberfl{\"a}chenmodellen aus Luftbildern}, series = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, journal = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, abstract = {Das Land Bayern erstellt zurzeit einen fl{\"a}chendeckenden 3D-Geb{\"a}udebestand. Die Erfassung erfolgt aktuell aus Punktwolken des flugzeuggetragenen Laserscannings. Die Verwendung von Digitalen Oberfl{\"a}chenmodellen (DOM) aus photogrammetrischen Befliegungen wird zurzeit diskutiert. In diesem Beitrag wird daher die Generierung von digitalen Oberfl{\"a}chenmodellen aus Luftbilddaten der regelm{\"a}ßigen Befliegung der Stadt W{\"u}rzburg untersucht. Zum Einsatz kommt die Software „Erdas Imagine 2014", die den Semi-Global Matching Algorithmus (SGM) implementiert. Das Verfahren wird unter wirtschaftlichen, die erzielten Punktwolken unter geometrischen Aspekten beurteilt. Zur Bewertung der geometrischen Qualit{\"a}t der Ergebnisse werden die erzeugten Punktwolken mit LoD2-Daten der Bayerischen Vermessungsverwaltung {\"u}berlagert und verglichen. Die Ergebnisse zeigen eine hohe geometrische Qualit{\"a}t in radiometrisch gut strukturierten Bereichen. Defizite sind in verschatteten Modellbereichen und teilweise in der Laufzeit der Berechnungen vorhanden.}, language = {de} } @article{BrunnMeyer, author = {Brunn, Ansgar and Meyer, Theresa}, title = {Calibration of a Multi-Camera Rover}, series = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, doi = {10.5194/isprs-archives-XLI-B5-445-2016}, pages = {445 -- 452}, abstract = {Multi-Camera-Rover are recently coming up for usual terrestrical surveying tasks. This technique is new for the surveyors. Although photogrammetric specialists realize the benefits of such systems immediately, surveyors have difficulties to find efficient usages. To approach this new measurement systems the technique has to be understood and the confidence on the accuray has to grow. In this paper we analyze the accuracy of a Multi-Camera-Rover using an indoor testfield by photogrammetric algorithms. The results show that the knowledge of the interior orientation parameter of the cameras and the relative orientation of the cameras is essential for precise geometric reconstructions. Knowing these additional data, high accurate results become possible.}, language = {en} } @article{ChizhovaBrunn, author = {Chizhova, Maria and Brunn, Ansgar}, title = {ОТ ФОТОСНИМКА К ОБЛАКУ ТОЧЕК: СОЗДАНИЕ 3D-МОДЕЛЕЙ НА ОСНОВЕ ОБЛАКА ТОЧЕК, ПОЛУЧЕННЫХ ФОТОГРАММЕТРИЧЕСКИМ СПОСОБОМ}, series = {Sammelband der Akademie Iwanowo 2015}, journal = {Sammelband der Akademie Iwanowo 2015}, language = {ru} } @article{HeldKaplanBurwitzetal., author = {Held, Winfried and Kaplan, Deniz and Burwitz, Henning and Brunn, Ansgar}, title = {2013 Yili Tarsus Donuk Ta{\c{s}} Y{\"u}zey ara{\c{s}}t{\i}rmas{\i}}, series = {32. Ara{\c{s}}{\i}rma Sonu{\c{c}}lar{\i} Toplant{\i}s{\i}, Gaziantep 2014}, journal = {32. Ara{\c{s}}{\i}rma Sonu{\c{c}}lar{\i} Toplant{\i}s{\i}, Gaziantep 2014}, number = {2}, issn = {1017-7663}, pages = {529 -- 540}, language = {tr} } @article{Herrmann, author = {Herrmann, Volker}, title = {Nachhaltigkeit in der Gummi- und Reifenindustrie}, series = {Kautschuk Gummi Kunststoffe}, volume = {76}, journal = {Kautschuk Gummi Kunststoffe}, pages = {8 -- 9}, language = {de} } @article{HerrmannSuhlFroschetal., author = {Herrmann, Volker and Suhl, L. and Frosch, S. and Endres, H.}, title = {Entwicklung eines Dynamisch-Mechanischen Indentationsmessger{\"a}ts zur Charakterisierung von Elastomeroberfl{\"a}chen auf der Mikrometerskala (µ-DMI)}, series = {Gummi Fasern Kunststoffe GAK}, volume = {75}, journal = {Gummi Fasern Kunststoffe GAK}, pages = {30 -- 37}, language = {de} }