Master Theses (finished)
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Analysis of 3D City Data Regarding SubtainabilityClimate change and rapid urbanization are intensifying heat stress in cities, raising concerns for public health and urban livability. This thesis examines how 3D geospatial data and shadow analysis can be applied to assess urban microclimates and enhance pedestrian comfort, focusing on the Linden-Nord district of Hannover, Germany. Utilizing mobile mapping point clouds, 3D building models, and a digital terrain model, a digital surface model was generated to simulate solar radiation for a representative summer day (25th July 2025). Shadow analysis from solar radiation was conducted in ArcGIS Pro to quantify shading patterns and their impacts, while also visualizing areas with higher and lower solar radiation potential. The results revealed clear temporal and spatial variations: radiation increased from morning to a midday peak before declining in the afternoon. The analysis quantified the shading contributions of trees, buildings, and their combined effects, showing that buildings accounted for the largest share, whereas trees offered a smaller but consistent contribution. Although thresholding in shadow delineation introduced some uncertainty, the overall balance between shadow cast by buildings and trees remained robust. To further support outdoor comfort, a radiation-based shortest path analysis was implemented through network analysis in ArcGIS Pro. The routing results demonstrated that shaded paths are feasible and adaptable to the time of day and the distribution of urban features. Although longer than the shortest path, these shaded routes provided substantial reductions in solar exposure, in some cases exceeding 50%, depending on the time of day and the specific origin-destination pair. The study underscores the complementary role of built structures and vegetation in shaping urban microclimates and demonstrates the potential of shadow-based routing to enhance pedestrian comfort. These findings offer practical insights for sustainable urban design and heat-resilient mobility planning.Led by: Sester, Thiemann, GolzeTeam:Year: 2025
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Open Bachelor Theses
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Detection of Signatures in old Maps using Deep LearningOld maps contain a lot of interesting information of the past reality. Most of maps are, however, only available in analogue form, and thus difficult to query and analyse automatically. The goal of this thesis is to explore modern deep learning methods to automatically detect signatures on old maps. There will be a concentration on certain types of objects, e.g. trees or buildings.Led by: Thiemann, SesterYear: 2023
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Kartographie: Automatische Platzierung von BöschungsschraffenFür die Darstellung von Wällen und Gräben in archäologischen Plänen werden Schraffen verwendet. Anders als bei neuzeitlichen künstlichen Böschungen sind die historischen Böschungen durch Einwirkung der Erosion sehr unregelmäßig geformt. Standardalgorithmen scheitern aus diesem Grund bei der automatischen Anordnung der Schraffen.Led by: ThiemannYear: 2019
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Homogenisierung der GebäudeausrichtungTopographischen Karten 1 : 25.000 werden Gebäude noch grundrissähnlich dargestellt. Detailierte Gebäudegrundrisse aus dem Kataster (ALKIS) müssen dazu generalisert (klassifiziert, selektiert, aggregiert, vereinfacht, betont, verdrängt) werden. Ein Aspekt der Generalisierung ist die homogene Ausrichtung der Gebäude.Led by: ThiemannYear: 2019
Open Master Theses
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Detection of Signatures in old Maps using Deep LearningOld maps contain a lot of interesting information of the past reality. Most of maps are, however, only available in analogue form, and thus difficult to query and analyse automatically. The goal of this thesis is to explore modern deep learning methods to automatically detect signatures on old maps. There will be a concentration on certain types of objects, e.g. trees or buildings.Led by: Thiemann, SesterYear: 2023
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