Northwestern Lower Saxony - Sustainable New (4N): Geo-Toolbox
2022-2025
Books and Papers
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Reznicek, J.; Luhmann, T.; Hastedt, H.; Jepping, C. (2016):
Influence of raw image preprocessing and other selected processes on accuracy of close-range photogrammetric systems according to VDI 2634. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B5, 107-113
, doi: 10.5194/isprs-archives-XLI-B5-107-2016
Wichmann, Andreas; Kada, Martin (2016):
Joint Simultaneous Reconstruction of Regularized Building Superstructures from Low-Density LiDAR Data Using ICP. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
, doi: https://doi.org/10.5194/isprs-annals-III-3-371-2016 , Weblink
Jepping, C.; Schulz, J.-U.; Luhmann, T. (2016):
Konzept zur Modellierung kinematischer Rotorblattverformungen an Windkraftanlagen. Allgemeine Vermessungsnachrichten (AVN), 1, 3-10
Luhmann, T. (2016):
Learning Photogrammetry with Interactive Software Tool PhoX. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B6, 39-44
, doi: 10.5194/isprs-archives-XLI-B6-39-2016
Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin (2016):
Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing. Sensors
, doi: https://doi.org/10.3390/s16060932 , Weblink
Presentations
Luhmann, T.
:
Optische 3D-Messtechnik im Kontext von Industrie 4.0.
Technische Universität Dresden,
Dezember 2019
Brinkhoff, T.
:
Geodatenbanksysteme.
CAS Räumliche Informationssysteme, ETH Zürich, Schweiz,
Dezember 2019
Brinkhoff, T.
:
What is Special About Spatial Data Management?.
Invited Keynote, 11th GeoMundus Conference 2019, Castellón de la Plana, Spain,
November 2019
Brinkhoff, T.
:
The Analysis of Spatial Sensor Data by Data Stream Management Systems.
Workshop, 11th GeoMundus Conference 2019, Castellón de la Plana, Spain,
November 2019
Projects
funded by: Niedersächsisches Vorab
Transformation and structural change in rural areas mean changes in space and time. Such spatiotemporal data is to be managed and processed by our “Geo-Toolbox”. It uses digital technologies such as databases and geographic information systems &#... more
people
Prof. Dr. Thomas Brinkhoff (head) Prof. Dr. rer. nat. habil. Roland Pesch (head) Prof. Dr. rer. nat. Frank Schüssler (head) Tobias Werner, M.Sc. (10.2022-) Jonas Schoo, M.Sc. (06.2022-) Maren Leiz, M.Sc. (08.2022-) Dr. Amirmohammad Ghavimi (08.2022-)
Prof. Dr. Thomas Brinkhoff (head) Prof. Dr. rer. nat. habil. Roland Pesch (head) Prof. Dr. rer. nat. Frank Schüssler (head) Tobias Werner, M.Sc. (10.2022-) Jonas Schoo, M.Sc. (06.2022-) Maren Leiz, M.Sc. (08.2022-) Dr. Amirmohammad Ghavimi (08.2022-)
funded by: Bundesministerium für Bildung und Forschung
The Project – „CoSAIR – Collaborative Spatial Artificial Intelligence in Realtime“ is funded by the Federal Ministry of Education and Research within the program „Research at Universities of Applied Sciences“ in order to create, consolida... more
people
Prof. Dr. Sascha Koch (head) Oliver Kahmen, M.Sc. (04.2022-07.2022) Tobias Neiß-Theuerkauff, M.Sc. Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann Mareike Fincken, M.Sc. (09.2023-)
Prof. Dr. Sascha Koch (head) Oliver Kahmen, M.Sc. (04.2022-07.2022) Tobias Neiß-Theuerkauff, M.Sc. Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann Mareike Fincken, M.Sc. (09.2023-)
funded by: Bundesministerium für Bildung und Forschung
This project focuses on the development of an automated production chain that will generate a digital image of the catalyst extrusion process. Using online measurement methods, the IAPG sub-project aims to detect batch-related fluctuations in the mat... more
people
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Simon Albers, M.Sc. (03.2023-10.2023) Robin Rofallski, M.Sc.
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Simon Albers, M.Sc. (03.2023-10.2023) Robin Rofallski, M.Sc.
Bachelor & Master Theses
Analyse und Vergleich der geometrischen Eigenschaften von Referenzdaten und KI-Ergebnissen für die automatische Gebäudeerkennung in Luftbildern (2024/2)
Maschinelles Lernen für die Identifikation von baulichen Erweiterungen an Gebäuden anhand geometrischer Merkmale von ALKIS- und durch KI bestimmten Hausumringen (2024/2)
Integration und Verteilung von ALKIS-Grunddaten und Fortführungsdaten in Echtzeit mittels Open-Source-Technologien (2024/2)
Design und prototypische Implementierung einer Georeferenzierung im Web-Browser mittels Javascript und dem Open-Source-Geoportal „Masterportal“ (2024/2)
Möglichkeiten der Herstellung synthetischer Trainingsdaten für KI-Modelle in einer Game-Engine aus Geodaten (2024/2)