Publications – Institute of Cartography and Geoinformatics

Peters, T., Brenner, C., & Schindler, K. (2023): Semantic segmentation of mobile mapping point clouds via multi-view label transfer, ISPRS Journal of Photogrammetry and Remote Sensing, 202, 30-39.

Reviewed Journal Articles and Book Chapters

Sester, M., Winter, S., Millonig, A., Pereira, F. (Hg.) (2023): Proceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility. SuMob '23: 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility. Hamburg Germany, 13.11.2023., ACM, New York, NY, USA.

Editorial Board

Stefan Fuest, Jens Golze, Oskar Wage, Udo Feuerhake, Sharon Dornbusch, Monika Sester (2023): Visuelle Kommunikation von Fahrradrouten mittels kartographischer Symbolisierung, KN - Journal of Cartography and Geographic Information
DOI: https://doi.org/10.1007/s42489-022-00130-6 Description: Abstract With the increasing promotion of sustainable forms of mobility in the context of the traffic policies, bicycles represent an environmentally friendly alternative to motorized private transport This especially accounts for coping with inner-city routes. However, in contrast to car drivers, the perceived riding comfort and safety of cyclists strongly depends on route characteristics, such as surface conditions or traffic infrastructure. However, currently available bicycle navigation systems hardly consider these factors relevant for the route choice of cyclists, and the visualization is often limited to a simple highlighting of the recommended route. Therefore, this article investigates the appropriateness of different cartographic representations of bicycle routes for the visual communication of route characteristics, such as type of terrain, terrain roughness, terrain gradient, and interruptions. A user survey is conducted to assess the effectiveness, attractiveness, appropriateness, and dispensability of a legend of the various display options for the different route features. The results of the survey indicate that many of the proposed visualization variants are appropriate for the visual communication of bicycle routes. This concerns in particular color representations as well as representations using symbols. However, with respect to the bicycle route features tested, the most appropriate representation heavily depends on the information being communicated. The findings of this study should contribute to the development of route visualizations that are specifically tailored to the needs of cyclists and thus support developers of bicycle navigation systems in making design decisions. Zusammenfassung Mit zunehmender Förderung nachhaltiger Mobilitätsformen im Rahmen der Verkehrswende stellt das Fahrrad eine umweltfreundliche Alternative zum motorisierten Individualverkehr dar - insbesondere zur Bewältigung innerstädtischer Wege. Im Gegensatz zu Autofahrenden hängt der empfundene Fahrkomfort und das Sicherheitsempfinden von Radfahrenden jedoch stark von Routenmerkmalen wie der Oberflächenbeschaffenheit oder der Verkehrsinfrastruktur ab. Aktuell verfügbare Systeme zur Fahrradnavigation berücksichtigen diese für die Routenwahl von Radfahrenden relevanten Faktoren jedoch kaum und die Visualisierung beschränkt sich vielfach auf eine einfache Hervorhebung der empfohlenen Route. In dieser Arbeit wird daher untersucht, inwieweit sich verschiedene kartographische Darstellungsvarianten für Fahrradrouten zur visuellen Kommunikation der Routenmerkmale Art des Untergrunds, Untergrundrauigkeit, Geländeneigung und Fahrtunterbrechungen, als angemessen erweisen. Im Rahmen einer Nutzerbefragung wird die Effektivität, Attraktivität, Eignung und Entbehrlichkeit einer Legende der verschiedenen Darstellungsvarianten für die unterschiedlichen Routenmerkmale überprüft. Die Ergebnisse der Umfrage zeigen auf, dass viele der vorgeschlagenen Visualisierungsvarianten angemessen für die visuelle Kommunikation von Fahrradrouten sind. Dies betrifft insbesondere Farbdarstellungen sowie Darstellungen mit Symbolen oder Signaturen. Hinsichtlich der getesteten Fahrradroutenmerkmale hängt die angemessenste Darstellung jedoch stark von der zu kommunizierenden Information ab. Die Erkenntnisse dieser Studie sollen zur Entwicklung von speziell auf die Bedürfnisse der Radfahrenden zugeschnittenen Routenvisualisierungen beitragen und somit Entwicklern von Fahrradnavigationssystemen bei Designentscheidungen unterstützen.

Reviewed Journal Articles and Book Chapters

Stefania Zourlidou (2023): Traffic Regulation Recognition from GPS Data, Deutsche Geodätische Kommission bei der Bayerischen Akademie der Wissenschaften, Reihe C, Nr. 898, (identisch mit / identical with: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover, Nr. 384, Hannover 2023) | File |
ISBN: 978-3-7696-5310-6
ISSN: 0174-1454

Monographs

Teusch, J.; Gremmel, J. N.; Koetsier, C.; Johora, F. T.; Sester, M.; Woisetschläger, D. M.; Muller, J. P. (2023): A Systematic Literature Review on Machine Learning in Shared Mobility, IEEE Open Journal of Intelligent Transportation Systems 4, S. 870–899.
DOI: doi: 10.1109/OJITS.2023.3334393

Reviewed Journal Articles and Book Chapters

Tim P. J. Schimansky, Oskar Wage, Jens Golze, Udo Feuerhake (2023): Bike Sensor Data Set for Vehicle Encounters: A Comprehensive Open Data Resource, Research Data Repository Leibniz University Hannover More info
DOI: 10.25835/e6iagxo9

Software and Data

Tim Peter Jörg Schimansky, Oskar Wage, Jens Golze and Udo Feuerhake (2023): Smartphone Based Detection of Vehicle Encounters, 16th ACM SIGSPATIAL International Workshop on Computational Transportation Science | File |
DOI: https://doi.org/10.1145/3615895.3628173 Description: Riding a bicycle in shared traffic alongside motor vehicles causes discomfort or even stress for many cyclists. Avoiding busy or crowded roads is only possible with good local knowledge, as no data is available on the frequency of encounters with motor vehicles for most roads. Acquiring a data set that combines smartphone sensor data with known vehicle encounters can become the foundation for a smartphone based moving vehicle detector. Therefore, readings from the omnipresent smartphone sensors magnetometer and barometer can be exploited as indicators of passing vehicles.      In this paper, a novel approach is presented to detect vehicle encounters in smartphone sensor data. For this purpose, a modular mobile sensor platform is first constructed and set up to collect smartphone, camera and ultrasonic sensor data in real traffic scenarios. The platform is designed to be used with various sensor configurations to serve a broader set of use cases in the future. In the presented use case, the platform is constructed to create a reference data set of vehicle encounters consisting of location information, direction, distance, speed and further metadata. To this end, a methodology is presented to process the collected camera images and ultrasonic distance data.      Furthermore, two smartphones are used to collect raw data from their magnetometer and barometric sensor. Based on both, the reference and the smartphones' data set, a classifier for the detection of vehicle encounters is then trained to operate on pure smartphone sensor data. Experiments on real data show that a Random Forest classifier can be successfully applied to recorded smartphone sensor data. The results prove that the presented approach is able to detect overtaking vehicle encounters with a F1-score of 71.0\,\%, which is sufficient to rank different cycling routes by their 'stress factor'.

Reviewed Conference Papers

Vinu kamalasanan, Ahmed Al-Taan, Steffen Busch, Monika Sester (2023): Enhancing Safety using AR Headsets with Motion Prediction Visualization | File |

Discussion Paper

Vinu Kamalasanan, Melanie Kruger, Monika Sester (2023): Developing a Cyclist 3D GameObject for a Mixed Reality Interaction, IEEE VR Workshop 2023 | File |

Discussion Paper

Wang, F., Prominski, M., Han, J., & Sester, M. (2023): Locality and the adaptation of river‐related built environment, River Research and Applications, 39.
DOI: https://doi.org/10.1002/rra.4193

Editorial Board

Yuan, Y., Cheng, H., Yang, M. Y., & Sester, M. (2023): Generating Evidential BEV Maps in Continuous Driving Space, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 204, Pages 27-41
DOI: https://doi.org/10.1016/j.isprsjprs.2023.08.013
ISSN: ISSN 0924-2716

Reviewed Journal Articles and Book Chapters

Zhang W., Cheng H., Johora F.T., Sester M. (2023): ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction, IEEE Intelligent Vehicles Symposium, Proceedings
DOI: 10.1109%2fIV55152.2023.10186643

Reviewed Conference Papers

Zou, Q., Brenner, C., & Sester, M. (2023): Gaussian Process Mapping of Uncertain Building Models with GMM as Prior, IEEE Robotics and Automation Letters
DOI: 10.1109/LRA.2023.3303694
ISSN: 23773766

Reviewed Journal Articles and Book Chapters

Bill, R., Blankenbach, J., Breunig, M., Haunert, J. H., Heipke, C., Herle, S., Maas, H. G., Mayer, H., Meng, L., Rottensteiner, F., Schiewe, J., Sester, M., Sörgel, U. & Werner, M. (2022): Geospatial Information Research: State of the Art, Case Studies and Future Perspectives, PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 90, 4, S. 349-389 41 S.

Reviewed Journal Articles and Book Chapters

Cheng, H., Lei, H., Zourlidou, S., Sester, M. (2022): Traffic Control Recognition with an Attention Mechanism Using Speed-Profile and Satellite Imagery data., The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022, pp. 287–293

Reviewed Journal Articles and Book Chapters

Florian Politz, Monika Sester (2022): BUILDING CHANGE DETECTION IN AIRBORNE LASER SCANNING AND DENSE IMAGE MATCHING POINT CLOUDS USING A RESIDUAL NEURAL NETWORK, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 625–632
DOI: https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-625-2022

Conference Papers

Harke, F. H., Merk, M., Otto, P. (2022): Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices., Symmetry 14(7)
DOI: https://doi.org/10.3390/sym14071474

Reviewed Journal Articles and Book Chapters

Heumann, Maximilian; Wage, Oskar; Feuerhake, Udo; Breitner, Michael H.; Sester, Monika (2022): Waren effizient und nachhaltig geliefert : Die USEfUL Webapplikation, Unimagazin 3/4 (2022), S. 52-53
DOI: https://doi.org/10.15488/13058

Other Contributions

J. Golze, U. Feuerhake and M. Sester (2022): Spatial Analysis of External Influences on Traffic Accidents using Open Data, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
DOI: 10.5194/isprs-archives-XLIII-B4-2022-125-2022

Conference Papers

Koetsier, C., Fiosina, J., Gremmel, J. N., Müller, J. P., Woisetschläger, D. M., & Sester, M. (2022): Detection of anomalous vehicle trajectories using federated learning, ISPRS Open Journal of Photogrammetry and Remote Sensing, 4, 100013 | File |
DOI: 10.1016/j.ophoto.2022.100013

Reviewed Journal Articles and Book Chapters

Publications of the Institute of Cartography and Geoinformatics