Tessio Novack (Assistant Professor)
Our observation and representations of the world are not objective. Instead, they are dependent on our perception capabilities, cultural context, and social biases. Aligned with this epistemological (and critical) stance, I am interested in theoretical and practical approaches for extracting and representing culture-bound spatial knowledges and conceptualizations of space. More specifically, I am interested in ways emerging digital data, computational methods, and Geographic Information Systems can be combined for representing alternative perceptions of the urban space and, ultimately, for advancing constructive social changes.
Before joining CIM as Assistant Professor and the convenor of the Urban Analytics and Visualisation degree in August 2020, I was a postdoctoral researcher at the GIScience Research Group from Heidelberg University (Germany). Prior to that, I held a DAAD scholarship with which I pursued my doctorate in urban remote sensing at the Technical University of Munich (Germany).
GIScience; critical GIS; volunteered geographic information; citizen science; urban geography.
Novack, T.; Vorbeck, L.; Lorei, H.; Zipf, A. (2020) Towards detecting building facades with graffiti artwork based on street view images. ISPRS International Journal of Geo-Information, 9, 98.
Zhiyong, W., Novack, T., Yan, Y., Zipf, A. (2020) Quiet route planning for pedestrians in traffic noise-polluted environments. IEEE Transactions on Intelligent Transportation Systems. DOI:10.1109/TITS.2020.3004660
Juhász, L.; Novack, T.; Hochmair, H.H.; Qiao, S. (2020) Cartographic vandalism in the era of location-based games - The case of OpenStreetMap and Pokémon Go. ISPRS International Journal of Geo-Information, 9, 197.
Lautenbach, S.,...,Novack, T.,..., Zipf, A. (2020) Optimal ans Ziel: Routing-Dienste auf Basis nutzergenerierter Geodaten - Herausforderungen und Lösungsansätze für globale Datensätze. In: Geo-IT in Mobilität und Verkehr. 1 ed. Berlin: Wichmann, pp. 89-108. ISBN 978-3-87907-682-6(3)
Hu, X.; Ding, L.; Shang, J.; Fan, H.; Novack, T.; Noskov, A.; Zipf, A. (2020) Data-driven approach to learning salience models of indoor landmarks by using genetic programming. International Journal of Digital Earth, DOI: 10.1080/17538947.2019.1701109.
Novack, T.; Wang, Z.; Zipf, A. (2018) A system for generating customized pleasant pedestrian routes based on OpenStreetMap data. Sensors, 18, 3794.
Novack, T., Peters, R., Zipf, A. (2018) Graph-based matching of points-of-interest from collaborative geo-datasets. ISPRS International Journal of Geo-Information, 7(3), p. 117-134.
Novack, T., Stilla, U. (2018) Classifying the built-up structure of urban blocks with probabilistic graphical models and TerraSAR-X spotlight imagery. Remote Sensing, 10, 842.
Novack, T., Kux, H. J. H., Feitosa, R. Q., Costa, G. A. O. P. (2014) A knowledge-based, transferable approach for block-based urban land-use classification. International Journal of Remote Sensing. v.35, p. 4739–4757.
Novack, T., Esch, T., Kux, H. J. H., Stilla, U. (2011) Machine learning comparison between WorldView-2 and QuickBird-2-simulated imagery regarding object-based urban land cover classification. Remote Sensing, v.3, p. 2263 – 2282.
Centre for Interdisciplinary Methodologies
University of Warwick
Email: Tessio dot Novack at warwick dot ac dot uk
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