Abstract
Today, with the development of location service providers and equipment providing location services, spatial data can be obtained from many different devices. This data can be used in various applications. Data are affected by both geographic and human factors, and sometimes they may show homogeneous and sometimes heterogeneous distributions. Displaying so much data in a way that users can perceive requires special methods. This study to be written aims at expressing many spatial data to the users in the most efficient way. As a result of this study, it is aimed to visualize spatial data consisting of many (e.g. millions) points globally or regionally and to do this in real time.
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References
Voronoi, G.: Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs. Journal für die reine und angewandte Mathematik (Crelles J.) 1908(134), 198–287 (1908)
Marko: Real-time cave destruction using 3D voronoi (2018)
Worboys, M.: GIS: a computer science perspective (1994)
Chang, K.-T.: Programming ArcObjects with VBA: A Task-Oriented Approach. CRC Press (2007)
Cakmak, B.: Complexity management in visualization of very large spatial data, pp. 1–68 (2017)
Guo, D.: Flow mapping and multivariate visualization of large spatial interaction data. IEEE Trans. Vis. Comput. Graph. 15(6), 1041–1048 (2009)
Zhu, X., Guo, D.: Mapping large spatial flow data with hierarchical clustering. Trans. GIS 18(3), 421–435 (2014)
Secchi, P., Vantini, S., Vitelli, V.: Bagging Voronoi classifiers for clustering spatial functional data. Int. J. Appl. Earth Obs. Geoinf. 22, 53–64 (2013)
Komzak, J., Eisenstadt, M.: Visualisation of entity distribution in very large scale spatial and geographic information systems. In: KMITR-116, KMi. The Open University (2001)
Smorodinsky, S.: Geometric permutations and common transversals. Ph.D. dissertation. Citeseer (1998)
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Ertekin, M.T., Genç, B. (2023). User Oriented Visualization of Very Large Spatial Data with Adaptive Voronoi Mapping (AVM). In: Hemanth, D.J., Yigit, T., Kose, U., Guvenc, U. (eds) 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering. ICAIAME 2022. Engineering Cyber-Physical Systems and Critical Infrastructures, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-031-31956-3_45
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DOI: https://doi.org/10.1007/978-3-031-31956-3_45
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