Visualization of Spatial Point Data
Spatial point data refers to data that is connected to one point in space, often the earth. Therefore, it's common in earth sciences, when data is measured at different locations, but e.g., geo-tagged social media content fits the definition too. Visualization of this data type depends on data attributes, such as uni- or multivariate, quantitative or categorical, and also tasks, as can be seen from dot maps (density is important) and bubble maps (value is important). An interactive visualization leads to more challenges, because e.g., glyphs need to be merged/replaced depending on the current zoom level.
Provide a systematic overview of visualization approaches for spatial point data.
 M. Gröbe and D. Burghardt, “Micro diagrams: visualization of categorical point data from location-based social media,” Cartography and Geographic Information Science, vol. 47, no. 4, pp. 305–320, Jul. 2020, doi: 10.1080/15230406.2020.1733438.
 A. Chua and A. V. Moere, “BinSq: visualizing geographic dot density patterns with gridded maps,” Cartography and Geographic Information Science, vol. 44, no. 5, pp. 390–409, Sep. 2017, doi: 10.1080/15230406.2016.1174623.
 L. McNabb and R. S. Laramee, “Multivariate Maps—A Glyph-Placement Algorithm to Support Multivariate Geospatial Visualization,” Information, vol. 10, no. 10, p. 302, Sep. 2019, doi: 10.3390/info10100302.
 J. Jo, F. Vernier, P. Dragicevic, and J.-D. Fekete, “A Declarative Rendering Model for Multiclass Density Maps,” IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 1, pp. 470–480, Jan. 2019, doi: 10.1109/TVCG.2018.2865141.
 J. Zhang, A. Malik, B. Ahlbrand, N. Elmqvist, R. Maciejewski, and D. S. Ebert, “TopoGroups: Context-Preserving Visual Illustration of Multi-Scale Spatial Aggregates,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver Colorado USA, May 2017, pp. 2940–2951, doi: 10.1145/3025453.3025801.