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Visual exploration of spatial data relies heavily on spatial aggregation queries that slice and summarize the data over different regions. These queries comprise computationally-intensive point-in-polygon tests that associate data points to polygonal regions, challenging the responsiveness of visualization tools. This challenge is compounded by the sheer amounts of data, requiring a large number of such tests to be performed. Traditional pre-aggregation approaches are unsuitable in this setting since they fix the query constraints and support only rectangular regions. On the other hand, query constraints are defined interactively in visual analytics systems, and polygons can be of arbitrary shapes. In this paper, we convert a spatial aggregation query into a set of drawing operations on a canvas and leverage the rendering pipeline of the graphics hardware (GPU) to enable interactive response times. Our technique trades-off accuracy for response time by adjusting the canvas resolution, and can even provide accurate results when combined with a polygon index. We evaluate our technique on two large real-world data sets, exhibiting superior performance compared to index-based approaches.
Henry Markram, Sean Lewis Hill, Mohameth François Sy, Samuel Claude Kerrien, Carolina Johanna Elisabeth Lindqvist, Alejandra Garcia Rojas Martinez, Huanxiang Lu, Anna-Kristin Kaufmann, Jonathan Raël Lurie, Henry Genet, Pierre-Alexandre Fonta, Alexander Désiré Ulbrich, Michaël Fernand Paul Dupont, Silvia Rosario Jimenez Tejeda, Bogdan Roman, Ian Lavriushev, Didac Montero Mendez, Wojciech Adam Wajerowicz, Kenneth William Pirman, Julien Antonin Machon, Dhanesh Neela Mana, Natalia Stafeeva
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Christophe Ballif, Jonathan Emanuel Thomet, Janina Christine Isabelle Löffler, Samira Alexandra Frey