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Therefore, we propose ConcaveCubes, a cluster-based data cube to support interactive visualization of large-scale multidimensional urban data. ... We propose a novel concave hull construction method to support boundary based cluster map visualization, where real-world geographical semantics are preserved without any information loss. ... Zhifeng Bao is supported by a Google Faculty Award. Hanan Samet is supported in part by the National Science Foundation of the US under grant IIS-13-20791. ...doi:10.1111/cgf.13414 fatcat:g5ib3s3kmbel5g7bumrawx6txy
The multidimensional nature of spatial data poses a challenge for visualization. ... Based on the analysis and participant feedback, we demonstrate that Phoenixmap 1) allows users to perceive and compare spatial distribution data efficiently; 2) frees up graphics space with a concise form ... ACKNOWLEDGMENTS The authors would like to appreciate the support and feedback from all participants in our user study, in particular Siwei Chen from Cornell University for the contribution on the statistical ...doi:10.1109/tvcg.2019.2945960 pmid:31603789 fatcat:mkdgzcekwjfe7ppcjnzeoulzpy
Visualizing multidimensional spatial data is an essential visual analysis strategy, it helps us interpret and communicate how different variables correlate to geographical information. ... In the end, we demonstrated two applications with real-world religious infrastructural data by AuroraMap to visualize geospatial data within complex boundaries and compare multiple variables in one graph ... Compared to existing heatmaps or binned plots, a cluster-based data cube has been utilized to support interactive visualization of large-scale multidimensional spatial data  . Li et al. ...doi:10.25394/pgs.12206438 fatcat:meuqhomaafenjnpgoy6rupbhre