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LIBKDV: A Versatile Kernel Density Visualization Library for Geospatial Analytics

Summary: LIBKDV: a versatile kernel density visualization library for geospatial analytics. Complexity-optimized algorithms enable high-resolution KDV on large-scale data, accelerating computation and enabling bandwidth-tuning and spatiotemporal analyses beyond existing tools. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
13030
Venue
VLDB
Year
2022
Pagerank
-
Overall Rank
13,423 | 7.91%
DOI
10.14778/3554821.3554855

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Authors

BibTeX Citation

@article{chan_vldb22,
        title = {{LIBKDV: A Versatile Kernel Density Visualization Library for Geospatial Analytics}},
        author = {Chan, Tsz Nam and Ip, Pak Lon and Zhao, Kaiyan and U, Leong Hou and Choi, Byron and Xu, Jianliang},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {12},
        pages = {3606--3609},
        doi = {10.14778/3554821.3554855},
        url = {https://doi.org/10.14778/3554821.3554855},
        year = {2022}
}

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