Map Memory Optimization

Map Memory Optimization is a computational framework within web map performance optimization that specifically governs the efficient allocation, caching, and retrieval of spatial data in memory to minimize latency and resource consumption during dynamic map rendering and interaction.

11

Publications

1.1K

Citations

32

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

32

  1. KL
    Kaihua Liu

    Tianjin University, China

    1 publications · 87 citations

    1

    h-index

  2. RC
    Ricardo Cannizzaro

    RMIT University, Australia

    1 publications · 66 citations

    1

    h-index

  3. ZD
    Zhiming Ding

    Chinese Academy of Sciences, China

    1 publications · 48 citations

    1

    h-index

  4. BW
    B.D. Woerner

    Virginia Tech, United States

    1 publications · 13 citations

    1

    h-index

  5. YL
    Yaguang Li

    University of Southern California, United States

    1 publications · 48 citations

    1

    h-index

1–5 of 32

Venues

  1. arXiv (Cornell University)

    Repository · 1 publications · 17 citations

    1

    h-index

  2. Assembly Automation

    1 publications · 20 citations

    1

    h-index

  3. Robotics and Autonomous Systems

    1 publications · 66 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Communications Letters

    1 publications · 87 citations

    1

    h-index

1–5