Adaptive Streamline Sampling

Adaptive Streamline Sampling is a streamline visualization method that dynamically adjusts seeding density based on local flow field characteristics to optimally resolve flow structures while minimizing visual clutter.

1

Publications

45

Citations

15

Authors

8

Institutions

Publications per year

2017–2026

1

Authors

15

  1. KH
    Kendra Hayashi

    University of California, Santa Cruz, United States

    1 publications · 45 citations

    1

    h-index

  2. JP
    John P. Ryan

    Monterey Bay Aquarium Research Institute, United States

    1 publications · 45 citations

    1

    h-index

  3. JM
    James M. Birch

    Monterey Bay Aquarium Research Institute, United States

    1 publications · 45 citations

    1

    h-index

  4. RM
    Raphael M. Kudela

    University of California, Santa Cruz, United States

    1 publications · 45 citations

    1

    h-index

  5. CM
    Christina M. Mikulski

    NOAA National Ocean Service, United States

    1 publications · 45 citations

    1

    h-index

1–5 of 15

Venues

  1. Harmful Algae

    1 publications · 45 citations

    1

    h-index

1–1