Multivariate Uncertainty Maps

Multivariate Uncertainty Maps is a visualization framework that simultaneously represents uncertainty across multiple interdependent variables in spatial or multivariate data by encoding probabilistic variability and correlations through integrated visual channels such as color, texture, and glyph-based designs.

6

Publications

262

Citations

27

Authors

19

Institutions

Publications per year

2017–2026

2

Authors

27

  1. YZ
    Yue Zhang

    Northeastern University, China

    1 publications · 10 citations

    1

    h-index

  2. AG
    Anders Garpebring

    Umeå University, Sweden

    1 publications · 27 citations

    1

    h-index

  3. GZ
    George Z. Gertner

    University of Illinois Urbana-Champaign, United States

    1 publications · 50 citations

    1

    h-index

  4. JY
    Jun Yu

    Umeå University, Sweden

    1 publications · 27 citations

    1

    h-index

  5. LC
    Leilei Chen

    Xinyang Normal University, China

    1 publications · 80 citations

    1

    h-index

1–5 of 27

Venues

  1. 2

    h-index

  2. Remote Sensing of Environment

    1 publications · 50 citations

    1

    h-index

  3. 1

    h-index

  4. Magnetic Resonance in Medicine

    MRM · 1 publications · 27 citations

    1

    h-index

  5. Natural Hazards

    1 publications · 10 citations

    1

    h-index

1–5