Interpolation Uncertainty Visualization

Interpolation Uncertainty Visualization is a methodological framework within spatial uncertainty visualization that specifically represents the uncertainty associated with estimating values at unsampled locations through interpolation techniques, distinguishing itself by focusing on the propagation, quantification, and graphical depiction of errors and variability inherent in spatial prediction models.

1

Publications

34

Citations

3

Authors

0

Institutions

Publications per year

2017–2026

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Authors

3

  1. AT
    Alex T. Pang

    1 publications · 34 citations

    1

    h-index

  2. SK
    Suresh K. Lodha

    University of California, Santa Cruz, United States

    1 publications · 34 citations

    1

    h-index

  3. CM
    Craig M. Wittenbrink

    University of California, Santa Cruz, United States

    1 publications · 34 citations

    1

    h-index

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