Cross-validation For Interpolation

Cross-Validation for Interpolation is a model evaluation technique that systematically partitions spatial data into training and test subsets to assess the predictive accuracy of an interpolation method by quantifying the discrepancy between observed and predicted values at withheld locations.

29

Publications

3K

Citations

97

Authors

50

Institutions

Publications per year

2017–2026

11

Authors

97

  1. BM
    Blazan Mijatovic

    University of Kentucky, United States

    1 publications · 20 citations

    1

    h-index

  2. PV
    Péter Varga

    Constantine the Philosopher University in Nitra, Slovakia

    1 publications · 27 citations

    1

    h-index

  3. QH
    Qingye Hou

    China University of Geosciences (Beijing), China

    1 publications · 18 citations

    1

    h-index

  4. RA
    Rodrigo Augusto Ferreira De Souza

    Universidade do Estado do Amazonas, Brazil

    1 publications · 31 citations

    1

    h-index

  5. CB
    Christian Berndt

    GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany

    1 publications · 128 citations

    1

    h-index

1–5 of 97

Venues

  1. Journal of Geographic Information System

    2 publications · 155 citations

    2

    h-index

  2. Computers & Geosciences

    CAGEO · 2 publications · 123 citations

    2

    h-index

  3. Earth and Space Science

    2 publications · 56 citations

    2

    h-index

  4. International Journal of Climatology

    2 publications · 666 citations

    2

    h-index

  5. Anais da Academia Brasileira de Ciências

    1 publications · 31 citations

    1

    h-index

1–5