Spatial Cross-validation

Spatial Cross-Validation is a model evaluation procedure belonging to the class of cross-validation techniques, distinguished by its explicit accommodation of spatial autocorrelation through spatially structured data partitioning to provide unbiased assessment of spatial prediction models.

87

Publications

6.3K

Citations

307

Authors

189

Institutions

Publications per year

2017–2026

69

Authors

307

  1. TH
    Tomislav Hengl

    ISRIC - World Soil Information, Netherlands

    7 publications · 1.3K citations

    7

    h-index

  2. GH
    G.B.M. Heuvelink

    Wageningen University & Research, Netherlands

    6 publications · 1.5K citations

    6

    h-index

  3. MN
    Madlene Nussbaum

    Bern University of Applied Sciences, Switzerland

    5 publications · 1.2K citations

    5

    h-index

  4. MN
    Marvin N. Wright

    Leibniz Institute for Prevention Research and Epidemiology - BIPS, Germany

    4 publications · 1.2K citations

    4

    h-index

  5. HM
    Hanna Meyer

    Philipps University of Marburg, Germany

    4 publications · 218 citations

    4

    h-index

1–5 of 307

Venues

  1. Remote Sensing

    9 publications · 369 citations

    8

    h-index

  2. PeerJ

    3 publications · 1.2K citations

    3

    h-index

  3. Environmental Science & Technology

    3 publications · 255 citations

    3

    h-index

  4. 2

    h-index

  5. 2

    h-index

1–5