Predictive Soil Mapping

Predictive Soil Mapping is a geospatial modeling approach that systematically infers the spatial distribution of soil properties or classes by leveraging environmental covariates and statistical or machine learning methods to predict soil variation in unsampled locations.

146

Publications

10K

Citations

529

Authors

249

Institutions

Publications per year

2017–2026

79

Variants

Digital Soil Mapping

Authors

529

  1. AZ
    A‐Xing Zhu

    University of Wisconsin–Madison, United States

    9 publications · 1.1K citations

    9

    h-index

  2. BM
    Budiman Minasny

    The University of Sydney, Australia

    7 publications · 1.1K citations

    7

    h-index

  3. AB
    Alex B. McBratney

    The University of Sydney, Australia

    7 publications · 1.6K citations

    7

    h-index

  4. CZ
    Chuanrong Zhang

    University of Connecticut, United States

    5 publications · 361 citations

    5

    h-index

  5. ÉG
    Élvio Giasson

    Universidade Federal do Rio Grande do Sul, Brazil

    5 publications · 161 citations

    5

    h-index

1–5 of 529

Venues

  1. Geoderma

    37 publications · 3.4K citations

    29

    h-index

  2. CATENA

    10 publications · 634 citations

    10

    h-index

  3. Geoderma Regional

    5 publications · 556 citations

    5

    h-index

  4. European Journal of Soil Science

    4 publications · 238 citations

    4

    h-index

  5. Soil Science Society of America Journal

    SSSAJ · 4 publications · 219 citations

    4

    h-index

1–5