Random Forest Salinity Mapping

Random Forest Salinity Mapping is a machine learning–based salinity mapping method that employs the Random Forest algorithm to predict spatial soil salinity distributions by leveraging remotely sensed data and environmental covariates.

43

Publications

2.1K

Citations

214

Authors

114

Institutions

Publications per year

2017–2026

42

Authors

214

  1. JD
    Jianli Ding

    Xinjiang University, China

    5 publications · 250 citations

    5

    h-index

  2. RT
    Ruhollah Taghizadeh‐Mehrjardi

    University of Tübingen, Germany

    3 publications · 250 citations

    3

    h-index

  3. GZ
    Gengxing Zhao

    Shandong Agricultural University, China

    3 publications · 133 citations

    3

    h-index

  4. SY
    Shengtian Yang

    Beijing Normal University, China

    3 publications · 199 citations

    3

    h-index

  5. ZZ
    Zhe Zhang

    Hohai University, China

    2 publications · 86 citations

    2

    h-index

1–5 of 214

Venues

  1. Remote Sensing

    10 publications · 637 citations

    10

    h-index

  2. Geoderma

    3 publications · 273 citations

    3

    h-index

  3. Journal of Applied Remote Sensing

    JARS · 2 publications · 39 citations

    2

    h-index

  4. Sustainability

    2 publications · 40 citations

    2

    h-index

  5. Scientific Reports

    2 publications · 81 citations

    2

    h-index

1–5