Spatial Yield Prediction

Spatial Yield Prediction is a geospatial modeling technique that distinguishes itself by estimating crop yield variations across heterogeneous landscapes through the integration of location-specific environmental, agronomic, and remote sensing data within a unified predictive framework.

144

Publications

7.3K

Citations

599

Authors

255

Institutions

Publications per year

2017–2026

80

Authors

599

  1. JZ
    Jing Zhang

    Beijing Normal University, China

    3 publications · 167 citations

    3

    h-index

  2. JC
    Juan Cao

    Chinese Academy of Sciences, China

    3 publications · 167 citations

    3

    h-index

  3. JX
    Jialu Xu

    Zhejiang University, China

    3 publications · 352 citations

    3

    h-index

  4. WD
    William D. Batchelor

    Auburn University, United States

    3 publications · 102 citations

    3

    h-index

  5. YL
    Yuchuan Luo

    Beijing Normal University, China

    3 publications · 167 citations

    3

    h-index

1–5 of 599

Venues

  1. Remote Sensing

    10 publications · 521 citations

    10

    h-index

  2. Computers and Electronics in Agriculture

    10 publications · 672 citations

    9

    h-index

  3. Agricultural Systems

    7 publications · 368 citations

    7

    h-index

  4. 5

    h-index

  5. Agricultural and Forest Meteorology

    5 publications · 351 citations

    5

    h-index

1–5