Wheat yield estimation using remote sensing data based on machine learning approaches

HIGHLIGHTS

• who: Enhui Cheng from the University of Granada, Spain have published the research: Wheat yield estimation using remote sensing data based on machine learning approaches, in the Journal: (JOURNAL) of June/16,/2021
• what: In this study, the four vegetation index feature variables (SR, EVI, NDWI, and REP) were input to the proposed model for training, and the importance of each feature was calculated using the PFI method based on the LSTM neural_network that the authors constructed. The model that had the largest value of R2 and the smallest values of MAE and RMSE was . . .
  

   

  

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