The ABMMDLF model achieves an R² of 0.89 for spatio-temporal crop yield prediction by combining multi-modal satellite, soil, and climate inputs with CNN spatial features and temporal attention.
Deep learning-based crop yield prediction using remote sensing
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Attention-based Multi-modal Deep Learning Model of Spatio-temporal Crop Yield Prediction with Satellite, Soil and Climate Data
The ABMMDLF model achieves an R² of 0.89 for spatio-temporal crop yield prediction by combining multi-modal satellite, soil, and climate inputs with CNN spatial features and temporal attention.