Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing

doi:doi:10.57702/00jqeiia

Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing

Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. The dataset is used for crop yield prediction, specifically for soybean, wheat, and rapeseed crops in Argentina, Uruguay, and Germany.

Data and Resources

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The json representation of the dataset with its distributions based on DCAT.
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Cite this as

Hiba Najjar, Miro Miranda, Marlon Nuske, Ribana Roscher, Andreas Dengel (2024). Dataset: Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing. https://doi.org/10.57702/00jqeiia

DOI retrieved: December 2, 2024

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Hiba Najjar
More Authors	Miro Miranda Marlon Nuske Ribana Roscher Andreas Dengel