An Open and Large Scale Dataset for Multi Modal Climate Change aware Crop Yield Predictions The CropNet dataset is an open, large scale, and deep learning ready dataset, specifically targeting climate change aware crop yield predictions for the contiguous United States (U.S.) continent at the county level. It is composed of three modalities of data, i.e., Sentinel 2 Imagery, WRF HRRR Computed Dataset, and USDA Crop Dataset, aligned in both the spatial and temporal domains, for over 2200 U.S. counties spanning 6 years (2017 2022). It is expected to facilitate researchers in developing deep learning models for timely and precisely predicting crop yields at the county level, by accounting for the effects of both short term growing season weather variations and long term climate change on crop yields. Although our initial goal of crafting the CropNet dataset is for precise crop yield prediction, we believe its future applicability is broad and can benefit the deep learning, agriculture, and meteorology communities, for exploring more interesting, critical, and climate change related applications, by using one or more modalities of data. Citation If you use our dataset, please cite our…
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