CropClimateX: A large scale, multitask, multisensory dataset for climate aware crop monitoring in the United States from 2018–2022 Adrian Höhl, Stella Ofori Ampofo, Miguel Ángel Fernández Torres, Rıdvan Salih Kuzu, and Xiao Xiang Zhu Repository: github.com/drnhhl/CropClimateX Paper: https://doi.org/10.1038/s41597 026 06611 x License: CC BY 4.0 Contact : adrian.hoehl@tum.de The database includes 15,500 small data cubes (i.e., minicubes), each with a spatial coverage of 12x12km, spanning 1527 counties in the US. The minicubes comprise data from multiple sensors (Sentinel 1/2, Landsat 8, MODIS), weather and extreme events (Daymet, heat/cold waves, and U.S. drought monitor maps), as well as soil and terrain features, making it suitable for various agricultural monitoring tasks. It integrates crop and climate related tasks within a single, cohesive dataset. In detail, the following data sources are provided: †The drought indices have been added to the original dataset from a master's thesis. Additional information can be found in the repository. Uses The dataset allows various tasks, including yield prediction, phenology mapping, crop condition forecasting, extreme weather event detecti…
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