This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program.
|University of Maryland|
Nakalembe, C.L., Ouedraogo, H., Diarra, N., & Kuzimbu, B. (2021). 2019 Mali Crop Type Training Data for Machine Learning (Version 1.0) Radiant MLHub. [Date Accessed] https://doi.org/10.34911/rdnt.tgz68o
from radiant_mlhub import Dataset ds = Dataset.fetch('umd_mali_crop_type') for c in ds.collections: print(c.id)
2019 Mali CropType Training Data Source Imagery
2019 Mali CropType Training Data Labels