Radiant MLHub

2019 Mali CropType Training Data

satellite

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.

Dataset ID

umd_mali_crop_type

DOI

10.34911/rdnt.tgz68o

Creator

University of Maryland

Contact

cnakalem@umd.edu

Documentation

Citation

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

Python Client example

from radiant_mlhub import Dataset

ds = Dataset.fetch('umd_mali_crop_type')
for c in ds.collections:
    print(c.id)

Python Client quick-start guide

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Source Imagery Collection

Description

2019 Mali CropType Training Data Source Imagery

License

CC-BY-4.0

Collection ID

umd_mali_crop_type_source

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Labels Collection

Description

2019 Mali CropType Training Data Labels

License

CC-BY-4.0

Collection ID

umd_mali_crop_type_labels

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