AgriFieldNet Competition Dataset
This dataset contains crop types of agricultural fields in four states of Uttar Pradesh, Rajasthan, Odisha and Bihar in northern India. There are 13 different classes in the dataset including Fallow land and 12 crop types of Wheat, Mustard, Lentil, Green pea, Sugarcane, Garlic, Maize, Gram, Coriander, Potato, Bersem, and Rice. The dataset is split to train and test collections as part of the AgriFieldNet India Competition. Ground reference data for this dataset is collected by IDinsight’s Data on Demand team. Radiant Earth Foundation carried out the training dataset curation and publication. This training dataset is generated through a grant from the Enabling Crop Analytics at Scale (ECAAS) Initiative funded by The Bill & Melinda Gates Foundation and implemented by Tetra Tech.
Dataset ID | ref_agrifieldnet_competition_v1 |
DOI | 10.34911/rdnt.wu92p1 |
Creator | Radiant Earth Foundation, IDinsight |
Contact | ml@radiant.earth |
Documentation
Tools & Applications
Citation
Radiant Earth Foundation & IDinsight (2022) AgriFieldNet Competition Dataset, Version 1.0, Radiant MLHub. https://doi.org/10.34911/rdnt.wu92p1
Python Client example
from radiant_mlhub import Dataset
ds = Dataset.fetch('ref_agrifieldnet_competition_v1')
for c in ds.collections:
print(c.id)
Download Dataset
Source Imagery Collections
Description | AgriFieldNet Competition Dataset - Source Imagery |
License | CC-BY-4.0 |
Collection ID | ref_agrifieldnet_competition_v1_source |
Download | |
Labels Collections
Description | AgriFieldNet Competition Dataset - Test Labels |
License | CC-BY-4.0 |
Collection ID | ref_agrifieldnet_competition_v1_labels_test |
Download | |
Description | AgriFieldNet Competition Dataset - Train Labels |
License | CC-BY-4.0 |
Collection ID | ref_agrifieldnet_competition_v1_labels_train |
Download | |
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