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Hand Labelled Crop / Non Crop datasets

Research datakeyboard_double_arrow_right Dataset 12 Apr 2021Publisher:Zenodo

Authors: Tseng, Gabriel; Kerner, Hannah; Nakalembe, Catherine; Becker-Reshef, Inbal;

doi: 10.5281/zenodo.4680394 , 10.5281/zenodo.4680393

Hand Labelled Crop / Non Crop datasets

- Summary
- Subjects
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Abstract

This dataset provides the hand-labelled crop / non-crop points used for training, which were created by labelling high-resolution satellite imagery in QGIS and Google Earth Pro. Data is available for Ethiopia, Sudan, Togo and Kenya. Code used to process these points is available in the following github repository: https://github.com/nasaharvest/crop-maml For more information, or if you use any part of this dataset, please refer to / cite the following paper: Gabriel Tseng, Hannah Kerner, Catherine Nakalembe and Inbal Becker-Reshef. 2021. Learning to predict crop type from heterogeneous sparse labels using meta-learning. GeoVision Workshop at CVPR ’21: June 19th, 2021

Related Organizations

University of Maryland, College Park
United States

Keywords

Africa, crop classification, food security, earth observation, crops, GIS, agriculture

Impact byBIP!

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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average