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Hand Labelled Crop / Non Crop datasets

Domaine:

agriculturegeospatial

Type de record:

datasetpaper
Créateur:
Tseng, GabrielKerner, HannahNakalembe, CatherineBecker-Reshef, Inbal
Éditeur:
Zenodo
Hôte:avatar

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/nasaharv…

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

Visit

doi.org

Tasks

computer visionimage classification

Tags

agriculturecropscrop classificationfood securityearth observationGISAfrica

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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