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Satellite-based Prediction of Forage Conditions for Livestock in Northern Kenya

Domaine:

agriculturegeospatialclimate

Type de record:

datasetpaper
Créateur:
HobSve
Éditeur:
arXiv
Hôte:avatar
This paper introduces the first dataset of satellite images labeled with forage quality by on-the-ground experts and provides proof of concept for applying computer vision methods to index-based drought insurance. We also present the results of a collaborative benchmark tool used to crowdsource an accurate machine learning model on the dataset. Our methods significantly outperform the existing technology for an insurance program in Northern Kenya, suggesting that a computer vision-based approach could substantially benefit pastoralists, whose exposure to droughts is severe and worsening with climate change. Paper presented at the ICLR 2020 Workshop on Computer Vision for Agriculture (CV4A)

Tasks

computer visionimage classification

Tags

Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences

Licenses

arXiv.org perpetual, non-exclusive licensehttp://arxiv.org/licenses/nonexclusive-distrib/1.0/

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