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AI-based evaluation of the SDGs: the case of crop detection with earth observation data

Abstract:
The framework of the seventeen sustainable development goals is a challenge for developers and researchers applying artificial intelligence (AI). AI and earth observations (EO) can provide reliable and disaggregated data for better monitoring of the sustainable development goals (SDGs). In this paper, we present an overview of SDG targets, which can be effectively measured with AI tools. We identify indicators with the most significant contribution from the AI and EO and describe an application of state-of-the-art machine learning models to one of the indicators. We describe an application of U-net with SE blocks for efficient segmentation of satellite imagery for crop detection. Finally, we demonstrate how AI can be more effectively applied in solutions directly contributing towards specific SDGs and propose further research on an AI-based evaluative infrastructure for SDGs.
Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
https://openreview.net/forum?id=mXmSjL1d2t0

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Sub department:
Saïd Business School
Role:
Author
ORCID:
0000-0003-4853-9550
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Saïd Business School
Role:
Author
ORCID:
0000-0003-0084-9410


Publisher:
OpenReview
Journal:
Proceedings of the ICLR Conference 2019 More from this journal
Publication date:
2019-06-28
Event title:
7th International Conference on Learning Representations (ICLR 2019)
Event location:
New Orleans, LA, USA
Event website:
https://iclr.cc/Conferences/2019
Event start date:
2019-05-06
Event end date:
2019-05-09


Language:
English
Keywords:
Pubs id:
1033123
Local pid:
pubs:1033123
Deposit date:
2021-04-29

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