Journal article
Deep learning for vegetation health forecasting: A case study in Kenya
- Abstract:
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East Africa has experienced a number of devastating droughts in recent decades, including the 2010/2011 drought. The National Drought Management Authority in Kenya relies on real-time information from MODIS satellites to monitor and respond to emerging drought conditions in the arid and semi-arid lands of Kenya. Providing accurate and timely information on vegetation conditions and health—and its probable near-term future evolution—is essential for minimising the risk of drought...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, 5.0MB, Terms of use)
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- Publisher copy:
- 10.3390/rs14030698
Authors
Bibliographic Details
- Publisher:
- MDPI
- Journal:
- Remote Sensing More from this journal
- Volume:
- 14
- Issue:
- 3
- Article number:
- 698
- Publication date:
- 2022-02-02
- Acceptance date:
- 2022-01-25
- DOI:
- EISSN:
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2072-4292
Item Description
- Language:
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English
- Keywords:
- Pubs id:
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1240344
- Local pid:
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pubs:1240344
- Deposit date:
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2022-05-23
Terms of use
- Copyright holder:
- Lees et al.
- Copyright date:
- 2022
- Rights statement:
- Copyright © 2022 The Author(s). This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
- Licence:
- CC Attribution (CC BY)
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