Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes
Tipo:
Título:
Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes
Creador/a:
Chipindu, L.;
Mupangwa, W.;
Nyagumbo, I.;
Zaman-Allah, M.
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Mupangwa, W.;
Nyagumbo, I.;
Zaman-Allah, M.
Zaman-Allah, M.
https://orcid.org/0000-0002-8120-5125
Scopus ID
Researcher ID
Mendeley
Items in this Repository
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Año:
2023
Copyright:
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Revista:
Geoscience Data Journal
Volumen de la Revista:
In press
DOI:
Lugar de publicación:
USA
Editor:
John Wiley & Sons Inc.
Cita:
Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes. 2023. In press DOI: 10.1002/gdj3.228 John Wiley & Sons Inc..
Iniciativas del CGIAR
Iniciativa:
Agroecology
Mixed Farming Systems
Mixed Farming Systems
Área de impacto:
Climate adaptation & mitigation
Área de acción:
Resilient Agrifood Systems
Donante o financiador:
United States Agency for International Development (USAID)
URL en CGSpace: