How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?

Presented at the Jameel Observatory Community of Practice meeting and drylands food security and resilience early action research and evidence dialogue, Addis Ababa, Ethiopia, 13-16 May 2025

Detalles Bibliográficos
Autor principal: Mlambo, Reason
Formato: Póster
Lenguaje:Inglés
Publicado: Jameel Observatory for Food Security Early Action 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/174665
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author Mlambo, Reason
author_browse Mlambo, Reason
author_facet Mlambo, Reason
author_sort Mlambo, Reason
collection Repository of Agricultural Research Outputs (CGSpace)
description Presented at the Jameel Observatory Community of Practice meeting and drylands food security and resilience early action research and evidence dialogue, Addis Ababa, Ethiopia, 13-16 May 2025
format Poster
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institution CGIAR Consortium
language Inglés
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher Jameel Observatory for Food Security Early Action
publisherStr Jameel Observatory for Food Security Early Action
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spelling CGSpace1746652025-05-21T01:07:34Z How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa? Mlambo, Reason earth observation satellites Presented at the Jameel Observatory Community of Practice meeting and drylands food security and resilience early action research and evidence dialogue, Addis Ababa, Ethiopia, 13-16 May 2025 2025-05 2025-05-20T08:09:15Z 2025-05-20T08:09:15Z Poster https://hdl.handle.net/10568/174665 en Open Access application/pdf Jameel Observatory for Food Security Early Action Mlambo, Reason. 2025. How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?. Poster. Presented at the Jameel Observatory Community of Practice meeting and drylands food security and resilience early action research and evidence dialogue, Addis Ababa, Ethiopia, 13-16 May 2025. Edinburgh: Jameel Observatory for Food Security Early Action
spellingShingle earth observation satellites
Mlambo, Reason
How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title_full How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title_fullStr How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title_full_unstemmed How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title_short How consistent are Earth Observation-based machine learning models for predicting poverty in sub-Saharan Africa?
title_sort how consistent are earth observation based machine learning models for predicting poverty in sub saharan africa
topic earth observation satellites
url https://hdl.handle.net/10568/174665
work_keys_str_mv AT mlamboreason howconsistentareearthobservationbasedmachinelearningmodelsforpredictingpovertyinsubsaharanafrica