A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems

A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems

AbstractThis manuscript aims to develop a new multivariate composite index for monitoring agricultural drought. To achieve this, the AVHRR, VIIRS, CHIRPS data series over a period of 40 years, rainfall and crop yield data as references were used. Variables include parameters for vegetative stress (S...

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Bibliografische gegevens
Hoofdauteurs: Ismaguil Hanadé Houmma, Sébastien Gadal, Loubna El Mansouri, Maman Garba, Paul Gérard Gbetkom, Mansour Badamassi Mamane Barkawi, Rachid Hadria
Formaat: Artikel
Taal:English
Gepubliceerd in: Taylor & Francis Group 2023-12-01
Reeks:Geomatics, Natural Hazards & Risk
Onderwerpen:
Drought
multivariate index
remote sensing
random forest
Sahelian
Online toegang:https://www.tandfonline.com/doi/10.1080/19475705.2023.2223384

Internet

https://www.tandfonline.com/doi/10.1080/19475705.2023.2223384

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