Machine Learning Methods for Predicting <i>Argania spinosa</i> Crop Yield and Leaf Area Index: A Combined Drought Index Approach from Multisource Remote Sensing Data

In this study, we explored the efficacy of random forest algorithms in downscaling CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) precipitation data to predict Argane stand traits. Nonparametric regression integrated original CHIRPS data with environmental variables, demonst...

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Hlavní autoři:	Mohamed Mouafik, Mounir Fouad, Ahmed El Aboudi
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-07-01
Edice:	AgriEngineering
Témata:	<i>Argania spinosa</i> (L.) Skeels crop yield prediction leaf area index spatial downscaling drought machine learning
On-line přístup:	https://www.mdpi.com/2624-7402/6/3/134
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