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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Mohamed Mouafik, Mounir Fouad, Ahmed El Aboudi
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2024-07-01
Sarja:	AgriEngineering
Aiheet:	<i>Argania spinosa</i> (L.) Skeels crop yield prediction leaf area index spatial downscaling drought machine learning
Linkit:	https://www.mdpi.com/2624-7402/6/3/134
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