Integrating multi-source remote sensing data and machine learning for predicting tree density and cover in Argania spinosa

This examination explores the application of remote sensing technologies, including Sеntinеl-2, Mohammed VI satellite imagery and Unmanned Aerial Vehicles (UAVs), to predict the cover and density of Argane forest stands in Morocco. The primary objective was to determine the most dependable dataset f...

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Hauptverfasser:	Mohamed Mouafik, Fouad Mounir, Ahmed El Aboudi
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2025-08-01
Schriftenreihe:	Smart Agricultural Technology
Schlagworte:	Argania spinosa (L.) Skeels Tree density Tree cover Sentinel-2 M6 UAVs
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2772375525001443
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