Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt

Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt

Monitoring strategic agricultural crops in terms of crop growth performance, by accurate cost-effective and quick tools is crucially important in site-specific management to avoid crop reductions. The availability of commercial high resolution satellite images with high resolution (spatial and spect...

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Bibliographic Details
Main Authors: Adel H. Elmetwalli, Yasser S. A. Mazrou, Andrew N. Tyler, Peter D. Hunter, Osama Elsherbiny, Zaher Mundher Yaseen, Salah Elsayed
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Agriculture
Subjects:
artificial neural network
QuickBird
random forest
satellite images
salinity
spectral indices
Online Access:https://www.mdpi.com/2077-0472/12/3/332

Internet

https://www.mdpi.com/2077-0472/12/3/332

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