Machine Learning Optimised Hyperspectral Remote Sensing Retrieves Cotton Nitrogen Status

Machine Learning Optimised Hyperspectral Remote Sensing Retrieves Cotton Nitrogen Status

Hyperspectral imaging spectrometers mounted on unmanned aerial vehicle (UAV) can capture high spatial and spectral resolution to provide cotton crop nitrogen status for precision agriculture. The aim of this research was to explore machine learning use with hyperspectral datacubes over agricultural...

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Bibliographic Details
Main Authors: Ian J. Marang, Patrick Filippi, Tim B. Weaver, Bradley J. Evans, Brett M. Whelan, Thomas F. A. Bishop, Mohammed O. F. Murad, Dhahi Al-Shammari, Guy Roth
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Remote Sensing
Subjects:
remote sensing
hyperspectral
multispectral
machine learning
nitrogen
cotton
Online Access:https://www.mdpi.com/2072-4292/13/8/1428

Internet

https://www.mdpi.com/2072-4292/13/8/1428

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