Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data

Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data

The pre-harvest estimation of seed composition from standing crops is imperative for field management practices and plant phenotyping. This paper presents for the first time the potential of Unmanned Aerial Vehicles (UAV)-based high-resolution hyperspectral and LiDAR data acquired from in-season sta...

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Bibliographic Details
Main Authors: Kamila Dilmurat, Vasit Sagan, Maitiniyazi Maimaitijiang, Stephen Moose, Felix B. Fritschi
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Remote Sensing
Subjects:
seed composition
UAV
hyperspectral
LiDAR
data fusion
AutoML
Online Access:https://www.mdpi.com/2072-4292/14/19/4786

Internet

https://www.mdpi.com/2072-4292/14/19/4786

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