Estimation of vegetation indices for high-throughput phenotyping of wheat using aerial imaging.pdf


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2024-03-29
ation veget cost aerial RG mult ispectral image index MSI
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Khan et al. Plant Methods (2018) 14:20
https://doi.org/10.1186/s13007-018-0287-6
METHODOLOGY
Estimation of vegetation indices
for high-throughput phenotyping of wheat
using aerial imaging
Zohaib Khan1* , Vahid Rahimi‑Eichi2, Stephan Haefele2, Trevor Garnett2 and Stanley J. Miklavcic1
Abstract
Background: Unmanned aerial vehicles offer the opportunity for precision agriculture to efficiently monitor agri‑
cultural land. A vegetation index (VI) derived from an aerially observed multispectral image (MSI) can quantify crop
health, moisture and nutrient content. However, due to the high cost of multispectral sensors, alternate, low‑cost
solutions have lately received great interest. We present a novel method for model‑based estimation of a VI using
RGB color images. The non‑linear spatio‑spectral relationship between the RGB image of vegetation and the index
computed by its corresponding MSI is learned through deep neural networks. The learned models can be used to
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ation/veget/cost/aerial/RG/mult/ispectral/image/index/MSI/ ation/veget/cost/aerial/RG/mult/ispectral/image/index/MSI/
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