Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images

Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images

Monitoring the aboveground biomass (AGB) of maize is essential for improving site-specific nutrient management and predicting yield to ensure food safety. A low-altitude unmanned aerial vehicle (UAV) was employed to acquire hyperspectral imagery of the maize canopy at three growth stages (V6, R1, R3...

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Bibliographic Details
Main Authors: Cheng, X. (Author), Feng, G. (Author), Gao, Q. (Author), Wang, Y. (Author), Xia, C. (Author), Zhang, X. (Author), Zhang, Y. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Above ground biomass
aboveground biomass
Aboveground biomass
Antennas
Biomass
China
Crop height
Crops
Decision trees
'Dry' [
Ecology
estimation method
Forecasting
Forestry
Growth stages
image analysis
Image enhancement
Jilin
NDVI
Precision agriculture
Precision Agriculture
Random forest regression
Regression analysis
Remote sensing
satellite imagery
soil-vegetation interaction
Spectroscopy
Stepwise regression
surface reflectance
UAV-remote sensing
Unmanned aerial vehicle-remote sensing
Unmanned aerial vehicles (UAV)
unmanned vehicle
Vegetation
Vegetation index
Xgboost regression
XGBoost regression
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