A critical review on applications of hyperspectral remote sensing in crop monitoring
H Yu, B Kong, Y Hou, X Xu, T Chen, X Liu - Experimental Agriculture, 2022 - cambridge.org
Numerous technologies have contributed to the recent development of agriculture,
especially the advancement in hyperspectral remote sensing (HRS) constituted a revolution …
especially the advancement in hyperspectral remote sensing (HRS) constituted a revolution …
Hyperspectral reflectance and machine learning to monitor legume biomass and nitrogen accumulation
Hyperspectral remote sensing provides opportunity for a nondestructive tool for estimating
biochemical or biophysical characteristics of agricultural crops. Importantly, among rotational …
biochemical or biophysical characteristics of agricultural crops. Importantly, among rotational …
Using PRISMA Hyperspectral Data for Land Cover Classification with Artificial Intelligence Support
Hyperspectral satellite missions, such as PRISMA of the Italian Space Agency (ASI), have
opened up new research opportunities. Using PRISMA data in land cover classification has …
opened up new research opportunities. Using PRISMA data in land cover classification has …
Special issue “hyperspectral remote sensing of agriculture and vegetation”
The advent of up-to-date hyperspectral technologies, and their increasing performance both
spectrally and spatially, allows for new and exciting studies and practical applications in …
spectrally and spatially, allows for new and exciting studies and practical applications in …
Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment
Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters.
These blooms can be detected using optical radiometers due to the presence of …
These blooms can be detected using optical radiometers due to the presence of …
Application of a hyperspectral imaging system to quantify leaf-scale chlorophyll, nitrogen and chlorophyll fluorescence parameters in grapevine
Z Yang, J Tian, K Feng, X Gong, J Liu - Plant Physiology and Biochemistry, 2021 - Elsevier
Rapidly and accurately monitoring the physiological and biochemical parameters of grape
leaves is the key to controlling the quality of wine grapes. In this study, a Pika L …
leaves is the key to controlling the quality of wine grapes. In this study, a Pika L …
[HTML][HTML] Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth
Hyperspectral measurements can help with rapid decision-making and collecting data
across multiple locations. However, there are multiple data processing methods (Savisky …
across multiple locations. However, there are multiple data processing methods (Savisky …
Improving the estimation of apple leaf photosynthetic pigment content using fractional derivatives and machine learning
As a key functional trait, leaf photosynthetic pigment content (LPPC) plays an important role
in the health status monitoring and yield estimation of apples. Hyperspectral features …
in the health status monitoring and yield estimation of apples. Hyperspectral features …
Quality Characterization of Fava Bean-Fortified Bread Using Hyperspectral Imaging
As the demand for alternative protein sources and nutritional improvement in baked goods
grows, integrating legume-based ingredients, such as fava beans, into wheat flour presents …
grows, integrating legume-based ingredients, such as fava beans, into wheat flour presents …
Utilizing VSWIR spectroscopy for macronutrient and micronutrient profiling in winter wheat
This study explores the use of leaf-level visible-to-shortwave infrared (VSWIR) reflectance
observations and partial least squares regression (PLSR) to predict foliar concentrations of …
observations and partial least squares regression (PLSR) to predict foliar concentrations of …