Hyperspectral imaging: A review on UAV-based sensors, data processing and applications for agriculture and forestry
Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be
useful in many agroforestry applications. However, it lacks the spectral range and precision …
useful in many agroforestry applications. However, it lacks the spectral range and precision …
Quantifying vegetation biophysical variables from imaging spectroscopy data: A review on retrieval methods
An unprecedented spectroscopic data stream will soon become available with forthcoming
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …
Drought monitoring over Yellow River basin from 2003–2019 using reconstructed MODIS land surface temperature in Google Earth Engine
Drought is one of the most complex and least-understood environmental disasters that can
trigger environmental, societal, and economic problems. To accurately assess the drought …
trigger environmental, societal, and economic problems. To accurately assess the drought …
[HTML][HTML] Modeling carbon storage in urban vegetation: Progress, challenges, and opportunities
Urban vegetation (UV) and its carbon storage capacity are critical for terrestrial carbon
cycling and global sustainable development goals (SDGs). With complex spatial distribution …
cycling and global sustainable development goals (SDGs). With complex spatial distribution …
Comparison of leaf chlorophyll content retrieval performance of citrus using FOD and CWT methods with field-based full-spectrum hyperspectral reflectance data
Citrus is one of the most economically valuable fruit trees in the world, for which leaf
chlorophyll content (LCC) serves as a crucial indicator for evaluating its growth and health …
chlorophyll content (LCC) serves as a crucial indicator for evaluating its growth and health …
Identification of plant leaf phosphorus content at different growth stages based on hyperspectral reflectance
A Siedliska, P Baranowski, J Pastuszka-Woźniak… - BMC Plant …, 2021 - Springer
Background Modern agriculture strives to sustainably manage fertilizer for both economic
and environmental reasons. The monitoring of any nutritional (phosphorus, nitrogen …
and environmental reasons. The monitoring of any nutritional (phosphorus, nitrogen …
Improved estimation of winter wheat aboveground biomass using multiscale textures extracted from UAV-based digital images and hyperspectral feature analysis
Rapid and accurate crop aboveground biomass estimation is beneficial for high-throughput
phenotyping and site-specific field management. This study explored the utility of high …
phenotyping and site-specific field management. This study explored the utility of high …
A comparison of hybrid machine learning algorithms for the retrieval of wheat biophysical variables from sentinel-2
D Upreti, W Huang, W Kong, S Pascucci, S Pignatti… - Remote Sensing, 2019 - mdpi.com
This study focuses on the comparison of hybrid methods of estimation of biophysical
variables such as leaf area index (LAI), leaf chlorophyll content (LCC), fraction of absorbed …
variables such as leaf area index (LAI), leaf chlorophyll content (LCC), fraction of absorbed …
Estimation of leaf nitrogen content in wheat using new hyperspectral indices and a random forest regression algorithm
Novel hyperspectral indices, which are the first derivative normalized difference nitrogen
index (FD-NDNI) and the first derivative ratio nitrogen vegetation index (FD-SRNI), were …
index (FD-NDNI) and the first derivative ratio nitrogen vegetation index (FD-SRNI), were …
[HTML][HTML] Newly-developed three-band hyperspectral vegetation index for estimating leaf relative chlorophyll content of mangrove under different severities of pest and …
Hyperspectral imaging-derived vegetation indices (VIs) have rarely been developed to
estimate leaf chlorophyll content of mangrove forests under pest and disease stress …
estimate leaf chlorophyll content of mangrove forests under pest and disease stress …