[HTML][HTML] Remote sensing monitoring of rice and wheat canopy nitrogen: A review

J Zheng, X Song, G Yang, X Du, X Mei, X Yang - Remote sensing, 2022 - mdpi.com
Nitrogen (N) is one of the most important elements for crop growth and yield formation.
Insufficient or excessive application of N fertilizers can limit crop yield and quality, especially …

Combining vegetation, color, and texture indices with hyperspectral parameters using machine-learning methods to estimate nitrogen concentration in rice stems and …

D Wang, R Li, T Liu, S Liu, C Sun, W Guo - Field crops research, 2023 - Elsevier
Context or problem Nitrogen is one of the important elements of crops, which plays a
decisive role in crop growth and development and the formation of yields. Monitoring of rice …

Improved estimation of leaf chlorophyll content of row crops from canopy reflectance spectra through minimizing canopy structural effects and optimizing off-noon …

D Li, JM Chen, X Zhang, Y Yan, J Zhu, H Zheng… - Remote sensing of …, 2020 - Elsevier
Leaf chlorophyll content (LCC), as an important indicator of photosynthetic capacity and
nitrogen status, has been non-destructively estimated from canopy reflectance spectra in …

Nitrogen monitoring and inversion algorithms of fruit trees based on spectral remote sensing: a deep review

R **, Y Gu, X Zhang, Z Ren - Frontiers in Plant Science, 2024 - frontiersin.org
Nitrogen, as one of the important elements affecting the growth and development of fruit
trees, leads to slowed protein synthesis and reduced photosynthesis, resulting in yellowing …

Improving retrieval of leaf chlorophyll content from Sentinel-2 and Landsat-7/8 imagery by correcting for canopy structural effects

L Wan, Y Ryu, B Dechant, J Lee, Z Zhong… - Remote Sensing of …, 2024 - Elsevier
Accurately estimating leaf chlorophyll content (Chl) at large spatial scales is crucial for
monitoring agricultural production and plant photosynthesis. Sentinel-2 and Landsat-7/8 …

Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model

J Li, NK Wijewardane, Y Ge, Y Shi - Computers and Electronics in …, 2023 - Elsevier
Accurate and robust quantifications of leaf chlorophyll and water contents facilitate a better
understanding of plant water and nutrient needs. Besides simplified spectral indices, other …

[HTML][HTML] Winter wheat nitrogen status estimation using UAV-based RGB imagery and Gaussian processes regression

Y Fu, G Yang, Z Li, X Song, Z Li, X Xu, P Wang… - Remote Sensing, 2020 - mdpi.com
Predicting the crop nitrogen (N) nutrition status is critical for optimizing nitrogen fertilizer
application. The present study examined the ability of multiple image features derived from …

[HTML][HTML] Quantifying leaf chlorophyll concentration of sorghum from hyperspectral data using derivative calculus and machine learning

S Bhadra, V Sagan, M Maimaitijiang… - Remote Sensing, 2020 - mdpi.com
Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor,
physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at …

Nitrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 data

FRS Pereira, JP De Lima, RG Freitas… - … and Electronics in …, 2022 - Elsevier
In agricultural production, nitrogen (N) deficiency reduces yield, while overapplication may
have an unwanted impact on the natural environment and farm finances. Frequent field N …

Estimation of canopy nitrogen content in winter wheat from Sentinel-2 images for operational agricultural monitoring

C Bossung, M Schlerf, M Machwitz - Precision Agriculture, 2022 - Springer
Canopy nitrogen content (CNC, kg/ha) provides crucial information for site-specific crop
fertilization and the usability of Sentinel-2 (S2) satellite data for CNC monitoring at high …