Remote sensing in field crop monitoring: A comprehensive review of sensor systems, data analyses and recent advances

E Omia, H Bae, E Park, MS Kim, I Baek, I Kabenge… - Remote Sensing, 2023 - mdpi.com
The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …

UAV-based chlorophyll content estimation by evaluating vegetation index responses under different crop coverages

L Qiao, W Tang, D Gao, R Zhao, L An, M Li… - … and electronics in …, 2022 - Elsevier
Efficiently estimating chlorophyll content is important in monitoring the photosynthesis
capacity and growth status of maize canopy in precision agriculture management …

Assessment of red-edge vegetation indices for crop leaf area index estimation

T Dong, J Liu, J Shang, B Qian, B Ma… - Remote Sensing of …, 2019 - Elsevier
This study explores the potential of vegetation indices (VIs) for crop leaf area index (LAI)
estimation, with a focus on comparing red-edge reflectance based (RE-based) and the …

A cubesat enabled spatio-temporal enhancement method (cestem) utilizing planet, landsat and modis data

R Houborg, MF McCabe - Remote Sensing of Environment, 2018 - Elsevier
Satellite sensing in the visible to near-infrared (VNIR) domain has been the backbone of
land surface monitoring and characterization for more than four decades. However, a …

Vegetation indices combining the red and red-edge spectral information for leaf area index retrieval

Q Xie, J Dash, W Huang, D Peng, Q Qin… - IEEE Journal of …, 2018 - ieeexplore.ieee.org
Leaf area index (LAI) is a crucial biophysical variable for agroecosystems monitoring.
Conventional vegetation indices (VIs) based on red and near infrared regions of the …

[HTML][HTML] Fusion of Sentinel-2 and PlanetScope time-series data into daily 3 m surface reflectance and wheat LAI monitoring

Y Sadeh, X Zhu, D Dunkerley, JP Walker… - International Journal of …, 2021 - Elsevier
Abstract The dynamics of Leaf Area Index (LAI) from space is key to identify crop types and
their phenology over large areas, and to characterize spatial variations within growers' …

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

R Houborg, MF McCabe - ISPRS Journal of Photogrammetry and Remote …, 2018 - Elsevier
With an increasing volume and dimensionality of Earth observation data, enhanced
integration of machine-learning methodologies is needed to effectively analyze and utilize …

Improving the monitoring of crop productivity using spaceborne solar‐induced fluorescence

K Guan, JA Berry, Y Zhang, J Joiner… - Global change …, 2016 - Wiley Online Library
Large‐scale monitoring of crop growth and yield has important value for forecasting food
production and prices and ensuring regional food security. A newly emerging satellite …

Progress and development on biological information of crop phenotype research applied to real-time variable-rate fertilization

Y Shi, Y Zhu, X Wang, X Sun, Y Ding, W Cao, Z Hu - Plant methods, 2020 - Springer
Background Variable-rate fertilization is crucial in the implementation of precision agriculture
and for ensuring reasonable and efficient fertilizer application and nutrient management that …

Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data

T Dong, J Liu, B Qian, L He, J Liu, R Wang… - ISPRS Journal of …, 2020 - Elsevier
The availability of Landsat 8 and Sentinel-2 has led to a steady increase in both temporal
and spatial resolution of satellite data, offering new opportunities for large-scale crop …