Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …

Upcoming satellite hyperspectral sensors require powerful and robust methodologies for
making optimum use of the rich spectral data. This paper reviews the widely applied coupled …

Unmanned aerial vehicle (UAV)-based remote sensing (RS) possesses the significant
advantage of being able to efficiently collect images for precision agricultural applications …

This paper provides an overview of the recent developments in remote sensing technology
and machine learning algorithms for estimating important biophysical and biochemical …

Visible–near‐infrared spectroscopy is known for its rapid and nondestructive characteristics
designed to predict leaf chlorophyll content (LCC) of winter wheat. It is believed that the …

Leaf area index (LAI) is a key biophysical parameter for monitoring crop growth status,
predicting crop yield, and quantifying crop variability in agronomic applications. Mapping the …

Leaf area index (LAI) is a key input in models describing biosphere processes and has
widely been used in monitoring crop growth and in yield estimation. In this study, a hybrid …

Field spectra acquired from a handheld spectroradiometer and Sentinel-2 images spectra
were used to investigate the applicability of hyperspectral and multispectral data in retrieving …

Using simultaneously collected remote sensing data and field measurements, this study
firstly assessed the consistency and applicability of China high-resolution earth observation …

To improve the accuracy of winter wheat yield estimation, the Crop Environment Resource
Synthesis for Wheat (CERES-Wheat) model with an assimilation strategy was performed by …