Optical-based remote sensing offers great potential for phenotyping vegetation traits and
functions for a range of applications including vegetation monitoring and assessment. A key …

Leaf chlorophyll content (LCC) is an important indicator of foliar nitrogen status and
photosynthetic capacity. Compared to physical models, the generality of empirical models …

Context Leaf area index (LAI) is a vital indicator to identify the crop growth condition and to
infer crop yield and water consumption. The generality of empirical models for estimating LAI …

Understanding how biophysical and biochemical variables contribute to the spectral
characteristics of vegetation canopies is critical for their monitoring. Quantifying these …

For crop growth monitoring and agricultural management, it is important to use hyperspectral
remote sensing techniques to estimate canopy nitrogen content in a timely and accurate …

The widely used SAIL (Scattering by Arbitrarily Inclined Leaves) radiative transfer model
(RTM) is designed for canopies that can be considered as homogeneous turbid media and …

Separation of soil effects from top-of-canopy (TOC) reflectance is crucial for quantitative
remote sensing of vegetation. Soil affects TOC reflectance via the soil-vegetation interaction …

氮素是水稻生长发育的重要元素之一, 精准估测氮素浓度对指导水稻精准施肥,
辅助氮高效品种选育是十分重要的. 传统田间采样方式难以实时获取水稻氮素浓度 …

As the invasion of alien species intensifies, the native salt marsh vegetation, especially the
ecosystem of Suaeda salsa (S. salsa), in Chinese coastal wetlands has been severely …

The photochemical reflectance index (PRI) is a promising remote sensing signal for
monitoring vegetation physiology. Variations in leaf PRI are usually attributed to either the …