Leaf pigments are sensitive to various stress conditions and senescent stages. Variation in the ratio of chlorophyll carotenoid content provides valuable insights into understanding physiological phenological status plants deciduous forests. While use spectral indices assess this has been attempted previously, almost all were derived indirectly from those developed for contents. Furthermore, there little focus on seasonal dynamics ratio, which is a good proxy leaf senescence, resulting only...

Chlorophyll a fluorescence (ChlFa) parameters provide insight into the physiological and biochemical processes of plants have been widely applied to monitor evaluate photochemical process photosynthetic capacity in variety environments. Recent advances remote sensing new opportunities for detection ChlFa at large scales but demand further tremendous efforts. Among such efforts, application hyperspectral index is always possible, performance indices detecting under varying light conditions...

Leaf area index (LAI) is an important structural parameter that controls energy, water, and gas exchanges of plant ecosystems. At present, remote sensing techniques, especially passive optical sensing, are the most widely used approaches to estimate LAI. However, prevalent usage spectral information alone often saturates, which a major issue for retrieving LAI in particular forests. In this study, our goal was improve estimation using Sentinel-2 data by combining both texture minimize...

Hyperspectral spectroscopy based on partial least squares regression (PLSR) is an effective tool for monitoring plant photosynthesis. Despite their wide applications, the robustness of PLSR models tracing photosynthetic capacity, which varies considerably among different species and at times, have been far less explored, leading to doubt about whether hyperspectral information can accurately predict capacity across temporal changes. Ordinary applications generally make use original or...

Timely acquisition of forest structure is crucial for understanding the dynamics ecosystem functions. Despite fact that combination different quantitative models (QSMs) and point cloud sources (ALS DAP) has shown great potential to characterize tree structure, few studies have addressed their pros cons in alpine temperate deciduous forests. In this study, clouds from UAV-mounted LiDAR DAP under leaf-off conditions were first processed into individual clouds, then explicit 3D reconstructed...

Changes in leaf physiological trait indicators and shifts their relationships are expected to reveal plant ecological strategies during succession, how they interact with the changing environment thought be useful forest restoration management. In this study, 9 indicators, 7 structural chemical of each dominant species across a successional series were measured southern China; 14 environmental factors also identify which most associated indicators. Results showed that photosynthesis (Amass...

A clear understanding of the dynamics photosynthetic capacity is crucial for accurate modeling ecosystem carbon uptake. However, such dynamical information hardly available and has dramatically impeded our cycles. Although tremendous efforts have been made in coupling dynamic into models, using “proxies” rooted from close relationships between other leaf parameters remains popular selection. Unfortunately, no consensus yet reached on “proxies”, leading them only applicable to limited cases....

Leaf-level hyperspectral-based species identification has a long research history. However, unlike hyperspectral image-based classification models, convolutional neural network (CNN) models are rarely used for the one-dimensional (1D) structured leaf-level spectrum. Our focuses on data from five laboratories worldwide to test general use of effective CNN model by reshaping 1D structure into two-dimensional greyscale images without principal component analysis (PCA) or downscaling. We...

Nitrogen is a major nutrient regulating the physiological processes of plants. Although various partial least squares regression (PLSR) models have been proposed to estimate leaf nitrogen content (LNC) from hyperspectral data with good accuracies, they are unfortunately not robust and often applicable novel datasets beyond which were developed. Selecting informative bands has reported be critical refining performance PLSR model improving its robustness for general applications. However, no...

The leaf area index (LAI) is a critical structural variable related to variety of biophysical processes vegetation, and its efficient accurate estimation importance understanding ecosystem dynamics. Despite many direct indirect methods being well developed, in the more recent unmanned aerial vehicle (UAV)-based RGB data have emerged be promising alternative source for LAI due their low-cost, considerable flexibility, useful applicability. In this study, we investigated feasibility using...

Abstract Unveiling informative chlorophyll a fluorescence (ChlF) parameters and leaf morphological/biochemical traits under varying light conditions is important in ecological studies but has less been investigated. In this study, the trait‐ChlF relationship regressive estimation of ChlF from were investigated using dataset synchronous measurements Mangifera indica L. The results showed that relationships between varied across intensities, as indicated by different slopes intercepts,...

Accurate knowledge of photosynthetic capacity is critical for understanding the carbon cycle under climate change. Despite fact that deep neural network (DNN) models are increasingly applied across a wide range fields, there very few attempts to predict leaf (indicated by maximum carboxylation rate, Vcmax, and electron transport Jmax) from reflected information. In this study, we have built DNN model uses spectra, alone or together with other traits, reliable estimation capacity, accounting...

Detailed three-dimensional (3D) radiative transfer models (RTMs) enable a clear understanding of the interactions between light, biochemistry, and canopy structure, but they are rarely explicitly evaluated due to availability 3D structure data, leading lack knowledge on how structure/leaf characteristics affect processes within forest ecosystems. In this study, newly released RTM Eradiate was extensively based both virtual scenes reconstructed using quantitative model (QSM) by adding leaves...