Search results for "leaf area"
showing 10 items of 124 documents
A prediction model for field drying of hay using a heat balance method
1993
Abstract A hay drying model with a multi-layer representation has been developed. This model, based on a heat balance method, was designed to compute hay drying dynamics in the field. It was implemented for hay spread over a field or in windrows. The necessary inputs are: (1) meteorological data (temperature, humidity, wind speed, solar and atmospheric radiation); (2) biological characteristics of the plant; (3) hay physical parameters (depth, leaf area index). The output provides time-dependent cumulative water losses and changes in water content and temperature in the different layers. The model was tested against data measured under experimental conditions with different kinds of grass (…
Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertai…
2013
products (R 2 >0.74), with typical deviations of<0.5 for nonforest and<1.0 for forest biomes. JRC-TIP, the only effective LAI product, is about half the values of the other LAI products. The average uncertainties and relative uncertainties are in the following order: MODIS (0.17, 11.5%)<GEOV1 (0.24, 26.6%)<Land-SAF (0.36, 37.8%) <JRC-TIP (0.43, 114.3%). The highest relative uncertainties usually appear in ecological transition zones. More than 75% of MODIS, GEOV1, JRC-TIP, and Land-SAF pixels are within the absolute uncertainty requirements (� 0.5) set by the Global Climate Observing System (GCOS), whereas more than 78.5% of MODIS and 44.6% of GEOV1 pixels are within the threshold for relat…
Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning
2009
In recent years, LIDAR (light detection and ranging) sensors have been widely used to measure environmental parameters such as the structural characteristics of trees, crops and forests. Knowledge of the structural characteristics of plants has a high scientific value due to their influence in many biophysical processes including, photosynthesis, growth, CO2-sequestration and evapotranspiration, playing a key role in the exchange of matter and energy between plants and the atmosphere, and affecting terrestrial, above-ground, carbon storage. In this work, we report the use of a 2D LIDAR scanner in agriculture to obtain three-dimensional (3D) structural characteristics of plants. LIDAR allows…
Hyperspectral response of agronomic variables to background optical variability: Results of a numerical experiment
2022
Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-type, and non-photosynthetic vegetation (NPV). This study focused on exploring the spectral response of two important agronomic variables (1) leaf chlorophyll content (Cab ) and (2) leaf area index (LAI) under various canopy backgrounds through a global sensitivity analysis of wheat-like canopy spectra simulated using the physically-based PROSAIL …
Global Scale IB AMSR2 Vegetation Optical Depth at X-Band
2021
Vegetation Optical Depth (VOD) plays an increasingly important role in studying global carbon, water and energy transformation [1], [2]. This study explores the performance of the X-MEB (X-band microwave emission of the biosphere) model at global scale. Similar to the L-MEB model, the X-MEB model, built by INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement) Bordeaux, aims to retrieve VOD (referred to as IB X-VOD) at X-band. To avoid the ill-posed problem caused by retrieving two parameters of interest (soil moisture (SM) and VOD) from mono-angular and dual-polarized observations (AMSR2), which are strongly correlated, we used the ERA5 SM product as a…
Vegetation growth parameters and leaf temperature: Experimental results from a six plots green roofs' system
2016
Abstract The paper provides a contribution for populating database of three physical parameters needed to model energy performance of buildings with green roofs: “coverage ratio” ( σ f ), leaf area index (LAI) and leaf temperature ( T f ). On purpose, six plant species were investigated experimentally: Phyla nordiflora, Aptenia lancifolia , Mesembryanthenum barbatus , Gazania nivea, Gazania uniflora , and Sedum . Proper ranges of the cited parameters have been found for each species. The here indicated ranges of σ f values refer to different growth levels of the species in the same lapse of time, that is four months. Single measured LAI values are also reported for the same plants. As for t…
Observations and snow model simulations of winter energy balance terms within and between different coniferous forests in Southern Boreal Finland
2015
Variation of canopy properties between different forest types is seldom taken into account in hydrological and climate models, and consideration of variation inside a forest is normally omitted. In this work, three data sets on near surface energy balance terms (incoming shortwave and longwave radiation; air and snow–soil interface temperatures) were collected in the southern boreal coniferous zone in Finland during three winters below different types of forest canopies. The aim was to evaluate the ability of a snow mass and energy balance model with a canopy module to reproduce the observed differences in below-canopy incoming radiations and snow–soil interface temperature. Clear differenc…
Quantifying the Robustness of Vegetation Indices through Global Sensitivity Analysis of Homogeneous and Forest Leaf-Canopy Radiative Transfer Models
2019
Vegetation indices (VIs) are widely used in optical remote sensing to estimate biophysical variables of vegetated surfaces. With the advent of spectroscopy technology, spectral bands can be combined in numerous ways to extract the desired information. This resulted in a plethora of proposed indices, designed for a diversity of applications and research purposes. However, it is not always clear whether they are sensitive to the variable of interest while at the same time, responding insensitive to confounding factors. Hence, to be able to quantify the robustness of VIs, a systematic evaluation is needed, thereby introducing a widest possible variety of biochemical and structural heterogeneit…
Evaluating the predictive power of sun-induced chlorophyll fluorescence to estimate net photosynthesis of vegetation canopies: A SCOPE modeling study
2016
Abstract Progress in imaging spectroscopy technology and data processing can enable derivation of the complete sun-induced chlorophyll fluorescence (SIF) emission spectrum. This opens up opportunities to fully exploit the use of the SIF spectrum as an indicator of photosynthetic activity. Simulations performed with the coupled fluorescence–photosynthesis model SCOPE were used to determine how strongly canopy-leaving SIF can be related to net photosynthesis of the canopy (NPC) for various canopy configurations. Regression analysis between SIF retrievals and NPC values produced the following general findings: (1) individual SIF bands that were most sensitive to NPC were located around the fir…
Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor
2021
ESA’s Eighth Earth Explorer mission “FLuorescence EXplorer” (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX’s preparatory activities, this paper presents a first validation exercise of OLCI vegetation products against in situ data coming from the 2018 FLEXSense cam…