Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. The triangular greenness index (TGI) was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at (670 nm, R670), (550 nm, R550), and (480 nm, R480), where R is the spectral reflectance at wavelengths of 67...

A methodology is described for the validation of Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data over heterogeneous land surfaces in an agricultural region in Southern Italy. The approach involves the use inverse canopy reflectance modeling techniques to derive maps of canopy chlorophyll content (CCC) and leaf area index (LAI) at fine spatial resolution....

15 16 Here we investigate relationships between NDVI, Biomass, and Leaf Area Index (LAI) for 17 six key plant species near Barrow, Alaska. We explore how key plant species differ in 18 biomass, leaf area index (LAI) and how can v e g e t a t i o n spectral indices be used to 19 estimate biomass and LAI for key plant species. A vegetation index (VI) or a spectral 20 vegetation index (SVI) is a q...

Simulation models of leaf area index (LAI) and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modifi...

Light canopy transmittance and the Beer-Lambert equation were utilized to assess monthly leaf area index (LAI) of a tropical deciduous forest ecosystem on the west coast of Mexico. The light transmittance coefficient (k) was obtained by analyzing vertical leaf and light distribution in the forest canopy. An independent LAI estimate was obtained using litterfall data. The calculated k value was ...

Leaf area index (LAI) is a key variable for modeling energy and mass exchange between the land surface and the atmosphere. Inversion of physically based radiative transfer models is the most established technique for estimating LAI from remotely sensed data. This study aims to evaluate the suitability of the PROSAIL model for LAI estimation of three typical row crops (maize, potato, and sunflow...

Regional scale vegetation monitoring and yield forecasting require the estimation of biophysical parameters, such as Leaf Area Index (LAI), biomass and canopy water content (CWC). The CWC is also targeted for fire risk and drought monitoring. This work presents a methodology for jointly retrieval of Canopy Water Content (CWC) and Leaf Area Index (LAI) from coarse resolution satellite data. The ...

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Different approaches have been used to simulate leaf area index (LAI) in soybean (Glycine max L. Merr). Many of these approaches require genotype-specific calibration procedures. Studies modeling LAI dynamics under optimal growth conditions with yields close to the yield potential of soybean have remained scarce. A sink-driven approach was developed and evaluated for LAI simulation in soybean u...

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle o...