scholarly journals A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

Forests ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
John Iiames ◽  
Ellen Cooter ◽  
Donna Schwede ◽  
Jimmy Williams
Author(s):  
Alexandre Ortega Gonçalves ◽  
Evandro Henrique Figueiredo Moura da Silva ◽  
Letícia Gonçalves Gasparotto ◽  
Juliano Mantelatto Rosa ◽  
Stephanie do Carmo ◽  
...  

Abstract: The objective of this work was to evaluate the use of plant height as a calibration variable for improving indirect measurements of the leaf area index (LAI). Three experiments were conducted with different crops - corn (Zea mays), soybean (Glycine max), and sugarcane (Saccharum officinarum) -, to compare the performance of the LAI measured indirectly (LAIind) and corrected by the calibration variable with the LAI measured directly (LAIref). Without the proposed correction, the LAIind tended to be overestimated by 20%, on average, compared with the LAIref, for the three crops. After crop height was used to adjust the LAIind, a strong positive relationship was observed between the LAIref and the corrected LAIind (R2 = 0.96); overestimation was reduced to 4% and the root-mean-square error decreased to 0.35 m2 m-2. The variable canopy height is promising for the correction of the LAI of the soybean, corn, and sugarcane crops.


2014 ◽  
Vol 151 ◽  
pp. 44-56 ◽  
Author(s):  
Gong Zhang ◽  
Sangram Ganguly ◽  
Ramakrishna R. Nemani ◽  
Michael A. White ◽  
Cristina Milesi ◽  
...  

2014 ◽  
Vol 2 (1) ◽  
pp. 31 ◽  
Author(s):  
Janerson J. Coêlho ◽  
José C.B. Dubeux Jr ◽  
Erick R.S. Santos ◽  
João M.C. Leão Neto ◽  
Márcio V. Da Cunha ◽  
...  

2014 ◽  
Vol 11 (11) ◽  
pp. 16349-16389
Author(s):  
K. D. Maurer ◽  
G. Bohrer ◽  
V. Y. Ivanov

Abstract. Surface roughness parameters are at the core of every model representation of the coupling and interactions between land-surface and atmosphere, and are used in every model of surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and do not vary them in response to spatial or temporal changes to canopy structure. In part, this is due to the difficulty of reducing the complexity of canopy structure and its spatiotemporal dynamic and heterogeneity to less than a handful of parameters describing its effects of atmosphere–surface interactions. In this study we use large-eddy simulations to explore, in silico, the effects of canopy structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but were able to find positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, and between eddy-penetration depth and maximum canopy height and leaf area index. Using a decade of wind and canopy structure observations in a site in Michigan, we tested the effectiveness of our model-resolved parameters in predicting the frictional velocity over heterogeneous and disturbed canopies. We compared it with three other semi-empirical models and with a decade of meteorological observations. We found that parameterizations with fixed representations of roughness performed relatively well. Nonetheless, some empirical approaches that incorporate seasonal and inter-annual changes to the canopy structure performed even better than models with temporally fixed parameters.


Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Yan Gong ◽  
Kaili Yang ◽  
Zhiheng Lin ◽  
Shenghui Fang ◽  
Xianting Wu ◽  
...  

Abstract Background Rice is one of the most important grain crops worldwide. The accurate and dynamic monitoring of Leaf Area Index (LAI) provides important information to evaluate rice growth and production. Methods This study explores a simple method to remotely estimate LAI with Unmanned Aerial Vehicle (UAV) imaging for a variety of rice cultivars throughout the entire growing season. Forty eight different rice cultivars were planted in the study site and field campaigns were conducted once a week. For each campaign, several widely used vegetation indices (VI) were calculated from canopy reflectance obtained by 12-band UAV images, canopy height was derived from UAV RGB images and LAI was destructively measured by plant sampling. Results The results showed the correlation of VI and LAI in rice throughout the entire growing season was weak, and for all tested indices there existed significant hysteresis of VI vs. LAI relationship between rice pre-heading and post-heading stages. The model based on the product of VI and canopy height could reduce such hysteresis and estimate rice LAI of the whole season with estimation errors under 24%, not requiring algorithm re-parameterization for different phenology stages. Conclusions The progressing phenology can affect VI vs. LAI relationship in crops, especially for rice having quite different canopy spectra and structure after its panicle exsertion. Thus the models solely using VI to estimate rice LAI are phenology-specific and have high uncertainties for post-heading stages. The model developed in this study combines both remotely sensed canopy height and VI information, considerably improving rice LAI estimation at both pre- and post-heading stages. This method can be easily and efficiently implemented in UAV platforms for various rice cultivars during the entire growing season with no rice phenology and cultivar pre-knowledge, which has great potential for assisting rice breeding and field management studies at a large scale.


2015 ◽  
Vol 12 (8) ◽  
pp. 2533-2548 ◽  
Author(s):  
K. D. Maurer ◽  
G. Bohrer ◽  
W. T. Kenny ◽  
V. Y. Ivanov

Abstract. Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.


Sign in / Sign up

Export Citation Format

Share Document