Showing papers on "Leaf area index published in 2011"

Remote Sensing Leaf Chlorophyll Content Using a Visible Band Index

Abstract: Leaf chlorophyll content (μg cm⁻²) is an important variable for agricultural remote sensing because of its close relationship to leaf N content. The objectives of this study were to develop and test a new index, based on red, green and blue bands, that is sensitive to differences in leaf chlorophyll content at leaf and canopy scales. We propose the triangular greenness index (TGI), which calculates the area of a triangle with vertices: (λr, Rr), (λg, Rg), and (λb, Rb), where λ is the wavelength (nm) and R is the reflectance for bands in red (r), green (g), and blue (b) wavelengths. The TGI was correlated with chlorophyll content using a variety of leaf and plot reflectance data. Generally, indices using the chlorophyll red-edge (710–730 nm) had higher correlations with chlorophyll content compared to TGI. However, correlations between TGI and chlorophyll content were equal to or higher than broad-band indices, when leaf area index (LAI) was >2. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, LAI, and soil type at low LAI, whereas at high LAI, TGI was only affected by leaf chlorophyll content. The TGI could be used with low-cost sensors, such as commercially-available digital cameras, for N management by remote sensing.

The role of canopy structural complexity in wood net primary production of a maturing northern deciduous forest

Abstract: The even-aged northern hardwood forests of the Upper Great Lakes Region are undergoing an ecological transition during which structural and biotic complexity is increasing. Early-successional aspen (Populus spp.) and birch (Betula papyrifera) are senescing at an accelerating rate and are being replaced by middle-successional species including northern red oak (Quercus rubra), red maple (Acer rubrum), and white pine (Pinus strobus). Canopy structural complexity may increase due to forest age, canopy disturbances, and changing species diversity. More structurally complex canopies may enhance carbon (C) sequestration in old forests. We hypothesize that these biotic and structural alterations will result in increased structural complexity of the maturing canopy with implications for forest C uptake. At the University of Michigan Biological Station (UMBS), we combined a decade of observations of net primary productivity (NPP), leaf area index (LAI), site index, canopy tree-species diversity, and stand age with canopy structure measurements made with portable canopy lidar (PCL) in 30 forested plots. We then evaluated the relative impact of stand characteristics on productivity through succession using data collected over a nine-year period. We found that effects of canopy structural complexity on wood NPP (NPPW) were similar in magnitude to the effects of total leaf area and site quality. Furthermore, our results suggest that the effect of stand age on NPPW is mediated primarily through its effect on canopy structural complexity. Stand-level diversity of canopy-tree species was not significantly related to either canopy structure or NPPW. We conclude that increasing canopy structural complexity provides a mechanism for the potential maintenance of productivity in aging forests.

Mapping grassland leaf area index with airborne hyperspectral imagery : a comparison study of statistical approaches and inversion of radiative transfer models

Abstract: Statistical and physical models have seldom been compared in studying grasslands. In this paper, both modeling approaches are investigated for mapping leaf area index (LAI) in a Mediterranean grassland (Majella National Park, Italy) using HyMap airborne hyperspectral images. We compared inversion of the PROSAIL radiative transfer model with narrow band vegetation indices (NDVI-like and SAVI2-like) and partial least squares regression (PLS). To assess the performance of the investigated models, the normalized RMSE (nRMSE) and R2 between in situ measurements of leaf area index and estimated parameter values are reported. The results of the study demonstrate that LAI can be estimated through PROSAIL inversion with accuracies comparable to those of statistical approaches (R2 = 0.89, nRMSE = 0.22). The accuracy of the radiative transfer model inversion was further increased by using only a spectral subset of the data (R2 = 0.91, nRMSE = 0.18). For the feature selection wavebands not well simulated by PROSAIL were sequentially discarded until all bands fulfilled the imposed accuracy requirements.

Integration of MODIS LAI and vegetation index products with the CSM-CERES-Maize model for corn yield estimation

Abstract: Advanced information on crop yield is important for crop management and food policy making. A data assimilation approach was developed to integrate remotely sensed data with a crop growth model for crop yield estimation. The objective was to model the crop yield when the input data for the crop growth model are inadequate, and to make the yield forecast in the middle of the growing season. The Cropping System Model (CSM)-Crop Environment Resource Synthesis (CERES)-Maize and the Markov Chain canopy Reflectance Model (MCRM) were coupled in the data assimilation process. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and vegetation index products were assimilated into the coupled model to estimate corn yield in Indiana, USA. Five different assimilation schemes were tested to study the effect of using different control variables: independent usage of LAI, normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), and synergic usage of LAI and EVI or NDVI. Parameters of the CSM-CERES-Maize model were initiated with the remotely sensed data to estimate corn yield for each county of Indiana. Our results showed that the estimated corn yield agreed very well with the US Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) data. Among different scenarios, the best results were obtained when both MODIS vegetation index and LAI products were assimilated and the relative deviations from the NASS data were less than 3.5%. Including only LAI in the model performed moderately well with a relative difference of 8.6%. The results from using only EVI or NDVI were unacceptable, as the deviations were as high as 21% and -13% for the EVI and NDVI schemes, respectively. Our study showed that corn yield at harvest could be successfully predicted using only a partial year of remotely sensed data.

Ultrasonic and LIDAR Sensors for Electronic Canopy Characterization in Vineyards: Advances to Improve Pesticide Application Methods

Abstract: Canopy characterization is a key factor to improve pesticide application methods in tree crops and vineyards. Development of quick, easy and efficient methods to determine the fundamental parameters used to characterize canopy structure is thus an important need. In this research the use of ultrasonic and LIDAR sensors have been compared with the traditional manual and destructive canopy measurement procedure. For both methods the values of key parameters such as crop height, crop width, crop volume or leaf area have been compared. Obtained results indicate that an ultrasonic sensor is an appropriate tool to determine the average canopy characteristics, while a LIDAR sensor provides more accuracy and detailed information about the canopy. Good correlations have been obtained between crop volume (CVU) values measured with ultrasonic sensors and leaf area index, LAI (R2 = 0.51). A good correlation has also been obtained between the canopy volume measured with ultrasonic and LIDAR sensors (R2 = 0.52). Laser measurements of crop height (CHL) allow one to accurately predict the canopy volume. The proposed new technologies seems very appropriate as complementary tools to improve the efficiency of pesticide applications, although further improvements are still needed.

Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

Abstract: In this study we examined ecosystem respiration (R-ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R-ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R-ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R-ECO. The maximum seasonal leaf area index (LAI(MAX)) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T-ref=15 degrees C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P 70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.

Silicon application and drought tolerance mechanism of sorghum

Abstract: Pot experiments were conducted at the PMAS, Arid Agriculture University, Rawalpindi, Pakistan during 2007 repeated during 2008 to study the effect of silicon and nanoirrigation (W40) on drought tolerance mechanism of sorghum. According to experimental design, the silicon fertilization was divided into two levels: control (no application of potassium silicate) Si0 and application of silicon Si200 (200 mlL-1 of potassium silicate per kg of soil). Irrigation was divided into two levels: crop upper limit (40 mm) irrigation denoted as W40 and without irrigation, crop lower limit as Wo. Each treatment was replicated three times with two sorghum cultivars: PARC SS-2 (drought tolerant) and Johar-1(drought susceptible). The results showed that increase in silicon leads to increase in leaf area index (LAI), specific leaf weight (SLW), chlorophyll content (SPAD), leaf dry weight (LDW), shoot dry weight (SDW), root dry weight (RDW), total dry weight (TDW) and remarkably decrease in leaf water potential and shoot to root ratio in sorghum cultivars compared to control treatment. When silicon concentration is applied with irrigation LAI, SPAD, LDW, SDW, RDW, TDW, net assimilation rate (NAR), relative growth rate (RGR), leaf area ratio (LAR) and water use efficiency (WUE) increased by 30, 31, 40, 30, 28, 30, 27, 35, 32, 30 and 36% respectively as compared to water deficient treatment. These results suggest that silicon application may be useful to improve the drought tolerance of sorghum through the enhancement of water uptake ability. Key words: Drought, leaf water potential, leaf area ratio, net assimilation rate, relative growth rate, nano-irrigation.

Effects on rice plant morphology and physiology of water and associated management practices of the system of rice intensification and their implications for crop performance

Abstract: Field experiments were conducted in Bhubaneswar, Orissa, India, during the dry season (January–May) in 2008 and 2009 to investigate whether practices of the System of Rice Intensification (SRI), including alternate wetting and drying (AWD) during the vegetative stage of plant growth, could improve rice plants’ morphology and physiology and what would be their impact on resulting crop performance, compared with currently recommended scientific management practices (SMP), including continuous flooding (CF) of paddies. With SRI practices, grain yield was increased by 48% in these trials at the same time, there was an average water saving of 22% compared with inundated SMP rice. Water productivity with AWD-SRI management practices was almost doubled (0.68 g l−1) compared to CF-SMP (0.36 g l−1). Significant improvements were observed in the morphology of SRI plants in terms of root growth, plant/culm height, tiller number per hill, tiller perimeter, leaf size and number, leaf area index (LAI), specific leaf weight (SLW), and open canopy structure. These phenotypic improvements of the AWD-SRI crop were accompanied by physiological changes: greater xylem exudation rate, crop growth rate, mean leaf elongation rate (LER), and higher light interception by the canopy compared to rice plants grown under CF-SMP. SRI plants showed delayed leaf senescence and greater light utilization, and they maintained higher photosynthetic rates during reproductive and grain-filling stages. This was responsible for improvement in yield-contributing characteristics and higher grain yield than from flooded rice with SMP. We conclude that SRI practices with AWD improve rice plants’ morphology, and this benefits physiological processes that result in higher grain yield and water productivity.

Ecohydrologic impact of reduced stomatal conductance in forests exposed to elevated CO2

Abstract: Plants influence ecosystem water balance through their physiological, phenological, and biophysical responses to environmental conditions, and their sensitivity to climate change could alter the ecohydrology of future forests. Here we use a combination of measurements, synthesis of existing literature, and modelling to address the consequences of climate change on ecohydrologic processes in forests, especially response to elevated CO2 (eCO2). Data assessed from five free-air CO2 enrichment (FACE) sites reveal that eCO2-reduced stomatal conductance led to declines in canopy transpiration and stand water use in three closed-canopy forest sites. The other two sites were in the early stages of stand development, where a strong eCO2-stimulation of canopy leaf area led to enhanced stand water use. In the sweetgum FACE experiment in Oak Ridge, Tennessee (USA), eCO2 reduced seasonal transpiration by 10–16%. Intra-annual peak measured fluxes in transpiration ranged from 4·0–5·5 mm day−1, depending on year. The Biome-BGC model simulated similar rates of transpiration at this site, including the relative reductions in response to eCO2. As a result, simulations predict ∼75 mm average annual increase in potential water yield in response to eCO2. The direct effect of eCO2 on forest water balance through reductions in transpiration could be considerable, especially following canopy closure and development of maximal leaf area index. Complementary, indirect effects of eCO2 include potential increases in root or leaf litter and soil organic matter, shifts in root distribution, and altered patterns of water extraction. Copyright © 2010 John Wiley & Sons, Ltd.

A global reanalysis of vegetation phenology

Abstract: [1] Simulations of the global water and carbon cycle are sensitive to the model representation of vegetation phenology. Current phenology models are empirical, and few predict both phenological timing and leaf state. Our previous study demonstrated how satellite data assimilation employing an Ensemble Kalman Filter yields realistic phenological model parameters for several ecosystem types. In this study the data assimilation framework is extended to global scales using a subgrid-scale representation of plant functional types (PFTs) and elevation classes. A reanalysis of vegetation phenology for 256 globally distributed regions is performed using 10 years of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of photosynthetically active radiation (FPAR) absorbed by vegetation and leaf area index (LAI) data. The 9 · 108 quality screened observations (corresponding to <1% of the globally available MODIS data) successfully constrain a posterior PFT-dependent phenological parameter set. It reduces the global FPAR and LAI prediction error to 20.6% and 14.8%, respectively, compared to the prior prediction error. A 50 year long (1960–2009) daily 1° × 1° global phenology data set with a mean FPAR and LAI prediction error of 0.065 (−) and 0.34 (m2 m−2) is generated. Temperate phenology is best explained by a combination of light and temperature. Tropical evergreen phenology is found to be largely insensitive to moisture and light variations. Boreal phenology can be accurately predicted from local to global scales, while temperate and mediterranean landscapes might benefit from a better subgrid-scale PFT classification or from a more complex canopy radiative transfer model.

Influence of four major plant traits on average height, leaf-area cover, net primary productivity, and biomass density in single-species forests: a theoretical investigation

Abstract: Numerous plant traits are known to influence aspects of individual performance, including rates of carbon uptake, tissue turnover, mortality and fecundity. These traits are bound to influence emerg ...

Retrieving crown leaf area index from an individual tree using ground-based lidar data

Abstract: Light detection and ranging (lidar) sensors, both at the terrestrial and airborne levels, have recently emerged as useful tools for three-dimensional (3D) reconstruction of vegetated environments. One such terrestrial laser scanner (TLS) is the Intelligent Laser Ranging and Imaging System (ILRIS-3D). The objective of this research was to develop approaches to use ILRIS-3D data to retrieve structural information of an artificial tree in a controlled laboratory experiment. The key crown-level structural parameters investigated in this study were gap fraction, leaf area index (LAI), and clumping index. Measured XYZ point cloud data from a systematically pruned tree were sliced to retrieve laser pulse return density profiles, which subsequently were used to estimate gap fraction, LAI, and clumping index. Gap fraction estimates were cross-validated with traditional methods of histogram thresholding of digital photographs (r2 = 0.95). LAI estimates from lidar data were corrected for the confounding effects of w...

Estimating leaf inclination and G-function from leveled digital camera photography in broadleaf canopies

Abstract: The effectiveness of using leveled digital camera for measuring leaf inclination angles was investigated in this study as an inexpensive and convenient alternative to existing approaches. The new method is validated with manual leaf angle measurements for various broadleaf tree species common to hemi-boreal region of Estonia and the tropical forests of Hawai’i Islands. The acquired leaf angle distributions suggest that planophile case might be more appropriate than the commonly assumed spherical as the general approximation of leaf orientation while modeling the radiation transmission through the canopies of (hemi)-boreal broadleaf stands. However, direct leaf inclination measurements should be obtained whenever possible, as there will always exist a large variety of leaf orientation, both among different species and in the space–time domain within a single species. The camera method tested in this study provides a new robust and affordable tool to obtain this information.

Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study

Abstract: . The performance of the joint assimilation in a land surface model of a Soil Wetness Index (SWI) product provided by an exponential filter together with Leaf Area Index (LAI) is investigated. The data assimilation is evaluated with different setups using the SURFEX modeling platform, for a period of seven years (2001–2007), at the SMOSREX grassland site in southwestern France. The results obtained with a Simplified Extended Kalman Filter demonstrate the effectiveness of a joint data assimilation scheme when both SWI and Leaf Area Index are merged into the ISBA-A-gs land surface model. The assimilation of a retrieved Soil Wetness Index product presents several challenges that are investigated in this study. A significant improvement of around 13 % of the root-zone soil water content is obtained by assimilating dimensionless root-zone SWI data. For comparison, the assimilation of in situ surface soil moisture is considered as well. A lower impact on the root zone is noticed. Under specific conditions, the transfer of the information from the surface to the root zone was found not accurate. Also, our results indicate that the assimilation of in situ LAI data may correct a number of deficiencies in the model, such as low LAI values in the senescence phase by using a seasonal-dependent error definition for background and observations. In order to verify the specification of the errors for SWI and LAI products, a posteriori diagnostics are employed. This approach highlights the importance of the assimilation design on the quality of the analysis. The impact of data assimilation scheme on CO2 fluxes is also quantified by using measurements of net CO2 fluxes gathered at the SMOSREX site from 2005 to 2007. An improvement of about 5 % in terms of rms error is obtained.