Leaf Area Index

swamy et al., 2003). In Mexico, it is important for determining import-export policies, government aid for Large-area yield prediction early in the growing season is important farmers, and allocation of subsidies for regional agriculin agricultural decision-making. This study derived maize (Zea mays L.) tural programs. leaf area index (LAI) estimates from spectral data and used these estimates with a simple LAI-based yield model to forecast yield under Crop models have been used for monitoring crop irrigated conditions in large areas in Sinaloa, Mexico. Leaf area index growth and predicting yield (Baez-Gonzalez and Jones, was derived from satellite data with the use of an equation developed 1995a, 1995b; Sinclair and Seligman, 1996; Sivakumar with LAI measurements from farmers' fields during the 2001-2002 and Glinni, 2002). However, their use in large areas has autumn-winter growing season. These measurements were correlated been limited because the required inputs are generally with the normalized difference vegetation index values from 2002 available only at field scale. Remote sensing provides Landsat ETMϩ (enhanced thematic mapper) data. The equation was observations over large areas at regular intervals, makthen tested with 2003 Landsat imagery data. A yield model was valiing it useful in large-scale crop modeling (Gallo and dated with maximum LAI and yield data measured in farmers' fields in

This study reports the seasonal assessment of energy balance components and carbon dioxides fluxes over a drip irrigated kiwifruit orchard, with a Leaf Area Index (LAI) of 3 at full canopy development. The most remarkable amount of energy partitioning throughout the whole season was due to latent heat flux that had values approximating to those of sensible heat flux (about

Eddy covariance measurements of CO2 fluxes were conducted in 2004 at the agricultural site of Lonzée, Belgium, over a sugar beet crop. Additional measurements of biomass net primary production and leaf area index (LAI) were carried out. The response of the fluxes to climatic and non-climatic variables was analysed. Nighttime fluxes were dependent on turbulence, temperature and high soil water

Leaf area, crown projection area and growth over the last 5 years were measured to assess growth efficiency (GE) and crown efficiency (CE) of dominant (D), codominant (CD) and suppressed (SP) trees growing in height-repressed (P sites) and normally developing (M sites) lodgepole pine stands. Leaf area index (LAI), hydraulic characteristics, and needle nutrient concentrations were also measured. Volume growth of P site trees between 1994 and 1999 was 46% that of M site trees. Volume growth was closely associated with both hydraulic supply capacity (Q*) and leaf area. Height repression was not associated with lower GE, but P site trees had CE that was 24.5% lower than M site trees. Average GE of D and CD trees was 28% lower than that of SP trees, while mean CE for the D trees was 46% greater than that of CD, and 80% greater than for SP trees. Between M and P sites, canopy LAI and Q* per unit leaf area did not differ. Needle nitrogen (N) concentrations of M site trees were 7.6% greater than for P site trees. SP tree needles had the highest concentration of N and phosphorus. The nutrient advantage enjoyed by SP trees presumably allowed them to maintain higher GE for a given Q*/A l . The fastest growing trees were the large D and CD trees from M sites. As LAI did not differ between sites, height repression on P sites may be a result of total leaf area being distributed among too many small trees.

Breeding to improve perennial grasses for forage usage aims to increase the whole-plant aerial biomass. However, the ability to increase the whole-plant yield by breeding may be questionable in grasses which are expected to reach an optimal leaf area index during grass stand growth rather rapidly. We carried out a field experiment aiming to compare herbage yield and other performances of seven natural populations and 21 cultivars of diploid perennial ryegrass registered on European National lists in the last 40 years. Cultivars were sampled in the spike emergence earliness range used for pasture usage, i.e. in the semilate and late earliness range according to the French classification into spike emergence earliness groups. Forage performances of populations and cultivars were tested in four locations in monthly cut dense sward plots. Morphological and phenological traits were recorded in two spaced-plant experiments, and seed yield was assessed in two locations in standard seed production conditions. Trait regression on cultivar registration year pointed out that total dry-matter yield of cultivars increased by +3.2% per decade. However, dry-matter yield was not improved in the most favourable period for grass growth, i.e. in spring. On the other hand, it was improved in summer (+2.8% per decade) and autumn (+7.4% per decade) when the aerial biomass production is on average rather small. Breeders succeeded in significantly reducing aftermath heading. Reduction in aftermath heading is likely to have contributed to the noted increase in summer and autumn dry-matter yields, and to a moderate improvement in herbage feeding value. Breeding was also efficient in improving rust resistance and in bringing forward the start of spring growth. For monthly cut swards, we evidenced a clear association of leaf and lamina lengths with spring and summer dry-matter yields. Breeding for long leaves, or for high leaf elongation rate, should contribute to improve the cumulated intercepted radiation during re-growths, and consequently could be a way of improving the spring dry-matter yield. Seed yield did not improve with breeding for forage performances. However, we did not notice any negative association between the seed yield and traits related with forage usage. Direct selection pressures on seed yield criteria applied at the core of the breeding process should enable to improve the seed yield without any negative impact on forage performances.

Wheat (Triticum aestivum L.) is the most important cereal crop after rice in India. Optimum schedule of irrigation for wheat and its response to irrigation based on the ratio of irrigation water and cumulative pan evaporation (irrigation depth (IW):CPE at 1.2, 0.9 and 0.6) was studied in a field experiment during the winter seasons of 1989-1990 and 1990-1991. The site had a sandy loam (Typic Fluvaquent) soil and shallow water table, located in the humid tropical canal command area at the University Experimental Farm, Memari (2381 0 N, 8885 0 E and 21.34 m above mean sea level) in West Bengal, India. The yield of wheat, weekly and seasonal actual evapotranspiration (ETa) from water balance equation, crop coefficients (K c ), soil water stress coefficients (K s ), water extraction patterns, water use efficiency (WUE) and water application efficiency (A e ) were determined. Maximum profile water depletion and ETa of wheat occurred in the wetter moisture regime (1.2 IW:CPE). The average daily ETa varied from <1 mm per day in the early growing period to a maximum value of 2.72 mm per day at 9-14 weeks after sowing (WAS) under 1.2 IW:CPE when leaf area index (LAI) was >3. During crop development to mid season (4-14 WAS), 1.2 IW:CPE showed 9-15% increased ETa than 0.9 and 0.6 IW:CPE. The seasonal ETa of wheat with IW:CPE of 1.2 was 238.2 and 261.95 mm during 1989-1990 and 1990-1991, respectively. Maximum roots were concentrated in the top 150 mm layer (57% of root length density) and maximum root water extraction efficiency (U z ) was observed at 600-750 mm depth under the drier soil moisture regimes of 0.9 and 0.6 IW:CPE, respectively. The yield increased significantly with increasing levels of irrigation. IW:CPE ratio of 1.2 produced 13 and 21% more yield, and 8 and 14% improved WUE than 0.9 and 0.6 IW:CPE, respectively. Water application efficiency (A e ) was noticed higher (79.85%) under 0.6 IW:CPE irrigation regime. Precise information of K c , which is required for regional scale irrigation planning is lacking in developing countries. The estimated values of K c for wheat at four crop growth stages (initial, crop development, mid season and maturity) were 0.33, 0.82, 1.08 and Agricultural Water Management 59 (2003) 33-47 : S 0 3 7 8 -3 7 7 4 ( 0 2 ) 0 0 1 1 2 -9 0.64, respectively which were identical to those suggested by the FAO indicating need for generating these values at the local/regional level. The K s values of 0.6 IW:CPE decreased steeply and experienced more stress condition than 0.9 IW:CPE. #

Plant leaf area index (LAI) is an important structural parameter for describing the ability of the canopy to intercept solar radiation, and it plays an important role in the estimation of forest biomass. To overcome the difficulties of current ground measurement instruments in automatically collecting plant LAI, we have designed a continuous LAI measurement system: LAINet. The main part of LAINet includes the distributed Below Node (BN), which is deployed below the canopy and receives transmitted solar radiation, the Above Node (AN), which is used to receive downward radiation above the canopy, and the Central Node (CN), which is used as a data reception and control node. Communication among the nodes is implemented through the Zigbee protocol, while data exchange between the CN and the remote data center server is completed through the General Packet Radio Service (GPRS) network. The design of the LAINet framework and the algorithm for estimating the LAI from a multi-point directional transmittance is presented in this paper. The sensors of LAINet are calibrated on two clear days, and the performance of the proposed system is compared in time series field experiments. Comparison of the nodes' sensor results indicates that under the condition of the same solar radiation, the response between the different sensors is of high consistence, and each node has a stable calibration coefficient across different dates. In the field coniferous forest experiment, upon comparing with TRAC (Tracing Radiance and Architecture of Canopies) instruments and the results obtained using different data processing algorithms, it is found that the LAINet system can produce the best results with a minimum root mean square error (RMSE = 0.34) and a higher determination coefficient (R 2 = 0.81). We adopt a multi-day window for aggregating the daily observed LAI to remove the noise that occurs from daily weather variation, and it indicates that the aggregated time series LAI can capture the process of the coniferous needles' growth and defoliation properly. Thus, it is confirmed that LAINet can be used as a feasible method to conduct automatic ground observations, especially in the scenario where continuous observation is required.

Leaf area index (LAI) is one of the most frequently used parameters for the analysis of canopy structure and it has also been shown to be an important structural characteristic of the forest ecosystem and forest productivity. The objectives of this study were: (1) to calibrate optical estimates of PAI (plant area index) from the LAI-2000 using leaf area index derived from allometric models for six different tropical tree species and (2) to explore the corresponding relationship of calibrated LAI-2000 with stand productivity indices and environmental factors along a strong environmental gradient in the southern region of Costa Rica. From sixteen 6-year-old pure stand plantations (trees spaced 3 m  3 m) of four fast growing native species (Terminalia amazonia, Vochysia ferruginea, Vochysia guatemalensis and Hieronyma alchorneoides) and two introduced species (Pinus caribaea var hondurensis and Gmelina arborea), the plant area index (PAI) was estimated indirectly using the LAI-2000 plant canopy analyzer (LI-COR, Lincoln, NE), under cloudy sky conditions at a fixed height of 1.3 m above the ground with a 458 view cap. In addition, leaf area index (LAI) was estimated allometrically by felling four selected trees and measuring the area and biomass of leaves. The specific leaf area (SLA) showed typical values for each tree species that ranged between 81 cm 2 g À1 (V. ferruginea) and 106 cm 2 g À1 (G. arborea). Based on the characteristic SLA, for all tree species, the leaf area per tree could be estimated by allometric equations using the dbh (diameter at 1.3 m) as the independent variable. The calibration of the LAI-2000 PAI data versus the allometric estimate of leaf area showed strong and unbiased relationship for the species: T. amazonia, V. guatemalensis, H. alchorneoides and P. caribaea. In the case of G. arborea and V. ferruginea the LAI-2000 PAI values underestimated and overestimated the allometric measurements of LAI. For all tree species, calibrated LAI-2000 values were used as an independent variable in highly significant regression equations to estimate dominant tree height in each stand (in m) and stand yield in m 3 ha À1 year À1 , implying that calibrated LAI-2000 can be used to evaluate site quality and stand productivity. The generalized relationships for all species, between average calibrated LAI-2000 with stands yield or dominant tree height among four Eco-regions, indicated that as soil nutrient and water supply become optimal for tree growth, maximum LAI, dominant stand height and yield values are obtained.

Reliable estimation of the surface energy balance from local to regional scales is crucial for many applications including weather forecasting, hydrologic modeling, irrigation scheduling, water resource management, and climate change research. Numerous models have been developed using remote sensing, which permits spatially distributed mapping of the surface energy balance over large areas. This study compares flux maps over a relatively simple agricultural landscape in central Iowa, comprised of soybean and corn fields, generated with three different remote sensing-based surface energy balance models: the Two-Source Energy Balance (TSEB) model, Mapping EvapoTranspiration at high Resolution using Internalized Calibration (METRIC), and the Trapezoid Interpolation Model (TIM). The three models have different levels of complexity and input requirements, but all have operational capabilities. METRIC and TIM make use of the remotely sensed surface temperature-vegetation cover relation to define key model variables linked to wet and dry hydrologic extremes, while TSEB uses these remotely sensed inputs to define component soil and canopy temperatures, aerodynamic resistances, and fluxes. The models were run using Landsat imagery collected during the Soil Moisture Atmosphere Coupling Experiment (SMACEX) in 2002 and model results were compared with observations from a network of flux towers deployed within the study area. While TSEB and METRIC yielded similar and reasonable agreement with measured heat fluxes, with root-mean-square errors (RMSE) of $50-75 W/m 2 , errors for TIM exceeded 100 W/m 2 . Despite the good agreement between TSEB and METRIC at discrete locations sampled by the flux towers, a spatial intercomparison of gridded model output (i.e., comparing output on a pixel-by-pixel basis) revealed significant discrepancies in modeled turbulent heat flux patterns that were largely correlated with vegetation density. Generally, the largest discrepancies, primarily a bias in H, between these two models occurred in areas with partial vegetation cover and a leaf area index (LAI) < 2.0. Adjustment of the minimum LE assumed for the hot/dry hydrologic extreme condition in METRIC reduced the bias in H between METRIC and TSEB, but caused a significant increase in bias in LE between the models. Spatial intercomparison of modeled flux patterns over a variety of landscapes will be required to better assess uncertainties in remote sensing surface energy balance models, and to work toward an improved hybrid modeling system.

Transpiration rates were measured in a flooded population of Phragmites australis ssp. altissima in a wetland located in El Hondo Natural Park (southeastern Spain) during the growing season of 2000. The heat balance method for measuring sap flow was used to calculate the rate of water transpiration on a whole-stem basis. Four series of measurements were carried out in selected weeks in May, June, August and October. Structure, biomass and leaf area index of the reed population were simultaneously quantified in order to scale transpiration on a plot-area basis.Overall, transpiration flux was high during the sampling period and showed a typical diurnal pattern with a maximum at about midday. Mean transpiration was highest at the end of June coinciding with the peak of reed growth and with the maximum leaf area both at individual and plot scales. Rates decreased abruptly in October, in parallel with the advanced foliar senescence. The variation of both midday and integrated daily transpiration is significantly related to that of the air temperature on clear days. Cloudy and rainy days exert a pronounced effect on water loss by decreasing transpiration. Our results highlight the potential use of the sap-flow method to measure transpiration in reed ecosystems and the relevance of this flux for the water balance in wetlands in semi-arid environments. Thus, it is suggested that water management in these areas could be favoured by acquiring high-quality experimental data.

Litter is frequently present within vegetation canopies and thus contributes to the overall spectral response of a canopy. Consequently, litter will affect spectral indices designed to be sensitive to green vegetation, soil brightness or other features. The main objectives of the current research were to 1) evaluate the spectral properties of green vegetation and litter and 2) quantify the effect of standing litter on the performance of spectral indices. The SAIL (scattering by arbitrarily inclined leaves) model was used to generate canopy reflectance "mixtures" and to estimate fractions of absorbed photosynthetically active radiation (fAPAR) with varying leaf area index (LAI), soil background, combinations of vegetation component spectral properties, and one or two horizontal vegetation layers. Spectral measurements of different bare soils and mature green and senescent leaves of representative plant species at the HAPEX-Sahel (Hydrological Atmospheric Pilot Experiment) study sites were used as input. The normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SA VI), and the modified NDVI (MNDVI) and mixture model spectral indices were selected to evaluate their performance with respect to standing litter and green vegetation mixtures. Spectral reflectance signatures of leaf litter varied significantly, but strongly resembled soil spectral characteristics. The biophysical parameters (LAI, fAPAR), derived from spectral vegetation indices, tended to be overestimated for randomly distributed, sparse green and litter vegetation cover mixtures, and underestimated for randomly distributed dense green and litter vegetation cover mixtures. All spectral indices and their biophysical interpretation were significantly altered by variability in 1) green leaf, leaf litter, and bark optical properties, 2) the amount and position of standing leaf litter, 3) leaf angle distribution, and 4) soil background. The NDVI response to these variables was inconsistent, and was the most affected by litter. The spectral mixture model indices, designed to be sensitive to litter, were shown to be promising for the identification of litter present among different ecosystems.

Progress in assessing the feasibility for imaging fluorescence using the O 2 -A band with 1 nm full-width halfmaximum (FWHM) bands centered at 757.5 and 760.5 nm is reported in this paper. Multispectral airborne data was acquired at 150 m above ground level in the thermal, visible and near infrared regions yielding imagery at 15 cm spatial resolution. Simultaneous field experiments conducted in olive, peach, and orange orchards (water stress trials), and an olive orchard (variety trial) enabled the detected variability in fluorescence emission to be examined as function of stress status. In a parallel modelling activity the coupled leaf-canopy reflectance-fluorescence model, FluorMOD, was used to assess fluorescence retrieval capability by the in-filling method, as well as by fluorescence indices from the published literature. Fluorescence retrievals using the in-filling method, the derivative index D702/D680 and reflectance indices R690/R630, R761-R757, and R761/R757 yielded the best results in the simulation study, while demonstrating insensitivity to leaf area index (LAI) variation. The fluorescence in-filling method, derivative index D702/ D680, and R761-R757 were the indices least affected by chlorophyll a + b (Cab) variation. On the other hand, other published indices for fluorescence detection at leaf and canopy levels exhibited high sensitivity to variations in Cab and LAI, and therefore were considered less suitable for in-field fluorescence detection. The fluorescence signal extraction from airborne imagery using the in-filling method was validated through comparisons with field-measured steady-state fluorescence (Fs) using the PAM-2100 and GFS-3000 instruments, confirming simulation predictions. The water stress experiments conducted on olive and peach orchards demonstrated the feasibility of chlorophyll fluorescence (F) extraction at the tree level from the airborne imagery, yielding determination coefficients r 2 = 0.57 (olive), and r 2 = 0.54 (peach). Consistent results were obtained between airborne F and ground truth assimilation (A) measured in the olive variety field experiment under no water stress levels, yielding r 2 = 0.71.

Crops respond to N deficiency through a reduction in resource capture and/or resource use efficiency. The objective of this paper is to examine whether differences in this response pattern are associated with either metabolic group (C 3 vs. C 4 ) or botanical classification (mono-vs. dicotyledons). Hereto, we analysed the effect of N deficiency on the relationships between N uptake, LAI, and biomass accumulation, for maize, sorghum, wheat, canola, tall fescue, and sunflower, grown in experiments in either France or Australia. Maize and tall fescue maintained LAI per unit biomass (measure of resource capture) at the expense of N uptake per unit LAI (measure of resource use efficiency). Wheat and canola had the opposite response, whereas sunflower and sorghum were intermediate. In general, C 4 species reduced N uptake per unit LAI more than C 3 species. Species differences in the effect of N deficiency on resource use efficiency were associated with differences in the SLN or in the N storage capacity of the stems. For wheat, canola, and tall fescue, SLN declined with increasing LAI under high N conditions, and the minimum crop SLN under N deficiency was only marginally lower than under high N conditions. For sorghum, sunflower, and maize, crop SLN under high N changed little with increasing LAI, but the minimum crop SLN under N deficiency was considerably lower than under high N. Sorghum and maize were the only species that substantially decreased stem N uptake per unit LAI under N deficiency. Overall, our data suggest that C 3 species are better able to maintain resource use efficiency under N stress than C 4 species, and a survey of literature suggests this may be because in C 4 species, the critical SLN for radiation use efficiency is higher than the critical SLN for leaf expansion, whereas the opposite is the case for C 3 species. We hypothesise that species differences in response to N deficiency could be associated with these differences in critical SLN, which in turn could be a consequence of the lower photosynthetic nitrogen use efficiency of C 3 crops. #

Eddy covariance measurements of CO 2 fluxes were conducted in 2004 at the agricultural site of Lonzée, Belgium, over a sugar beet crop. Additional measurements of biomass net primary production and leaf area index (LAI) were carried out. The response of the fluxes to climatic and non-climatic variables was analysed. Nighttime fluxes were dependent on turbulence, temperature and high soil water content. The u * correction was determined using a statistically based algorithm. The lower u * threshold was 0.1 m s À1 . Daytime fluxes during maximum canopy development depended mainly on incident radiation and its repartition between direct and diffuse components. A limited response to saturation deficit and soil water content was also observed. The evolution of assimilation and respiration throughout the growing season was studied. Maximum assimilation fluxes were observed in July when canopy had not fully developed and these then decreased from the end of July to the harvest, due not only to a reduction in radiation but also to a reduction in canopy assimilation capacity. Normalised respiration evolution presented two peaks during the year: the first in July, when the assimilation was at its greatest, and the second after the harvest, during the crop residues decomposition. The annual sequestration, estimated by half-hourly flux summing and measurement gap filling, was À0.61 AE 0.11 kg C m À2 and the impact of the u * correction and of the residues decomposition was estimated to be 5.3 and 3.5%, respectively.

Various crop growth simulation models exist for rice but thorough validation and evaluation reports are scarce. We present the model ORYZA2000, which simulates the growth and development of rice under conditions of potential production and water and nitrogen limitations. The model was evaluated against a data set of five field experiments with irrigated rice performed at IRRI between 1991 and 1993, with nitrogen levels varying from 0 to 400 kg ha À1 in different splits and timings of application. We compared simulated and measured leaf area index (LAI) and biomass of leaves, stems, panicles, and total aboveground biomass by graphics; by the slope, intercept, and adjusted coefficient of correlation; by StudentÕs t test of means; and by absolute and normalized root mean square errors (RMSE). On average, RMSE was 690-1280 kg ha À1 for total biomass, 350-380 kg ha À1 for leaf biomass, 460-790 kg ha À1 for stem biomass, and 380-580 kg ha À1 for panicle biomass. Yield was simulated with an RMSE of 840-850 kg ha À1 and a normalized RMSE of 11-13%. For these crop variables, normalized RMSE values were 65-84% higher than the typical coefficients of variation associated with their measurements. Simulated LAI generally exceeded measured values, especially at low levels of nitrogen application. We can use ORYZA2000 to support N field experiments and investigate optimum N application regimes with quantified errors of simulation.

Because of the high water content of vegetation, water absorption features dominate spectral reflectance of vegetation in the near-infrared region of the spectrum. In comparison to indices based on chlorophyll absorption features (such as the normalized difference vegetation index (NDVI)), indices based on the water absorption bands are expected to ''see'' more deeply into thick canopies and have a preferential sensitivity to thin as opposed to thick tissues. These predictions are based on the much lower absorption coefficients for water in the short wavelength water bands as compared to chlorophyll. Thus, the water bands may have advantages over NDVI for remote sensing of photosynthetic tissues. Previous studies have primarily related water band indices (WI) to leaf area index (LAI). Here we expand the definition of photosynthetic tissues to include thin green stems and fruits and measure a wide range of species to determine the influence of variable tissue morphologies and canopy structures on these relationships. As expected, indices based on reflectance in the water absorption bands in the near infrared were best correlated with the water content of thin tissues (less than 0.5-cm thickness). The choice of wavelength for a water index was much more important for thick than for thin canopies, and the best wavelengths were those where water absorptance was weak to moderate. We identified three wavelength regions (950-970, 1150-1260 and 1520-1540 nm) that produced the best overall correlations with water content. Comparison of these wavelength regions with the atmospheric ''windows'' where water vapor absorption is minimal suggests that the 1150-1260 and 1520-1540 nm regions would be the best wavelengths for satellite remote sensing of water content. We also developed and tested a new Canopy Structure Index (CSI) that combines the low absorptance water bands with the simple ratio vegetation index (SR) to produce an index with a wider range of sensitivity to photosynthetic tissue area at all canopy thicknesses. CSI was better than either WI or SR alone for prediction of total area of photosynthetic tissues. However, SR was best for prediction of leaf area when other green tissues were excluded. All of these relationships showed good generality across a wide range of species and functional types.

The magnitude and seasonal dynamics of evapotranspiration (ET) for a steppe in central Mongolia was estimated over a full year period (from 25 March 2003 to 24 March 2004, 366 days) using the eddy covariance (EC) technique. The steppe, typical of central Mongolia, ...

The montado/dehesa landscapes of the Iberian Peninsula are savannah-type open woodlands dominated by evergreen oak species (Quercus suber L. and Q. ilex ssp. rotundifolia). Scattered trees stand over an undergrowth of shrubs or herbaceous plants. To partition leaf area index between trees and the herbaceous/shrubby understorey requires good estimates of tree canopy cover and is of key importance to understand the ecology and the changes in land cover. The two vegetation components differ in phenology as well as in radiation and rainfall interception, water and CO 2 fluxes. The main goal of this study was to estimate tree canopy cover in a montado/dehesa region of southern Portugal (Alentejo) using remote sensed data. For this purpose we developed empirical models combining measurements obtained through the analysis of aerial photos and reflectance from Landsat Thematic Mapper (TM) individual channels, vegetation indices, and the components of the Kauth-Thomas (K-T) transformation. A set of 142 plots was designed, both in the aerial photos and in the satellite data. Several simple and multiple linear regression models were adjusted and validated. A subset of 75% of the data (n = 106) was used for model fitting, and the remainder (n = 36) was used for model assessment. The best linear equation includes Landsat TM channels 3, 4, 5 and 7 (r 2 = 0.74), but the Normalised Difference Vegetation Index (NDVI), the components of the K-T transformation, and the Atmospherically Resistant Vegetation Index (ARVI) also performed well (r 2 = 0.72, 0.70, and 0.69, respectively). The statistics of prediction residuals and tests of model validation indicates that these were also the models with better predictive capability. These results show that detection of low/medium tree canopy cover in this type of land cover (i.e. evergreen oak woodlands) can be accomplished with the help of high and medium spatial resolution satellite imagery. #

The water balance and growth of Eucalyptus grandis hybrid plantations in Brazil are presented based on 6 years of intensive catchment hydrology, physiological and forest growthsurveying, and modelling. The results show a balance between water supply by precipitation and output through evapotranspiration (considered as canopy interception, soil evaporation and trees transpiration) and runoff. The annual average precipitation was 1147 mm

A field study on cotton (Gossypium hirsutum L., cv.) was carried out from 2005 to 2008 in the Çukurova Region, Eastern Mediterranean, Turkey. Treatments were designated as I100 full irrigation; DI70, DI50 and DI00 which received 70, 50, and 0% of the irrigation water amount applied in the I100 treatment. The irrigation water amount to be applied to the plots

Native tree plots have been established in river irrigation districts in the western U.S. to provide habitat for threatened and endangered birds. Information is needed on the effective irrigation requirements of the target species. Cottonwood (Populus spp.) and willow (Salix gooddingii) trees were grown for seven years in an outdoor plot in a desert environment in Tucson, Arizona. Plants were allowed to achieve a nearly complete canopy cover over the first four years, then were subjected to three daily summer irrigation schedules of 6.20 mm d−1; 8.26 mm d−1 and 15.7 mm d−1. The lowest irrigation rate was sufficient to maintain growth and high leaf area index for cottonwoods over three years, while willows suffered considerable die-back on this rate in years six and seven. These irrigation rates were applied April 15–September 15, but only 0.88 mm d−1 was applied during the dormant period of the year. Expressed as a fraction of reference crop evapotranspiration (ETo), recommended annual water applications plus precipitation (and including some deep drainage) were 0.83 ETo for cottonwood and 1.01 ETo for willow. Current practices tend to over-irrigate restoration plots, and this study can provide guidelines for more efficient water use.

Th e fi rst crop chosen to parameterize and test the new FAO AquaCrop model is maize (Zea mays L.). Working mainly with data sets from 6 yr of maize fi eld experiments at Davis, CA, plus another 4 yr of Davis maize canopy data, a set of conservative (nearly constant) parameters of AquaCrop, presumably applicable to widely diff erent conditions and not specifi c to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr of Davis data. Th e treatment variable was irrigation-withholding water aft er planting continuously, only up to tasseling, from tasseling onward, or intermittently, and with full irrigation (FI) as the control. From year to year, plant density (7-11.9 plants m −2 ), planting date (14 May-15 June), cultivar (a total of four), and atmospheric evaporative demand varied. Th e conservative parameters included: canopy growth and canopy decline coeffi cient (CDC); crop coeffi cient for transpiration (Tr) at full canopy; normalized water productivity for biomass (WP*); soil water depletion thresholds for the inhibition leaf growth and of stomatal conductance, and for the acceleration of canopy senescence; reference harvest index (HI o ); and coeffi cients for adjusting harvest index (HI) in relation to inhibition of leaf growth and of stomatal conductance. With all 19 parameters held constant, AquaCrop simulated the fi nal aboveground biomass within 10% of the measured value for at least 8 of the 13 treatments (6 yr of experiments) and also the grain yield for at least fi ve of the cases. In at least four of the cases, the simulated results were within 5% of the measured for biomass as well as for grain yield. Th e largest deviation between the simulated and measured values was 22% for biomass, and 24% for grain yield. Importantly, the simulated pattern of canopy progression and biomass accumulation over time were close to those measured, with Willmott's index of agreement (d) for 11 of the 13 cases being ≥0.98 for canopy cover (CC), and ≥0.97 for biomass. Accelerated senescence of canopy due to water stress, however, proved to be diffi cult to simulate accurately; of the six cases, the index of agreement for the worst one was 0.957 for canopy and 0.915 for biomass. Possible reasons for the discrepancies between the simulated and measured results include simplifi cations in the model and inaccuracies in measurements. Th e usefulness of AquaCrop with well-calibrated conservative parameters in assessing water use effi ciency (WUE) of a crops under diff erent conditions and in devising strategies to improve WUE is discussed. area index; p, fractional depletion of total available water in the root zone; PWP, permanent wilting point; SWC, soil water content; Tr, crop transpiration; WP, water productivity (for biomass); WP*, normalized (for evaporative demand and atmospheric CO 2 ) water productivity (for biomass); WUE, water use effi ciency.

Abstract A lack of reliable observations for canopy science research is being partly overcome by the gradual use of lidar remote sensing. This study aims to improve lidar-based canopy characterization with airborne laser scanners through the combined use of lidar ...

Forest managers now operate in an information-rich but increasingly challenging environment in which the competing demands of environmental stewardship and sustainable management must counter-balance the demands of increased production and profitability. Management support tools, in particular, decision support systems are essential aids in this operating environment. A dynamic forest growth model, CArbon BALAnce (CABALA), that links carbon, water and nitrogen flows through the atmosphere, trees and soil including soil organic matter is presented here as a central part of a silvicultural decision support system.The strong linkage between stand biomass allocation and external environmental conditions make CABALA a model suitable for exploring stand management options and the effects of factors such as frost and drought on growth.The model performance is verified extensively using fertiliser, spacing and thinning trials. Predictions of nitrogen mineralisation, light interception, plant water stress, and biomass allocation as well as stand growth and stand leaf area index are tested with observed data.

Light attenuation within a row crop such as maize is in¯uenced by canopy architecture, which has to be de®ned in terms of the size, shape and orientation of shoot components. Cultural practices that improve the ef®ciency of light interception affect canopy architecture by modifying such components. Our objectives were to: (i) determine the nature and timing of leaf growth responses to plant population and row spacing; (ii) analyze light attenuation within fully developed maize canopies. Field experiments were conducted at Pergamino (33856 H S, 60834 H W) and Salto (34833 H S, 60833 H W), Argentina, during 1996/1997 and 1997/1998 on silty clay loam soils (Typic Argiudoll) that were well watered and fertilized. Four maize hybrids of contrasting plant type were grown at three plant populations (3, 9 and 12 plants m À2 ) and two row spacings (0.35 and 0.70 m). Plant population promoted larger changes in shoot organs than did row spacing. As from early stages of crop growth, leaf growth (V 6 ±V 8 ) and azimuthal orientation (V 10 ±V 11 ) were markedly affected by treatments. Modi®cations in shoot size and leaf orientation suggest shade avoidance reactions, probably triggered by a reduction in the red:far-red ratio of light within the canopy. An interaction between hybrid and plant rectangularity on leaf azimuthal distribution was determined, with one hybrid displaying a random azimuthal leaf distribution under most conditions. This type of hybrid was de®ned as rigid. The other hybrids showed modi®ed azimuthal distribution of leaves in response to plant rectangularity, even at very low plant populations. These hybrids were de®ned as plastic. Once maximum leaf area index (LAI) was attained light attenuation did not vary among hybrids and row spacing for plant populations !9 plants m À2 (k coef®cient: 0.55 and 0.65 for 9 and 12 plants m À2 , respectively). A more uniform plant distribution increased light attenuation (k coef®cient: 0.37±0.49) only when crop canopies did not reach the critical LAI. #

This paper presents a mathematical model yielding a sensible, albeit simplified representation of the dynamic thermal behaviour of actual green roofs. Several parametric sensitivity analyses have been carried out to assess the cooling potential of green roofs in summer. The main conclusion of these analyses is that green roofs do not act as cooling devices but as insulation ones, reducing the heat flux through the roof. A relatively small set of parameters have been identified as relevant for green roof design: the leaf area index (LAI) and the foliage geometrical characteristics, the soil apparent density, its thickness, and its moisture content. 0 1998 Elsevier Science S.A.

This paper presents a methodology for water stress detection in crop canopies using a radiative transfer modelling approach and the Photochemical Reflectance Index (PRI). Airborne imagery was acquired with a 6band multispectral camera yielding 15 cm spatial resolution and 10 nm FWHM over 3 crops comprising two tree-structured orchards and a corn field. The methodology is based on the PRI as a water stress indicator, and a radiative transfer modelling approach to simulate PRI baselines for non-stress conditions as a function of leaf structure, chlorophyll concentration (Cab), and canopy leaf area index (LAI). The simulation work demonstrates that canopy PRI is affected by structural parameters such as LAI, Cab, leaf structure, background effects, viewing angle and sun position. The modelling work accounts for such leaf biochemical and canopy structural inputs to simulate the PRI-based water stress thresholds for non-stress conditions. Water stress levels are quantified by comparing the image-derived PRI and the simulated non-stress PRI (sPRI) obtained through radiative transfer. PRI simulation was conducted using the coupled PROSPECT-SAILH models for the corn field, and the PROSPECT leaf model coupled with FLIGHT 3D radiative transfer model for the olive and peach orchards. Results obtained confirm that PRI is a pre-visual indicator of water stress, yielding good relationships for the three crops studied with canopy temperature, an indicator of stomatal conductance (r 2 = 0.65 for olive, r 2 = 0.8 for peach, and r 2 = 0.72 for maize). PRI values of deficit irrigation treatments in olive and peach were consistently higher than the modelled PRI for the study sites, yielding relationships with water potential (r 2 = 0.84) that enabled the identification of stressed crowns accounting for within-field LAI and Cab variability. The methodology presented here for water stress detection is based on the visible part of the spectrum, and therefore it has important implications for remote sensing applications in agriculture. This method may be a better alternative to using the thermal region, which has limitations to acquire operationally high spatial resolution thermal imagery.

A pot experiment was conducted in a completely randomized design, to study the effect of Zinc Sulphate (ZnSO4) and Ascorbic Acid (AA) foliar application application 20 and 40 ppm was compared to the control (distillated water) on flowering Gazania (Gazania rigens cv. daybreak red stripe). Results were analyzed by SPSS software and duncan test. The data showed significant differences between different concentrations of zinc sulphate and ascorbic acid and control. According to variance analysis, significant differences were observed among 40 mg.L-1 AA + 40 mg.L-1 ZnSO4 of treatments and control in Leaf area with 13.4 and 6.55 cm2 respectively. According to variance analysis, significant differences were observed among 40 mg.L-1 ZnSO4 of treatments and control in Total of flowers/plant, No. Sucker, Pedicle diameter, Pedicle length, Shoot fresh weight and Shoot dry weight respectively. In view of the obtained results, the growth rate of Gazania rigens plants can be stimulated through increasing growth and flowering by applications of Zinc Sulphate.

To study the leaf area index, LAI, based thermal performance in distinguishing trees for Cairo's urban developments, ENVI-met plants database was used as platform for a foliage modeling parameter, the leaf area density, LAD. Two Egyptian trees; Ficus elastica, and Peltophorum pterocarpum were simulated in 2 urban sites with one having no trees, whilst the second is having Ficus nitida trees. Trees LAD values were calculated using flat leaves' trees LAI definition to produce maximum ground solid shadow at peak time. An empirical value of 1 for LAI is applied to numerically introduce LAD values for ENVI-met.

The continuously increasing demand of accurate quantitative high quality information on land surface properties will be faced by a new generation of environmental Earth observation (EO) missions. One current example, associated with a high potential to contribute to those demands, is the multi-spectral ESA Sentinel-2 (S2) system. The present study focuses on the evaluation of spectral information content needed for crop leaf area index (LAI) mapping in view of the future sensors. Data from a field campaign were used to determine the optimal spectral sampling from available S2 bands applying inversion of a radiative transfer model (PROSAIL) with look-up table (LUT) and artificial neural network (ANN) approaches. Overall LAI estimation performance of the proposed LUT approach (LUT N50 ) was comparable in terms of retrieval performances with a tested and approved ANN method. Employing seven-and eight-band combinations, the LUT N50 approach obtained LAI RMSE of 0.53 and normalized LAI RMSE of 0.12, which was comparable to the results of the ANN. However, the LUT N50 method showed a higher robustness and insensitivity to different band settings. Most frequently selected wavebands were located in near infrared and red edge spectral regions. In conclusion, our results emphasize the potential benefits of the Sentinel-2 mission for agricultural applications. OPEN ACCESS Remote Sens. 2012, 4 562