Foliage Area Research Articles

Adaptation of stomatal conductance, photosynthesis and water-use efficiency at shoot and canopy scales in adjacent stands of Dacrycarpus dacrydioides and Podocarpus totara.

We tested an approach to estimate daily canopy net photosynthesis, A, based on estimates of transpiration, E, using measurements of sap flow and water-use efficiency, ω, by measuring δ13C in CO2 respired from shoots in the canopies of two conifers (Podocarpaceae) native to New Zealand. The trees were planted in adjacent 20-year-old stands with the same soil and environmental conditions. Leaf area index was lower for Dacrycarpus dacrydioides D.Don in Lamb (1.34m2m-2) than for Podocarpus totara G.Benn. ex D.Don var. totara (2.01m2m-2), but mean (± standard error) stem diameters were the same at 152±21mm for D. dacrydioides and 154±25mm for P. totara. Over a 28-day period, daily A (per unit ground area) ranged almost five-fold but there were no significant differences between species (mean 2.73±1.02 gC m-2 day-1). This was attributable to higher daily values of E (2.63±0.83mm day-1) and lower ω (1.35±0.53 gC kg H2O-1) for D. dacrydioides compared with lower E (1.82±0.72mm day-1) and higher ω (1.90±0.77 gC kg H2O-1) for P. totara. We attributed this to higher nitrogen availability and nitrogen concentration per unit foliage area, Na, and greater exposure to irradiance in the D. dacrydioides canopy compared with P. totara. Our findings support earlier observations that D. dacrydioides is more adapted to sites with poor drainage. In contrast, the high retention of leaf area and maintaining low rates of transpiration by P. totara, resulting in higher water-use efficiency, is an adaptive response to survival in dry conditions. Our findings show that physiological adjustments for two species adapted to different environments led to similar canopy photosynthesis rates when the trees were grown in the same conditions. We demonstrated consistency between whole-tree and more intensive shoot-scale measurements, confirming that integrated approaches are appropriate for comparative estimates of carbon uptake in stands with different species.

Diminishing carryover benefits of earlier spring vegetation growth.

Spring vegetation growth can benefit summer growth by increasing foliage area and carbon sequestration potential, or impair it by consuming additional resources needed for sustaining subsequent growth. However, the prevalent driving mechanism and its temporal changes remain unknown. Using satellite observations and long-term atmospheric CO2 records, here we show a weakening trend of the linkage between spring and summer vegetation growth/productivity in the Northern Hemisphere during 1982-2021. This weakening is driven by warmer and more extreme hot weather that becomes unfavourable for peak-season growth, shifting peak plant functioning away from earlier periods. This is further exacerbated by seasonally growing ecosystem water stress due to reduced water supply and enhanced water demand. Our finding suggests that beneficial carryover effects of spring growth on summer growth are diminishing or even reversing, acting as an early warning sign of the ongoing shift of climatic effects from stimulating to suppressing plant photosynthesis during the early to peak seasons.

River flow decline across the entire Arkansas River Basin in the 21st century

The Arkansas River and its tributaries provide critical water resources for agricultural irrigation, hydropower generation, and public water supply in the Arkansas River Basin (ARB). However, climate change and other environmental factors have imposed significant impacts on regional hydrological processes, resulting in widespread ecological and economic consequences. In this study, we projected future river flow patterns in the 21st century across the entire ARB under two climate and socio-economic change scenarios (i.e., SSP2-RCP45 and SSP5-RCP85) using the process-based Dynamic Land Ecosystem Model (DLEM). We designed “baseline simulations” (all driving factors were kept constant at the level circa 2000) and “environmental change simulations” (at least one driving factor changed over time during 2001–2099) to simulate the inter-annual variations of river flow and quantify the contributions of four driving factors (i.e., climate change, CO2 concentration, atmospheric nitrogen deposition, and land use change). Results showed that the Arkansas River flow in 2080–2099 would decrease by 12.1% in the SSP2-RCP45 and 27.9% in the SSP5-RCP85 compared to that during 2000–2019. River flow decline would occur from the beginning to the middle of this century in the SSP2-RCP45 and happen throughout the entire century in the SSP5-RCP85. All major rivers in the ARB would experience river flow decline with the largest percentage reduction in the western and southwestern ARB. Warming and drying climates would account for 77%–95% of the reduction. The rising CO2 concentration would exacerbate the decline through increasing foliage area and ecosystem evapotranspiration. This study provides insight into the spatial patterns of future changes in water availability in the ARB and the underlying mechanisms controlling these changes. This information is critical for designing watershed-specific management strategies to maintain regional water resource sustainability and mitigate the adverse impacts of climate changes on water availability.

Factors Affecting Droplet Loss behind Canopies with Air-Assisted Sprayers Used for Fruit Trees

Air-assisted sprayers are widely employed in orchards, but inappropriate spray parameters can lead to large droplet losses, pesticide waste, and environmental pollution. To investigate the factors affecting the droplet loss of an air-assisted sprayer behind canopies, a two-factor, five-level full experiment was conducted in an actual orchard, where the two factors were the power gradient and foliage area volume density (FAVD). In addition, the location of the sampling point was also considered in the data analysis, including horizontal distance, forward distance, and height. The results show that all factors significantly affected droplet coverage (p-value < 0.01). The droplet coverage showed an increase and then a decrease with an increasing power gradient, and the maximum coverage was measured at power gradient P3 (forward speed: 0.49 m/s, spray pressure: 0.30 MPa, and spray flow rate: 7.13 L/min) or P4 (forward speed: 0.58 m/s, spray pressure: 0.35 MPa, and spray flow rate: 8.44 L/min). The effect of FAVD on droplet coverage had obvious regularity, and this regularity did not change with the power gradient. At different positions behind canopies, the droplet coverage had great differences. The droplet coverage gradually decreases with increasing horizontal distance and height, while increasing with forward distance. This study provides a reference for the air-assisted sprayers to reduce droplet loss, and data support for subsequent research on precision spraying based on FAVD.

Disease incidence and severity of Cercospora leaf spot in sugar beet assessed by multispectral unmanned aerial images and machine learning.

Disease incidence and metrics of disease severity are relevant parameters for decision making in plant protection and plant breeding. To develop automated and sensor-based routines, a sugar beet variety trial was inoculated with Cercospora beticola and monitored with a multispectral camera system mounted to an unmanned aerial vehicle (UAV) over the vegetation period. A pipeline based on machine learning methods was established for image data analysis and extraction of disease-relevant parameters. Features based on the digital surface model (DSM), vegetation indices, shadow condition and image resolution improved classification performance in comparison to using single multispectral channels in 12% and 6% of diseased and soil regions, respectively. With a post-processing step, area-related parameters were computed after classification. Results of this pipeline also included extraction of disease incidence (DI) and disease severity (DS) from UAV data. The calculated area under disease progress curve (AUDPC) of DS was 2810.4 to 7058.8 %.days for human visual scoring and 1400.5 to 4343.2 %.days for UAV-based scoring. Moreover, a sharper differentiation of varieties compared to visual scoring was observed in area-related parameters, like area of complete foliage (AF), area of healthy foliage (AH) and mean area of CLS lesion by unit of foliage (Ac/F). These advantages provide the option to replace the laborious work of visual disease assessments in the field with a more precise non-destructive assessment via multispectral data acquired by UAV flights.

Design and development of agricultural spraying system

The majority of the sprayer pumps available in the current market are back-mounted, hand pumps that are used to spray pesticides. Although tractor-mounted sprayers are presently available on market are seen to use 10 sets of nozzles to spray the pesticide is very demanding on pesticide consumption leading to pesticide wastage, and subsequent soil and water pollution. This paper focused on the development of an agriculture sprayer with an appropriate pesticide application mechanism that would apply the pesticide directly to the plant foliage, and fruits with minimal wastage thereby making effective pest control and so also reducing pesticide consumption which will aid to reduce spraying cost per acre and more importantly reduce the probability of soil and water pollution. Oscillating Nozzle Agriculture Sprayer is an innovative solution to the above-mentioned problem where four nozzles with oscillating action cover maximum plant foliage area, with effect reach, application of Italian nozzles adds to proper atomization of spray and effective application is attained through the combination of the nozzle and oscillating arm action. The system has been designed, manufactured, and tested in actual conditions. Field test results showed that the cost of spray saved annually is around 25–30% of the pesticide cost for existing tractor-mount spraying mechanisms.

How drought events during the last century have impacted biomass carbon in Amazonian rainforests.

During the last two decades, inventory data show that droughts have reduced biomass carbon sink of the Amazon forest by causing mortality to exceed growth. However, process-based models have struggled to include drought-induced responses of growth and mortality and have not been evaluated against plot data. A process-based model, ORCHIDEE-CAN-NHA, including forest demography with tree cohorts, plant hydraulic architecture and drought-induced tree mortality, was applied over Amazonia rainforests forced by gridded climate fields and rising CO2 from 1901 to 2019. The model reproduced the decelerating signal of net carbon sink and drought sensitivity of aboveground biomass (AGB) growth and mortality observed at forest plots across selected Amazon intact forests for 2005 and 2010. We predicted a larger mortality rate and a more negative sensitivity of the net carbon sink during the 2015/16 El Niño compared with the former droughts. 2015/16 was indeed the most severe drought since 1901 regarding both AGB loss and area experiencing a severe carbon loss. We found that even if climate change did increase mortality, elevated CO2 contributed to balance the biomass mortality, since CO2 -induced stomatal closure reduces transpiration, thus, offsets increased transpiration from CO2 -induced higher foliage area.

Sheep in the Vineyard: Suitability of Different Breeds and Potential Breeding Objectives.

Simple SummaryThere is a large number of sheep breeds worldwide. Today, many of them are endangered, because there are very little market demands for the majority of breeds. The integration of sheep in viticultural systems offers a promising option to put sheep and unique breed characteristics in value. However, it is unknown which characteristics and breeds are best suited for this purpose. The lack of information leads to problems in the implementation of this so-called new integrated crop-livestock system. In our research, we addressed this challenge. We studied 26 breeds and tested their suitability for integration into common vineyards of Central Europe. Two breeds fulfill the most important requirement. Southdown and Shropshire, for the latter especially, the sheep of the shorter legged Danish type seem to be unable to stand on two legs. Their muzzle heights stay within a tolerable range without harming the foliage area of vines. Therefore, adult animals of both breeds seem suitable to take over important viticultural tasks during the growing season. A third breed, the Ouessant sheep, is suitable with some limitations.Protecting a breed of sheep is simple when there is demand for its breed traits, but new market options are often hard to find. In general, grazing sheep are able to take over some viticultural work. Here, we address a new and promising integrated crop-livestock system that involves the integration of sheep in the vineyard during the growing season. Using sheep in a vineyard entails opportunities but also risks, such as the current lack of information, specifically in relation to breed traits. In our survey, we evaluated 26 breeds for their suitability for grazing as long as possible in Central European vineyards during the growing season. First, the breed traits required were identified. Then, 94 flock book breeders were interviewed about specific breed traits. The height of a sheep’s muzzle is particularly important for assessing the suitability of a breed, as it defines the potential impact on the foliage area during the growing season. To determine the height of the muzzle, 179 flock book animals were measured. We found that the most important breeding objective for a new breed of sheep is the inability to stand on two legs. Adult animals of the breed Shropshire, and among these especially the shorter-legged Danish type, and Southdown, show a widespread inability to stand on two legs. Ouessant sheep are able to do so, yet are suitable with some limitations. Due to their extraordinarily small size, their reach is limited, as is their grazing performance. Thus, three of the 26 breeds studied here seem suitable for use in the most widespread vine training systems of Central Europe during the growing season. Targeted breeding could further improve the suitability of sheep for viticulture. Our findings could help to protect breeds and breed traits.

Allometric models for the estimation of foliage area and biomass from stem metrics in black locust

Allometric equations relating trees’ vascular system and other stem metrics with foliage area and mass are important to estimate their growth, carbon stocks and interactions with abiotic environment in terms of carbon and water balance. In this study we focused on Robinia pseudoacacia restoration plantations in Greece and aimed at establishing species-specific models to predict foliage leaf area and biomass based on stem traits. In particular, we evaluated stem cross-sectional areas of sapwood, current sapwood and total stem (sapwood and heartwood), measured at different tree heights, as predictors of leaf area and mass, based on the pipe model theory. Furthermore, we assessed the variation in the ratios of leaf area to different stem cross-sectional areas across the tree profile and we examined the relationships of diameter at breast height (DBH) with diameter at the base of the live crown and with leaf area. Taking into account the trees’ DBH distribution according to the plantations’ inventory, 25 black locust individuals were destructively sampled and the relationships among the studied traits were analyzed by means of multiple and simple linear regression at p<0.001. Foliage dry mass and area were best predicted by total stem cross-sectional area at mid-bole and stump height (R2=0.81), followed by current sapwood area at stump height (R2=0.74), which outperformed the most often used sapwood area (R2=0.70). DBH was also reliably estimating tree leaf area (R2=0.72) but was less precise, compared to total cross-sectional area, while it was a useful proxy of diameter at the base of the live crown (R2=0.80). In line with the pipe model theory, the ratio of leaf area to total cross-sectional area declined across the canopy basipetally, but only when total cross-sectional area was considered. Deviations from the sapwood-foliage functions described by the pipe model theory may be due to the small sample size and the variability in tree size in such developing restoration plantations. The produced species-specific relationships between stem and foliage metrics may be a useful tool to predict the carbon sequestration and climate change adaptation potential of black locust restoration plantations, which are often characterized by harsh site conditions.

Wind field and droplet coverage characteristics of air-assisted sprayer in mango-tree canopies.

Air-assisted sprayers is one of the primary fruit tree pest control approaches in agricultural production. It is necessary to study the influence of multiple factors on both wind field and droplet coverage of air-assisted sprayers. In this article, foliage area volume density (FAVD) and power gradient were considered factors, and field tests were conducted in an orchard to determine such influence. The results showed that in-canopy wind speed was mainly affected by the air-assisted sprayer. FAVD showed significance to the wind speed and droplet coverage inside canopies (P < 0.001), compared with power gradient (P > 0.05). With the increase of FAVD, the wind speed in the bottom layer of canopies first increased and then decreased, while the wind speed in the middle and top layers first decreased and then increased. Meanwhile, the wind field was mainly concentrated on the surface of canopies and gradually approached the canopy center as the power gradient increased. Furthermore, a Back-Propagation (BP) neural network prediction model was constructed to predict droplet coverage at any canopy location to avoid repeated experiments. The overall correlation coefficient (R) of this model was about 0.731, indicating good fitting performance. FAVD has a significant effect on wind speed and droplet deposition inside the canopy, and the air-assisted sprayer parameter setting should consider the effect of FAVD. The prediction model can predict droplet deposition inside the canopy without repeating. The study can provide a reference for selecting operating parameters of air-assisted sprayers and help reduce droplet loss and environmental pollution. © 2022 Society of Chemical Industry.

Elevated ozone phytotoxicity ameliorations in mung bean {Vigna radiata (L.) Wilczek} by foliar nebulization of silicic acid and ascorbic acid.

The present work provides an insight into the development of biochemical adaptations in mung beans against ozone (O3) toxicity. The study aims to explore the O3 stress tolerance potential of mung bean genotypes under exogenous application of growth regulators. The seeds of twelve mung bean genotypes were grown in plastic pots under controlled conditions in the glasshouse. Six treatments, control (ambient ozone level 40-45ppb), ambient O3 with ascorbic acid, ambient ozone with silicic acid, elevated ozone (120ppb), elevated O3 with ascorbic acid (10mM), and elevated ozone with silicic acid (0.1mM) were applied. The O3 fumigation was carried out using an O3 generator. The results revealed that ascorbic acid and silicic acid application decreased the number of plants with foliar O3 injury symptoms in different degrees, i.e., zero, first, second, third, and fourth degrees; whereas 0-4 degree symptoms represent, no symptoms, symptoms occupying < 1/4, 1/4-1/2, 1/2-3/4, and > 3/4 of the total foliage area, respectively. Application of ascorbic acid and silicic acid also prevented the plants from the negative effects of O3 in terms of fresh as well as dry matter production, leaf chlorophyll, carotenoids, soluble proteins and ascorbic acid, proline, and malondialdehyde (MDA) contents. Overall, silicic acid application proved more effective in reducing the negative effects of O3 on mung bean genotypes as compared to that of the ascorbic acid. Three mung bean genotypes (NM 20-21, NM-2006, and NM-2016) were identified to have a better adaptive mechanism for O3 toxicity tolerance and may be good candidates for future variety development programs.

Abundance and Distribution of Foliage on Balsam Fir and White Spruce in Reference to Spruce Budworm Ecology and Absolute Population Density Estimation

We describe the distribution and amount of foliage, expressed as foliated branch surface area, weight, or number of buds in the live crown of healthy open-grown and closed-canopy balsam fir and white spruce trees. Balsam fir and white spruce have very similar total foliage surface area and weight. The live crown of white spruce trees contains fewer buds than balsam fir of similar dimensions. Thus, bud density per unit foliage weight or surface area is higher in balsam fir than in white spruce. We also observed that buds tend to grow in clusters more often on balsam fir than on white spruce, and that larvae of the spruce budworm preferentially attack buds that grow in clusters. Equations were developed to predict the total surface area and weight of foliage as well as number of buds in the live crown for estimation of absolute population density of spruce budworm. These equations use diameter at breast height (DBH) and the number of nodes in the live crown as predictors. When data on the number of live nodes are unavailable, it can be estimated from tree height. Equations were also developed from which to estimate foliage area, weight or bud numbers from DBH only.

Severe declines in hydraulic capacity and associated carbon starvation drive mortality in seawater exposed Sitka-spruce (Picea sitchensis) trees

Sea-level rise is causing widespread tree mortality of coastal forests, with large consequences on the Earth system as a result of these forests’ importance in carbon and nutrient export. The mechanisms of mortality under these conditions are, however, poorly tested. We used wood anatomy traits, wood δ 13C, and tree radial growth to retrospectively assess the physiological process of seawater effects on whole tree xylem hydraulic capacity, gas exchange, and radial growth. During the latter stages of mortality (2018–2019), we directly measured metrics of water use and carbon metabolism across trees having crowns ranging from fully foliated to completely defoliated to investigate mortality processes at the sub-annual scale. Upon seawater exposure, soil salinity increased and allocation to hydraulic function declined, resulting in a dramatic reduction in water supply to the crown, increased crown-level water stress, and subsequent crown foliage loss. Simultaneously, leaf-level photosynthetic capacity declined steeply with increasing salinity. The combined loss of crown foliage area and photosynthetic rates per unit leaf area promoted carbon starvation, while no evidence of hydraulic failure was observed. These results elucidate mechanisms of coastal forest death under seawater exposure, enabling more accurate modeling in the future.

적응형 압축센싱 기반의 드론 SAR 시스템을 이용한 저피탐 은폐 표적물 탐지

Synthetic aperture radar (SAR) uses radio waves to detect targets in all-weather conditions. The latest SAR development enables to operate drone-based SAR systems that can detect low radar cross section (RCS) targets hidden around foliage areas in mountain sides. In drone SAR equipment, low weight constraints limit the battery capacity and pulse sampling rate, leading to image quality degradation. In this study, we attempt to enhance the image quality of power limited drone SAR system by applying compression sensing algorithms. After conducting on-site field experiments, an adaptive target detection process is adopted toward low RCS targets concealed in vegetation areas. It is shown that drone SARs can be used to obtain images of various underground targets or targets hidden under foliage using enhanced compressive sensing algorithms.

Woody and Foliage Biomass, Foliage Traits and Growth Efficiency in Young Trees of Four Broadleaved Tree Species in a Temperate Forest.

The main goal of this study is to analyse and interpret interspecific differences in foliage biomass/area and woody parts biomass as well as the ratio between quantities of foliage and woody components (i.e., branches, stem and roots). The study was principally aimed at determining basic biomass allocation patterns and growth efficiency (GE) of four broadleaved species, specifically common aspen (Populus tremula L.), European hornbeam (Carpinus betulus L.), silver birch (Betula pendula Roth.) and sycamore (Acer pseudoplatanus L.) in young growth stages. We performed whole-tree sampling at 32 sites located in central and northern parts of Slovakia. We sampled over 700 trees and nearly 4900 leaves to quantify biomass of woody parts and foliage traits at leaf and tree levels. Moreover, we estimated specific leaf area in three parts of the crown, i.e., the upper, middle and lower thirds. We found that hornbeam had the largest foliage biomass and the lowest foliage area of all investigated species, while its biomass of woody parts did not differ from aspen and sycamore. Birch had the lowest biomass of woody parts, although its foliage properties were similar to those of aspen. Intraspecific differences of foliage were related to tree size and to leaf position along the vertical crown profile. Growth efficiency (GE), expressed as woody biomass production per foliage area unit, was evidently larger in hornbeam than in the other three broadleaves. We suggest that future GE modelling should utilize real values of stem diameter increment measured in a current year, bio–sociological position of trees and competition indicators as inputs. Such an approach would elucidate the role of stand structure and tree species mixture for ecological and production properties of forest stands.

A bagging tree-based pseudorange correction algorithm for global navigation satellite system positioning in foliage canyons

Global navigation satellite system is indispensable to provide positioning, navigation, and timing information for pedestrians and vehicles in location-based services. However, tree canopies, although considered as valuable city infrastructures in urban areas, adversely degrade the accuracy of global navigation satellite system positioning as they attenuate the satellite signals. This article proposes a bagging tree-based global navigation satellite system pseudorange error prediction algorithm, by considering two variables, including carrier to noise C/ N0 and elevation angle θe to improve the global navigation satellite system positioning accuracy in the foliage area. The positioning accuracy improvement is then obtained by applying the predicted pseudorange error corrections. The experimental results shows that as the stationary character of the geostationary orbit satellites, the improvement of the prediction accuracy of the BeiDou navigation satellite system solution (85.42% in light foliage and 83.99% in heavy foliage) is much higher than that of the global positioning system solution (70.77% in light foliage and 73.61% in heavy foliage). The positioning error values in east, north, and up coordinates are improved by the proposed algorithm, especially a significant decrease in up direction. Moreover, the improvement rate of the three-dimensional root mean square error of positioning accuracy in light foliage area test is 86% for BeiDou navigation satellite system/global positioning system combination solutions, while the corresponding improvement rate is 82% for the heavy foliage area test.

Estimation and counter- validation of LISS-III derived leaf area index in Deltaic vegetation

Leaf area index (LAI), a dimensionless biophysical variable is considered as one of the most important factors in characterizing canopy structure. It estimates the amount of foliage area per unit of ground area and helps indirectly to assess biomass and energy balance in an ecosystem. Remote sensing techniques established a strong correlation between the vegetation reflectance characteristics in red and near infra-red bands and LAI. Good number of image derived vegetation indices has been applied so far to estimate LAI successfully. In this paper correlation is established between field-collected LAI and three soil adjusted vegetation indices, i.e., SAVI, MSAVI and OSAVI derived from IRS-LISS-III data in deltaic ecosystem in Sagar Island of West Bengal, India. LAI was estimated from OSAVI for the whole island as OSAVI yielded best result (R2= 0.92). Coarse resolution MODIS LAI (MOD 15A3) product was counter-validated with respect to the LISS-III derived LAI image following the upscale validation approach. Out of the six best-fit models applied, the logistic regression showed strong positive correspondence between the two products (R2 = 0.71). Uncertainty of the model was also assessed and probable reasons were identified.

Evaluation of the FluorWPS Model and Study of the Parameter Sensitivity for Simulating Solar-Induced Chlorophyll Fluorescence

Solar-induced chlorophyll fluorescence (SIF) has been used as an indicator for the photosynthetic activity of vegetation at regional and global scales. Canopy structure affects the radiative transfer process of SIF within canopy and causes the angular-dependencies of SIF. A common solution for interpreting these effects is the use of physically-based radiative transfer models. As a first step, a comprehensive evaluation of the three-dimensional (3D) radiative transfers is needed using ground truth biological and hyperspectral remote sensing measurements. Due to the complexity of forest modeling, few studies have systematically investigated the effect of canopy structural factors and sun-target-viewing geometry on SIF. In this study, we evaluated the capability of the Fluorescence model with the Weighted Photon Spread method (FluorWPS) to simulate at-sensor radiance and SIF at the top of canopy, and identified the influence of the canopy structural factors and sun-target-viewing geometry on the magnitude and directional response of SIF in deciduous forests. To evaluate the model, a 3D forest scene was first constructed from Goddard’s LiDAR Hyperspectral and Thermal (G-LiHT) LiDAR data. The reliability of the reconstructed scene was confirmed by comparing the calculated leaf area index with the measured ones from the scene, which resulted in a relative error of 3.5%. Then, the performance of FluorWPS was evaluated by comparing the simulated at-sensor radiance spectra with the spectra measured from the DUAL and FLUO spectrometer of HyPlant. The radiance spectra simulated by FluorWPS agreed well with the measured spectra by the two high-performance imaging spectrometers, with a coefficient of determination (R2) of 0.998 and 0.926, respectively. SIF simulated by the FluorWPS model agreed well with the values of the DART model. Furthermore, a sensitivity analysis was conducted to assess the effect of the canopy structural parameters and sun-target-viewing geometry on SIF. The maximum difference of the total SIF can be as large as 45% and 47% at the wavelengths of 685 nm and 740 nm for different foliage area volume densities (FAVDs), and 48% and 46% for fractional vegetation covers (FVCs), respectively. Leaf angle distribution has a markedly influence on the magnitude of SIF, with a ratio of emission part to SIF range from 0.48 to 0.72. SIF from the grass layer under the tree contributed 10%+ more to the top of canopy SIF even for a dense forest canopy (FAVD = 3.5 m−1, FVC = 76%). The red SIF at the wavelength of 685 nm had a similar shape to the far-red SIF at a wavelength of 740 nm but with higher variability in varying illumination conditions. The integration of the FluorWPS model and LiDAR modeling can greatly improve the interpretation of SIF at different scales and angular configurations.

Estimation and counter- validation of LISS-III derived leaf area index in Deltaic vegetation

Leaf area index (LAI), a dimensionless biophysical variable is considered as one of the most important factors in characterizing canopy structure. It estimates the amount of foliage area per unit of ground area and helps indirectly to assess biomass and energy balance in an ecosystem. Remote sensing techniques established a strong correlation between the vegetation reflectance characteristics in red and near infra-red bands and LAI. Good number of image derived vegetation indices has been applied so far to estimate LAI successfully. In this paper correlation is established between field-collected LAI and three soil adjusted vegetation indices, i.e., SAVI, MSAVI and OSAVI derived from IRS-LISS-III data in deltaic ecosystem in Sagar Island of West Bengal, India. LAI was estimated from OSAVI for the whole island as OSAVI yielded best result (R2= 0.92). Coarse resolution MODIS LAI (MOD 15A3) product was counter-validated with respect to the LISS-III derived LAI image following the upscale validation approach. Out of the six best-fit models applied, the logistic regression showed strong positive correspondence between the two products (R2 = 0.71). Uncertainty of the model was also assessed and probable reasons were identified.

Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment

The need for fine scale description of vegetation structure is increasing as Leaf Area Density (LAD, m2/m3) becomes a critical parameter to understand ecosystem functioning and energy and mass fluxes in heterogeneous ecosystems. Terrestrial Laser Scanning (TLS) has shown great potential for retrieving the foliage area at stand, plant or voxel scales. Several sources of measurement errors have been identified and corrected over the past years. However, measurements remain sensitive to several factors, including, 1) voxel size and vegetation structure within voxels, 2) heterogeneity in sampling from TLS instrument (occlusion and shooting pattern), the consequences of which have been seldom analyzed at the scale of forest plots. In the present paper, we aimed at disentangling biases and errors in plot-scale measurements of LAD with TLS in a simulated vegetation scene. Two negative biases were formerly attributed to (i) the unsampled voxels and to (ii) the subgrid vegetation heterogeneity (i.e. clumping effect), and then quantified, thanks to a the simulation experiment providing known LAD references at voxel scale, vegetation manipulations and unbiased point estimators. We used confidence intervals to evaluate voxel-scale measurement accuracy.We found that the unsampled voxel effect (i) led to underestimations with the “mean layer” method –commonly used to fill unsampled voxels- for small voxels (0.1–0.2 m) and/or low number of scans (<4). It was explained by the spatial correlations in vegetation, which induced that dense voxels were more often occluded by dense neighbors than light voxels. The distribution of the bias was heterogeneous in canopy, the bias being stronger at mid canopy where occlusion started, but smaller in highly-occluded upper layers. This somehow counterintuitive result was explained by a more random sampling of upper layers, but could highly depend on vegetation structure.The subgrid vegetation heterogeneity effect (ii) was confirmed to increase with voxel size, yet, the magnitude of this bias -quantified with vegetation manipulation- was found to be more homogeneously-distributed than the unsampled voxel effect.Overall, we found that no scenario was unbiased. However, an intermediate voxel size (0.5 m) was the best option, because the relatively homogeneous subgrid effect could be handled with a single correction factor and voxel-scale measurements errors were reasonable. On the contrary, smaller voxels led to poor voxel-scale measurements and variable biases in magnitude and spatial distribution with sampling design. However, more similar research in other context is required to adapt these conclusions to other forest plots.