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Leaf area index (LAI) is an important vegetation structure parameter in terrestrial ecosystem modeling. Although the spaceborne Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat) has been proved to have potential for deriving forest LAI, previous methods were only applicable to estimate the effective LAI. In this study, a physical method based on the gap fraction model was proposed to retrieve the LAI correcting the between-crown clumping in discontinuous forest using GLAS full-waveform data. Landsat TM imagery was utilized as auxiliary data for providing crown cover information within the footprint. Using the gap probability from GLAS data and the crown coverage fraction from Landsat imagery, the method corrects the between-crown clumping, which has been proved to contribute most to the total clumping effect, and accurately estimates the LAI in discontinuous forest (R2 = 0.83, RMSE = 0.39, n = 47). Additionally, the forest LAI underestimation caused by between-crown clumping was analyzed in practice and theory. Results show that the between-crown clumping has a nonnegligible influence on forest LAI estimation in cases that the forest area within the footprint is close to the nonforest area, and the average LAI of individual tree is high. This study may shed some light on the development of clumping effect and quantitative LAI inversion models.

Gap fraction (P gap) and vertical gap fraction profile (vertical P gap profile) are important forest structural metrics. Accurate estimation of P gap and vertical P gap profile is therefore critical for many ecological applications, including leaf area index (LAI) mapping, LAI profile estimation and wildlife habitat modelling. Although many studies estimated P gap and vertical P gap profile from airborne LiDAR data, the scan angle was often overlooked and a nadir view assumed. However, the scan angle can be off-nadir and highly variable in the same flight strip or across different flight strips. In this research, the impact of off-nadir scan angle on P gap and vertical P gap profile was evaluated, for several forest types. Airborne LiDAR data from nadir (0°∼7°), small off-nadir (7°∼23°), and large off-nadir (23°∼38°) directions were used to calculate both P gap and vertical P gap profile. Digital hemispherical photographs (DHP) acquired during fieldwork were used as references for validation. Our results show that angular P gap from airborne LiDAR correlates well with angular P gap from DHP (R 2 = 0.74, 0.87, and 0.67 for nadir, small off-nadir and large off-nadir direction). But underestimation of P gap from LiDAR amplifies at large off-nadir scan angle. By comparing P gap and vertical P gap profiles retrieved from different directions, it is shown that scan angle impact on P gap and vertical P gap profile differs amongst different forest types. The difference is likely to be caused by different leaf angle distribution and canopy architecture in these forest types. Statistical results demonstrate that the scan angle impact is more severe for plots with discontinuous or sparse canopies. These include coniferous plots, and deciduous or mixed plots with between-crown gaps. In these discontinuous plots, P gap and vertical P gap profiles are maximum when observed from nadir direction, and then rapidly decrease with increasing scan angle. The results of this research have many important practical implications. First, it is suggested that large off-nadir scan angle of airborne LiDAR should be avoided to ensure a more accurate P gap and LAI estimation. Second, the angular dependence of vertical P gap profiles observed from airborne LiDAR should be accounted for, in order to improve the retrieval of LAI profiles, and other quantitative canopy structural metrics. This is especially necessary when using multi-temporal datasets in discontinuous forest types. Third, the anisotropy of P gap and vertical P gap profile observed by airborne LiDAR, can potentially help to resolve the anisotropic behavior of canopy reflectance, and refine the inversion of biophysical and biochemical properties from passive multispectral or hyperspectral data.

Leaf area index (LAI) is a forest canopy variable that is closely related to forest growth and health. The LAI-2000 Plant Canopy Analyzer is widely used for indirect measurement of LAI; however, use of the instrument is limited to diffuse sky conditions, greatly restricting sampling. A new bidirectional transmission model allows measurements to be obtained under clear sky conditions. This is accomplished by calculating a correction factor to reduce the impact of scattered light from canopy elements on gap fraction estimates. In this study we evaluate this technique by contrasting LAI measurements taken under diffuse and clear skies in a Pinus radiata D. Don plantation. We also evaluate the importance of obtaining accurate needle optical properties to parameterise the scattering correction model. Clear sky LAI estimates calculated with (a) measured optical values of P. radiata needles, (b) default values from the instrument software, and (c) maximum published values were compared to diffuse sky LAI estimates. Agreement was strongest where measured optical properties were used ( R 2 = 0.87), with the relationship weakening under the default ( R 2 = 0.78), and maximum value ( R 2 = 0.67) scenarios. Under these three scenarios average clear sky LAI exceeded diffuse sky LAI by 16%, 17%, and 22%, respectively. The disagreement was due in part to erroneous measurements from the outer sensor ring under diffuse skies. With these data removed agreement improved markedly under all scenarios ( R 2 = 0.94, 0.89, and 0.75, respectively), and the mean differences under each scenario declined to 8%, 9%, and 15%, respectively. Measurement of LAI under clear skies appeared to reduce error in the outer ring, greatly reduced logistical constraints, and reduced errors associated with sky variability.

a b s t r a c t Estimates of the canopy gap fraction, on which calculations of leaf area index (LAI) are based, are sensi- tive to photographic exposure in upward-facing images. In this article we describe a simple, automated method of image acquisition and processing that eliminates both subjectivity and the need for the oper- ator to consider photographic exposure in the field. A key strength of our methodology was the use of a test apparatus (perforated aluminum screen) with a precisely known gap fraction; this allowed us to separate the confounding effects of gap size and gap fraction on the optimal photographic exposure for a canopy. We took photographs of the test apparatus at different photographic exposures; we varied the gap fraction by covering a proportion of the holes in the screen, and also varied gap size by varying the distance of the camera from the screen. We acquired both raw images and JPEG images. We found that the optimal exposure of JPEG images varied with both gap size and gap fraction, not just gap fraction as previously assumed. Underexposing by one stop yielded raw data that were never clipped resulting in data loss, but that used most of the 14-bit range of the raw file. We also found that it was easily possible to standardize photographic exposure during image processing by acquiring raw images in the field; thus eliminating the variation in estimated gap fraction and LAI associated with exposure variations. This result was replicated in both fisheye images and cover images that we acquired in real canopies. We recommend the following protocol for acquiring canopy images in future studies

Recently, Armston et al. (2013) have demonstrated that a new, physically-based method for direct retrieval of canopy gap probability Pgap from waveform lidar can improve the estimation of Pgap over discrete return lidar data. The success of the approach was demonstrated in a savanna woodland environment in Australia. The huge advantage of this method is that it uses the data themselves to solve for the canopy contrast term i.e. the ratio of the reflectance from crown and ground, ρv/ρg. In this way the method avoids local calibration that is typically required to overcome differences in either ρv or ρg. To be more generally useful the method must be demonstrated on different sites and in the presence of slope and different sensor and survey configurations. If it is robust to these things, slope in particular, then we would suggest it is likely to be widely useful. Here, we test the robustness of the retrieval of Pgap from waveform lidar using the Watershed Allied Telemetry Experimental Research dataset, over the Heihe River Basin region of China. The data contain significant canopy, terrain and survey variations, presenting a rather different set of conditions to those previously used. Results show that ρv/ρg is seen to be stable across all flights and for all levels of spatial aggregation. This strongly supports the robustness of the new Pgap retrieval method, which assumes that this relationship is stable. A comparison between Pgap estimated from hemiphotos and from the waveform lidar showed agreement with Pearson correlation coefficient R=0.91. The waveform lidar-derived estimates of Pgap agreed to within 8% of values derived from hemiphotos, with a bias of 0.17%. The new waveform model was shown to be stable across different off-nadir scan angles and in the presence of slopes up to 26° with R≥0.85 in all cases. We also show that the waveform model can be used to calculate Pgap using just the mean value of canopy returns, assuming that their distribution is unimodal. Lastly, we show that the method can also be applied to discrete return lidar data, albeit with slightly lower accuracy and higher bias, allowing Pgap comparisons with previously-collected lidar datasets. Our results show the new method should be applicable for estimating Pgap robustly across large areas, and from lidar data collected at different times and using different systems; an increasingly important requirement.

The increasing availability of high-quality sensors and computational power on low-cost mobile devices like smartphones and tablets is opening new possibilities for adopting this kind of technology for monitoring biophysical processes of interest for agronomic and environmental studies. A method for leaf area index (LAI) estimates based on gap fraction, derived from the segmentation of images acquired at 57° below the canopy, was recently proposed and implemented in the smartphone app PocketLAI ® , and successfully tested against commercial devices for paddy rice. In this study, PocketLAI was tested against the AccuPAR ceptometer on canopy structures (maize, row-seeded giant reed and natural grassland) that strongly deviate from the ideal assumption behind the simplified model for light transmittance into the canopy used in the app (i.e., random distribution of infinitely small leaves). The comparison between PocketLAI and AccuPAR showed overall good performances for the app, with root mean square error of 0.41, 0.49 and 0.96 m 2 m −2 for grassland, maize and giant reed respectively, and R 2 of 0.86, 0.92 and 0.88. A saturation effect was observed for PocketLAI for LAI values higher than 5 m 2 m −2 especially for giant reed, with the LAI values obtained with the app markedly underestimating those provided by AccuPAR. Although further studies are needed to better investigate the need for calibrating the app in case of low-quality devices, these results confirm the possible role of PocketLAI in providing a suitable alternative to the commercial tools available for indirect LAI estimates in contexts characterized by few economic resources or when a high portability is needed.

The dimensionless leaf area index (LAI) is a fundamental crop characteristic. Since the direct measurement of LAI or leaf area is labour intensive and destructive, fast and reliable indirect methods have been devised to estimate LAI of different crops. The objective of this work was to test indirect methods for the non-destructive estimation of LAI in kohlrabi ( Brassica oleracea var. gongylodes L.) and lettuce ( Lactuca sativa var. capitata L.). Focusing on the gap fraction methodology, digital photographs and simultaneous radiation interception measurements were taken using a Li-Cor plant canopy analyser (LAI-2200) on 12 sampling dates from planting to harvest, with concurrent destructive estimations of the leaf area. Several geometric protocols of the LAI-2200 and inversion algorithms of the accompanying software were evaluated. Very good indirect-direct LAI relationships were obtained for kohlrabi ( R 2 > 0.97, n = 12) and lettuce ( R 2 > 0.99, n = 9) for the most suitable protocols and algorithms.

This study evaluated the performance of digital photography for measuring the green leaf area index (LAI) and green plant area index (GAI) of field crops by quantifying gap fraction either at nadir or at a 57.5° view angle. Clumping index was estimated using the logarithmic averaging method of Lang and Xiang (1986) to derive the total GAI. Measurement uncertainty associated with foliage inclination and view angles was assessed analytically, as was image classification. The GAI derived for corn, soybean and wheat crops was strongly linearly correlated with the destructive GAI for both the nadir and the 57.5° photographic methods (R2 > 0.83, root mean square error < 0.63). Because the destructive LAI and GAI exhibited strong linear correlations for soybean and corn, LAI could be predicted from photographic methods. The LAI and GAI of the wheat canopy were poorly correlated because of a significant proportion of non-leaf tissues contributing to photosynthesis after the start of stem elongation. Clumping had a greater effect on the nadir photographic method than on the 57.5° method. The effective GAI from nadir viewing was better correlated to the destructive GAI than the photographic GAI, whereas the effective GAI from the 57.5° photographic method provided a greater underestimation of the destructive GAI than the photographic GAI. The extinction coefficient at nadir viewing was found to be 22% larger than the assumed value (i.e. k = 0.61 vs. the theoretical value of 0.5). When gap reduction reached the asymptotic saturation level with increasing LAI, higher classification accuracy was required to achieve acceptable LAI measurement accuracy. The 57.5° photographic method was more affected by classification accuracy when LAI was higher than 1.5. With crop canopy development, the decrease in gap size and the decline in signal strength from shadows mean that high-quality photos are required to effectively differentiate gaps from plant tissues.

Angular distribution of leaves is an important parameter determining the transmission and reflection of radiation by vegetation canopies. When inverting canopy transmittance measurements for estimating the leaf area index or canopy clumping, incorrect assumptions on leaf angles may lead to considerable errors. To address this issue, we measured an extensive data set of leaf angle distributions for 58 deciduous broadleaf tree species commonly found in temperate and boreal ecoclimatic regions. Additionally, a small subset of species was sampled several times during the growing season. We found that reliable estimates of leaf angle distributions at the level of a whole tree can be obtained by measuring the leaf inclination angles of 75 leaves distributed across the vertical tree profile using a simple technique based on digital photography. According to our measurements, the common assumption of a spherical leaf angle distribution often used when no measurement data is available is not a valid assumption for most of the studied tree species. Our multitemporal measurements indicated no seasonality of leaf inclination angles of the selected tree species, except directly after budburst. Finally, using a gap fraction model, we illustrate the influence of different leaf angle distributions on the clumping factor and leaf area index. We advocate the use of species-specific leaf angle distributions from actual leaf inclination measurements. However, a planophile or a plagiophile leaf angle distribution appears to be a more appropriate assumption than a spherical one for modeling radiation transmission through temperate and boreal broadleaf stands when no leaf inclination angle measurements are available.

article i nfo The Echidna Validation Instrument (EVI), a ground-based, near-infrared (1064 nm) scanning lidar, provides gap fraction measurements, element clumping index measurements, effective leaf area index (LAIe) and leaf area index (LAI) measurements that are statistically similar to those from hemispherical photos. In this re- search, a new method integrating the range dimension is presented for retrieving element clumping index using a unique series of images of gap probability (Pgap) with range from EVI. From these images, we iden- tified connected gap components and found the approximate physical, rather than angular, size of connected gap component. We conducted trials at 30 plots within six conifer stands of varying height and stocking den- sities in the Sierra National Forest, CA, in August 2008. The element clumping index measurements retrieved from EVI Pgap image series for the hinge angle region are highly consistent (R 2 =0.866) with those of hemi

The “damage accumulation” phenomenon has not been quantitatively demonstrated in clinical cement mantles surrounding femoral hip stems. We stained transverse sections of 11 postmortem retrieved femoral hip components fixed with cement using fluorescent dye-penetrant and quantified cement damage, voids, and cement-bone interface gaps in epifluorescence and white light micrographs. Crack density (Cr.Dn), crack length-density (Cr.Ln.Dn), porosity, and cement-bone interface gap fraction (c/b-gap%) were calculated, normalized by mantle area. Multiple regression tests showed that cement damage (Cr.Ln.Dn. & Cr.Dn.) was significantly positively correlated (r2=0.98, p

An estimate of the required amount of LAI-2000 or digital hemispheric image measurements to ensure the desired accuracy of the leaf area index value derived from optical analyser measurements by inversion of gap fraction data is given. The estimate is based on a theoretical model of the second order statistics of gap occurrence in forest canopies. The main attention is paid to gap fractions averaged over the angular rings similar to the LAI-2000 instrument. Nilson's (1999) forest gap fraction model is first extended to simulate the bidirectional gap fraction and next the approximate equations for the standard deviation of gap fraction, correlation matrix of gap readings in different LAI-2000 angular rings, standard deviation of the LAI value as determined by the inversion of gap fraction data are derived. The results of simulation are compared with those obtained by LAI-2000 instrument and digital hemispheric photographs in three mature forests from Jarvselja, Estonia. The comparison shows an acceptable agreement between the simulated and measured second order statistical characteristics. The distance from the observation height to the crowns and crown dimensions appear to be important in determining the magnitude of variance. When the LAI-2000 instrument is used together with a view-cap, the angular size of the view-cap has an effect on the second order statistics and on the value of apparent clumping index. A computer program has been written to calculate the second-order gap statistics.

Effective leaf area index is routinely quantified with optical instruments that measure gap fraction through the probability of beam penetration of sunlight through the vegetation. However, there have been few efforts to obtain theoretically consistent effective leaf area indices from those measurements. To apply the Beer–Lambert law, multiple gap fraction measurements may be averaged in two ways: (1) by taking the mean of the logarithms of the individual gap fraction values or (2) by taking the logarithm of the mean gap fraction. Based on a theoretical model and gap fraction measurements from 41 sites, we report that effective leaf area index must be quantified using the second approach. The first approach implemented in the LAI-2000 instrument considers clumping effects at scales larger than shoots. Thus, the combination of the first approach with an independent clumping index overestimates leaf area index up to 30% at the investigated sites. Clumping effects accounted for by the LAI-2000 instrument, called the “apparent” clumping index, were dependent on canopy cover, crown shape, and canopy height. A forest gap fraction model showed that short canopy height, vertically prolonged crown shape and higher canopy cover are associated with the lowest apparent clumping indices. We show that the apparent clumping index is a useful quantity to constrain the true clumping index and to investigate spatial and temporal variation of clumping effects. Such information would be useful to evaluate a coarse global clumping index map and improve land surface models.

The slope effect and correction methods for estimation of canopy gap fraction, leaf area index (LAI), mean leaf angle and clumping index using hemispherical photography, were investigated. The evaluation was carried out in tropical cloud forest and plantations in South-East Kenya in order to consider a range of canopy architecture and slopes up to 65%. The aim was to compare two acquisition techniques and various correction procedures. All estimates assume uniform slope, canopy parallel to ground and homogeneous canopy structure at the photo site level.

The concept of recollision probability originates from the theory of canopy spectral invariants (‘p-theory’) but is a simplification that involves several heuristic assumptions. Nonetheless, the concept has been shown to be a useful tool for incorporating the effects of 3D structure on canopy absorptive and reflective properties in forest reflectance models. A method is presented by which an average value of the canopy recollision probability (pˆ) can be calculated from canopy gap fraction data, which are provided for example by the LAI-2000 plant canopy analyzer or can be extracted from fisheye photographs. The new method was used to calculate the average recollision probabilities (pˆ values) of uniform leaf and shoot canopies, showing good agreement with results from Monte Carlo simulations. Strengths of the method presented here are the explicitly formulated relationship between recollision probability and canopy structure, and its direct applicability in canopy RT studies.

A correct exposure is of crucial importance for accurate retrieval of canopy parameters using hemispherical photograph techniques. Digital hemispherical photographs were collected under different sky brightness conditions using a Nikon CoolPix 4500 camera with an FC-E8 fish-eye lens for canopies of different species and openness. Different exposure schemes were employedto investigatethe effects ofphotographic exposure ontheestimations ofthe effective leaf area index(Le)and gap fraction. The contrast between the sky and foliage under each exposure scheme was calculated to determine the correct exposure under different weather conditions. The results demonstrated that digital hemispherical photographs taken with automatic exposure are not reliable, causing Le underestimations by 16‐71% for medium and high density canopies (Le = 3.2‐4.8) and corresponding gap fraction overestimations by 18‐72%. While for open canopies with Le < 1.26, Le was overestimated by 11‐29%, and the corresponding gap fraction was underestimated by 4‐28%. Studies showed that increasing one stop of exposure results in 3‐28% differences inLe for canopies with different openness. Based on the analysis, we determined the optimum exposure and developed a protocol for acquiring digital hemispherical photographs. The protocol requires first measuring reference exposure for the open sky using a built-in camera light meter, and then take photographs inside the canopy using the same camera with two stops of more exposure than the reference exposure in order to make the sky appear white and consequently also maximize the contrast between theskyandfoliage.Thisprotocol isapplicablefordifferentskybrightnessandfordifferentcanopyopenness.Indensecanopies,this procedure requires much less exposure than automatic exposure, but in very open canopies, this procedure requires more exposure than automatic exposure. Using the exposure determined with this procedure rather than the automatic exposure, the comparison of Le values from the LAI-2000 and digital photographs is greatly improved, with R 2 increasing from 0.77 to 0.95, and RMSE

Thresholding is a central part of the analysis of hemispherical images in terms of gap fraction and leaf area index (LAI), and the selection of optimal thresholds has remained a challenge over decades. The need for an objective, automatic, operatorindependent thresholding method has long been of interest to scientists using hemispherical photography. This manuscript deals with the comparison of a wide variety of different well-known automatic thresholding techniques against the subjective manual method, using high-dynamic range digital hemispherical photographs. The performance of the different thresholding methods was evaluated based on: (1) visual inspection by means of a multi-criteria decision system and (2) quantitative analysis of the methods’ sensitivity to an overall performance criterium. The automatic Ridler clustering method proved to be the most robust thresholding method for various canopy structure conditions. This automatic method might be the best solution for a fast, reliable and objective use of hemispherical photographs for gap fraction and LAI estimation in forest stands, given that the threshold setting is no longer manually performed. The fine-tuning potential of local thresholding methods to better address particular photographic limitations (e.g. over-exposure in a certain image region) is also presented. # 2005 Elsevier B.V. All rights reserved.

The leaf area index (LAI), was estimated in deciduous forests of southern Sweden using different estimation techniques. The effective LAI (L-e) was estimated optically by measurements with the gap fraction instrument LAI-2000 and corrections for the aggregation of leaves were achieved by using the TRAC (Tracing Radiation and Architecture of Canopies) instrument. Two methods for correcting the contribution of the woody material were tested. The aim was to find the most reliable estimation technique, and therefore the measurements were compared with LAI estimated from litter fall collection. Optically estimated L-e was correlated with litter trap LAI, indicating that L-e can be used as an estimate of LAI in deciduous forests of the same characteristics as tested here. The litter fall collection technique involves knowledge about the specific leaf area (SLA). Since, we found that SLA varied between leaves picked from top positioned branches and leaves picked from low positioned branches as well as between different species, we suggest some caution when interpreting the values. (Less)

The theoretical background of modeling the gap fraction and the leaf inclination distribution is presented and the different techniques used to derive leaf area index (LAI) and leaf inclination angle from gap fraction measurements are reviewed. Their associated assumptions and limitations are discussed, i.e., the clumping effect and the distinction between green and non-green elements within the canopy. Based on LAI measurements in various canopies (various crops and forests), sampling strategy is also discussed.

We investigated ground and canopy damage and recovery following conventional logging and reduced-impact logging (RIL) of moist tropical forest in the eastern Amazon of Brazil. Paired conventional and RIL blocks were selectively logged with a harvest intensity of approximately 23 m 3 ha −1 (geometric volume) in the dry seasons (July–December) of 1996 and 1998. Ground damage (roads+skid trails+log decks) in the conventional logging treatments occupied 8.9–11.2% of total operational area. In contrast, ground damage in RIL treatments ranged from 4.6 to 4.8% of the total area. Forest canopy damage was assessed using gap fraction measurements collected with an automated optical canopy analyzer (LAI-2000; Licor Inc.) in March 1999. Canopy opening varied by time since logging. The recently logged (1998) blocks had integrated canopy gap fractions of 21.6 and 10.9% of total area for conventional and RIL blocks, respectively. The blocks logged in 1996 had more closed canopies with 16.5 and 4.9% gap fraction for conventional and RIL blocks, respectively. For comparison, undisturbed forest had a canopy gap fraction of 3.1%. Measurements of ground disturbance and gap fraction using the Licor LAI-2000 generally agree with other field evaluations of RIL and conventional logging. Detailed understanding of canopy structural changes resulting from different logging intensities are critical to the prospect of logging damage estimation using current and future remote sensing products.

Hemispherical photographs were taken in a range of Sitka spruce ( Picea sitchensis (Bong.) Carr.) stands in northern Britain. These were used to estimate the canopy gap fraction, and thereby estimate the transmission of light to the ground within each stand. Stands under routine management systems, whether thinned or unthinned, generally had too low a gap fraction to allow sufficient light through for seedling growth. The only stand with a gap fraction substantially higher than the others was a widely spaced (8 m) stand from a spacing experiment. The observations showed good agreement with a theoretical curve of canopy transmittance calculated using the Beer–Lambert law. The results indicate that a Sitka spruce stand should be thinned to a basal area 2 ha −1 , which is below management table stocking, if the gap fraction is to be increased to levels suitable for seedling growth.

Based on inversion of gap fraction data (Poisson model of foliage distribution), three optical methods using the Demon, the Plant Canopy Analyzer LAI-2000 (PCA) and hemispherical photographs, have been compared to estimate canopy openness (CO) and leaf area index (LAI) in a mature, neutrophil, oak-beech-hornbeam forest on mull in eastern France. Mean CO over the whole hemisphere was similar for PCA (7.9 %) and hemispherical photographs (8.0 %). The needle method, a vertical point quadrat method, applied to the litter after leaf fall has served as a reference to LAI (4.7). The Demon provided the estimate (4.9) closest to the reference value. The PCA and hemispherical photographs underestimate mean LAI by 30 % (3.3) and 19 % (3.8), respectively, if used without correction. Based on fish-eye sensors, LAI estimates can be improved if 3 annuli (4.2) or 2 annuli (4.5) are used in place of 5 with the PCA, or by means of logarithmic averaging of gap fractions over azimuth at an appropriate angular resolution (180°: 4.6, or 120°: 5.2) with hemispherical photographs. Not taking into account azimuthal variation in gap fraction distribution generates a more important error than the error induced by light scattering near horizon. In order to improve LAI estimates, an original iterative procedure is presented, which allows the simultaneous calculation of LAI over a broad range of angular azimuthal resolutions.

Gaps are unavoidable when compositing small or narrow plant parts (e.g., conifer needles, twigs, narrow leaves, and leaflets) on sample holders in preparation for measuring spectral optical properties. The Daughtry et al. (1989) (A new technique to measure the spectral properties of conifer needles. Remote Sens. Environ. 27:81–91.) method of measuring conifer needle optical properties utilizes a relatively large gap fraction (approximately 0.3–0.6) and needles painted black on one surface of the sample from which the gap fraction of the sample is indirectly determined. Following this protocol typically results in distortions in optical properties, including underestimates in transmittance (sometimes negative values), and only one surface of the sample can be measured. The objectives of this article are to: 1) evaluate the influence of gaps between sample elements (conifer needles, twigs, narrow leaves and leaflets) on optical properties calculated with the published equations from Daughtry et al. (1989) and 2) revise the original Daughtry et al. method for optical property measurements by using an image-analysis to directly measure the gap fraction and use both surfaces of the sample. We achieve these objectives by reviewing the theory and investigating the effects of gaps by measurements of an inert photographic film material, fir needles, and mesquite leaflets. Tests to estimate the transmittance of film samples (film) and foliage (fir needles, mesquite leaflets) indicate that a relatively small gap fraction (less than 0.20) reduces the occurrence of computed negative transmittance values, reduces the variation in computed values, and yields values expected for the “true” or “nongap” transmittance. Employing the image analysis along with reduced gap fractions decreased the variance of measurements and permitted measurements of both surfaces per sample, thus reducing the time required by making half as many samples as originally required by Daughtry et al.

The aim of this study was to validate an indirect method of estimating leaf area index (LAI) in cordon-trained spur-pruned grapevines. Indirect estimates were made using the LAI-2000 instrument, based on the principles of gap fraction theory. Results indicate that using an adjustment coefficient factor, this method could provide rapid and accurate estimates of LAI.

We compared leaf area index (LAI) estimates of a broad-leaf tropical hardwood, Metrosideros polymorpha Gaud (‘Ōhi’a), using a optical method (LI-COR LAI-2000) and direct determination (harvest and allometry). There was a strong correlation between LAI estimates by the two methods, but direct estimates were higher than the optical estimates by a factor of 2.44. The ratio of harvest leaf area to projected leaf area within twigs was similar (2.42) to that of whole plots, suggesting that aggregation of leaves at this scale of branching may account for most of the underestimate by the optical method. The within-branch ratio of actual to projected leaf area did not differ among three sites on three islands of varying land surface age but similar climate, suggesting that a correction factor determined by harvest could be used to adjust optical estimates of LAI in other M. polymorpha forests.

We estimated leaf area index (LAI) in a needle-leaved forest and a broad-leaved orchard using four instruments which measure fractional light penetration through the canopy. Gap fraction data were analyzed by a one-dimensional inversion model or by using the Beer-Lambert Law. Instrument and analytical technique both had a strong influence on calculated LAI. There was no consistent pattern of LAI results among instruments so no simple cross-calibration can be offered. Three of the four instruments accurately estimated orchard LAI when used with one or the other analytical technique. In addition to performance, practical considerations including cost, sampling, and data analysis were also compared among the instruments. Because the instruments do not provide consistently accurate LAI estimates, LAI should be independently corroborated before use in any particular situation. These instruments may be most useful for relative LAI comparisons in a specific canopy type when a single combination of instrument and analytical technique is employed.

A Poisson model is developed to describe sunfleck or gap size distributions beneath clumped plant canopies. This model is based on the assumption that foliage clumps are randomly distributed in space and foliage elements are randomly distributed within each clump. Using this model, the foliage clumping index, leaf area index ( L ), clump area index, element area index in each clump, and element and clump widths were successfully derived for two artificial canopies and a thinned and pruned Douglas-fir forest stand. It is shown that existing theories for deriving L from measurements of canopy gap fraction have limitations, and the use of canopy architectural information derived from canopy gap size distribution can substantially improve the technique for indirectly measuring L of plant canopies.