LAI-2000 Instrument Research Articles

Comparison of non-destructive LAI determination methods and optimization of sampling schemes in an open Populus euphratica ecosystem

Populus euphratica (P. euphratica) grows in the water-limited Tarim River Basin in spatially heterogeneous open ecosystems; thus, efforts to quantify the leaf area index (LAI) with optical instruments developed for homogeneous closed canopies have a high probability of failure. In this study, we explored methods for designing an acceptable sampling scheme to quantify the tree LAI for open P. euphratica canopies in arid areas. Field data were collected from three 30m×30m plots and one 100m×100m plot. We compared three indirect methods, i.e. i) allometry, ii) LAI-2000 canopy analyser, iii) Tracing Radiation and Architecture of Canopies (TRAC), and a new semi-direct method combining leaf density and crown volume (SDDV) method for quantifying the isolated tree and canopy LAI of a P. euphratica forest. We also analysed the effects of random and grid sampling designs on the accuracy of the LAI estimates obtained with the LAI-2000. The results showed that the allometric method is applicable to isolated trees with regular shapes; however, because the LAI of P. euphratica was calculated from an allometric equation based on the basal area (at 1.3m), the allometric equation is prone to failure if the basal area is beyond a specific range. Because there are no significant differences in the plot size between the allometric and the SDDV method predictions, the proposed SDDV method can be used as an alternative for field measurements. The combination of LAI-2000 and TRAC is found to be more reliable than TRAC only, and the field view of the LAI-2000 sensor and the clumping index are important factors for sparse vegetation LAI retrieval. The results from sampling optimization showed that for the LAI-2000 instrument, the best sampling method is grid sampling, and the sampling interval should not be less than 20m. For random sampling scheme, the number of sampling points in a 100m×100m plot should be greater than 86 with a coefficients of variation of 15% and an allowable error (AE) of 0.15m2m−2, respectively.

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Forest leaf area index (LAI) is a key characteristic affecting a field canopy microclimate. In addition to traditional professional measuring instruments, smartphone-based methods have been used to measure forest LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To further validate the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that the method with the smartphone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regards to four aspects that can affect LAI: gap fraction; leaf projection ratio; sensor field of view (FOV); and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Mapping tree distribution and LAI in peatlands using field methods and imaging spectroscopy: a case study for the Haaksbergerveen, the Netherlands

Leaf area index (LAI) is among the vegetation parameters that play an important role in climate, hydrological and ecological studies, and is used for assessing growth and expansion of vegetation. The main objective of this study was to develop a methodology to map the LAI distribution of birch trees (Betula pendula) in peatland ecosystems using field-based instruments and airborne-based remote-sensing techniques. The developed mapping method was validated using field-based LAI measurements using the LAI-2000 instrument. First vegetation indices, including simple ratio (SR), normalized difference vegetation index (NDVI), and reduced simple ratio (RSR), were derived from HyMap data and related to ground-based measurements of LAI. LAI related better with RSR (R2 = 0.68), followed by NDVI (R2 = 0.63) and SR (R2 = 0.58), respectively. Areas with birch were identified using Spectral Angle Mapper (SAM) to classify the image into 11 end members of dominant species including bare soil and open water. Next, the relationship between LAI and RSR was applied to areas with birch, yielding a birch LAI map. Comparison of the map of the birch trees and field-based LAI data was done using linear regression, yielding an R2 = 0.38 and an RMSE = 0.25, which is fairly accurate for a structurally highly diverse field situation. The method may prove an invaluable tool to monitor tree encroachment and assess tree LAI in these remote and poorly accessible areas.

Estimating seasonal variations of leaf area index using litterfall collection and optical methods in four mixed evergreen–deciduous forests

Leaf area index (LAI), a critical parameter used in process models for estimating vegetation growth, can be measured through litterfall collection, which is usually referred to as a direct method. This method has been demonstrated to be applicable to deciduous forests, but few studies have used this method for estimating seasonal variations of LAI in mixed evergreen–deciduous forests. In this study, we proposed a practical method to estimate the seasonal variation of LAI directly by combining leaf emergent seasonality and litterfall collection (defined as LAIdir) in a mixed broadleaved-Korean pine (Pinus koraiensis) forest (BK), a Korean pine plantation (KP), a spruce–fir valley forest (SV), and a secondary birch (Betula platyphylla) forest (SB). In this direct method, the seasonal variation of LAI in a mixed forest can be quantified by tracking leaf growth and fall patterns throughout the growing season for each major evergreen and deciduous species. Using the LAIdir as a reference, we validated optical LAI (effective LAI, Le) measurements through a digital hemispherical photography (DHP) and the LAI-2000 instrument. We also explored the contribution of major sources of errors to optical LAI, including woody-to-total area ratio (α), clumping index (ΩE), needle-to-shoot area ratio (γE) and automatic exposure (E). We determined that DHP Le significantly (P<0.05) underestimated LAIdir from May to November by 48–64% in BK, KP and SV but overestimated LAIdir by 7% on average in SB. Similarly, LAI-2000 Le also significantly (P<0.05) underestimated LAIdir by an average of 27–35% in BK, KP and SV but overestimated LAIdir by 22% on average in SB. The relative contribution of E to the error in DHP Le is larger than other factors, and the γE was the largest relative contributor to the underestimation of LAI by LAI-2000. The results from our study demonstrate that seasonal variations of LAI in mixed evergreen–deciduous forests can be optically estimated with high accuracy (85% for DHP and 91% for LAI-2000), as long as accurate corrections are made to the various factors mentioned above. These close agreements between direct and optical LAI results also suggest that the direct method developed in this study is useful for tracking the seasonal variation of LAI in mixed forests.

Simulation of statistical characteristics of gap distribution in forest stands

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 Järvselja, 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.

Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments

At Swiss long-term forest ecosystem research sites, ground vegetation was assessed during the period 1994-2003/2008 following two approaches: (1) visual assessment of the cover of species occurring in sixteen 1 m(2) quadrats, distributed over a 43 × 43 m area, and (2) phytosociological relevés in concentric circular plots of 30, 200, and 500 m(2). We first compared the two approaches with respect to diversity assessment. The number of species recorded in the 16 quadrats was in general higher than in the 30 m(2) plot and it represented 42% to 108% of the number of species recorded in the 500 m(2) plot. In a second step, we tested whether any temporal trends were apparent. In a few cases, a decrease or increase in Landolt's mean indicator values for light, nitrogen availability, soil pH, soil moisture, or temperature was found to be significant. However, these changes were usually restricted to one approach or one area. The only clear trend was detected in an unmanaged former coppice beech stand, for which all survey approaches indicated canopy closure. At another site, vegetation reacted to the local opening of the canopy following windthrow. In a third step, we compared the leaf area index (LAI), measured with an LAI-2000 instrument (Licor, Inc.) over each quadrat, with the indicator value of the vegetation for light (L). Within a site, there was no clear relationship between LAI and L values per quadrat. In contrast, across all sites, the relationship between LAI and L, averaged per site for all available years, was highly significant.

On the correct estimation of effective leaf area index: Does it reveal information on clumping effects?

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.

Biophysical estimation in tropical forests using JERS‐1 VNIR imagery. I: Leaf area index

Leaf area index (LAI) is often used as an indicator of green biomass. In tropical forests it can provide important inputs to ecological and physical models that simulate woody biomass accumulation, water-gas exchanges and carbon sequestration. Commonly accepted ground measurements with the LI-COR LAI-2000 instrument were found very difficult to deploy in mountainous, seasonal tropical forests in northern Thailand. As a result, spatial distribution of LAI cannot be derived from remotely sensed data via empirical regression models. Using hemispherical photography, this study developed a new approach to estimate LAI from remote sensing images. A linear unmixing model in the Modified Soil-Adjusted Vegetation Index (MSAVI) domain was first applied to estimate canopy fractional cover (fc) from the JERS-1 optical images acquired with the Very Near Infrared Radiometer (VNIR) onboard the satellite. Based on hemispherical photographs taken at the study sites, a modified Gaussian regression model was developed to relate LAI to estimated fc, with a squared correlation coefficient (R 2 ) of 0.87. Assuming the 1-m pan-sharpened IKONOS image as ground truth, the VNIR-estimated fc values agreed well with the IKONOS fc in 400 randomly selected locations (R 2 =0.79). The rms errors (RMSE) of the VNIR-estimated fc in different forest types ranged from 13% to 21%. With ground hemispherical photographs taken in the wet season, the RMSE of the LAI-fc model developed in this study was only 0.1 in LAI units, indicating that the LAI-fc regression model could be used in all seasons in the study area.

Using direct and indirect measurements of leaf area index to characterize the shrub canopy in an ombrotrophic peatland

Leaf area index (LAI) is an important ecological parameter that characterizes the interface between a vegetation canopy and the atmosphere. Indirect measurements of LAI using optical techniques such as the LAI-2000 plant canopy analyzer have been routinely conducted for different vegetation canopies including forests and agricultural crops. However, little attention has been paid to shrub canopies of peatlands, where microtopography presents an additional challenge in the optical measurement of shrub LAI. Based on an established equation for boreal forest canopies to derive LAI from “effective” LAI obtained from the LAI-2000 instrument, we evaluated the overall performance of this indirect measurement technique by comparing it with destructive sampling results for the shrub canopy of a precipitation-fed (ombrotrophic) peatland near Ottawa, Ontario, Canada. Under the assumption of no foliage clumping in the shrub canopy, we demonstrate that the contribution of woody canopy elements to light interception has to be taken into account. For this purpose, we determined species-specific woody-to-total area ratios for the five major shrub species. Furthermore, we evaluated the combined effect of microtopographic position of the measurement location and multiple light scattering within the shrub canopy on the measurements. Taking both the contribution of woody canopy elements to light interception and the combined effect of microtopography and multiple light scattering into account, the agreement between direct and indirect measurements of shrub LAI is good ( R 2 = 0.74), and intercept and slope of the linear correlation are not significantly different from 0 ( p = 0.3575) and 1 ( p = 0.7489), respectively. The indirect approach refined through this study provides a reliable method for quick measurements of shrub LAI in ombrotrophic peatlands.

Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning

In a balanced experiment based on 20 field plots located in a 21 km 2 Scots pine forest in southeast Norway covering age classes from newly regenerated to old forest, leaf area index (LAI) was determined in field by a LAI-2000 instrument and hemispheric photography. Based on a formalized framework, i.e., the so-called Beer-Lambert law, gap fraction derived from small-footprint airborne laser scanner data was regressed against field-measured LAI. LAI was strongly ( R 2 = 0.87–0.93), positively, and linearly related to the log-transformed inverse of the gap fraction derived from the laser scanner data. This was as expected according to the Beer-Lambert law, as was the absence of an intercept, producing a directly proportionality of the two variables. We estimated an extinction coefficient for the first return echoes to be 0.7, fortunately fairly stable across age classes, and this is likely to be a parameter specific for the applied laser scanner system under the given flight and system settings, such as flying altitude and laser pulse repetition frequency. It was demonstrated that airborne laser was able to detect defoliation in terms of estimated changes in LAI, by three repeated laser data acquisitions over the area where severe insect attacks were going on in between the acquisitions.

Estimating canopy cover in Scots pine stands

The way canopy cover is defined and measured influences the obtained canopy cover percentage. Estimates of canopy cover are needed, for example, in canopy radiation modelling and remote sensing applications and as a tool for political decision-making. In this paper, we demonstrated the use of two methods, the LAI-2000 Plant Canopy Analyzer instrument and the Cajanus tube, in Scots pine stands for canopy cover estimation, and also assessed the number of measurement points required for reliable estimates. The Cajanus tube yielded slightly larger canopy closure values than the LAI-2000 instrument, but the values were nevertheless in good agreement. Both of the methods required approximately 250 measurement points for canopy closure estimates of a stand to become relatively stable. We also present the first measured effective canopy transmittance values for Scots pine stands in Finland and an example of tree pattern mapping with the Cajanus tube.

Mapping leaf area index through spectral vegetation indices in a subtropical watershed

Leaf area index (LAI) has been associated with vegetation productivity and evapotranspiration in mathematical models. At a regional level LAI can be estimated with enough accuracy through spectral vegetation indices (SVIs), derived from remote sensing imagery. However, there are few studies showing LAI–SVI relationships in subtropical regions. The aim of this work was to examine the relationship between LAI and SVIs in a subtropical rural watershed (in Piracicaba, State of Sa˜o Paulo, Brazil), for different land covers, and to use the best relationship to generate a LAI map for the watershed. LAI was measured with a LAI-2000 instrument in 32 plots on the field in areas of sugar cane, pasture, corn, eucalypt, and riparian forest. The SVIs studied were Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI), calculated from Landsat-7 ETM+ data. The results showed LAI values ranging from 0.47 to 4.48. LAI–SVI relationships were similar for all vegetation types, and the potential model gave the best fit. It was observed that LAI–NDVI correlation (r 2=0.72) was not statistically different from LAI–SR correlation (r 2=0.70). The worst correlation was obtained by LAI–SAVI (r 2=0.56). A map was generated for the study area using the LAI–NDVI relationship. This was the first LAI map for the region.

Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands

Estimation of leaf area index (LAI) using spectral vegetation indices (SVIs) was studied based on data from 683 plots on two Scots pine and Norway spruce dominated sites in Finland. The SVIs studied included the normalised difference vegetation index (NDVI), the simple ratio (SR), and the reduced simple ratio (RSR), and were calculated from Landsat ETM images of the two sites. Regular grids of size 1 km2 with gridpoints placed at 50 m intervals were established at the sites and measurements of LAI using the LAI-2000 instrument were taken at the gridpoints. SVI-LAI relationships were examined at plot scale, where the plots were defined as circular areas of radius 70 m around each gridpoint. Plotwise mean LAI was computed as a weighted average of LAI readings taken around the gridpoints belonging to the plot. Mean LAI for the plots ranged from 0.36 to 3.72 (hemisurface area). All of the studied SVIs showed fair positive correlation with LAI but RSR responded more dynamically to LAI than did SR or NDVI. Especially NDVI showed poor sensitivity to changes in LAI. RSR explained 63% of the variation in LAI when all plots were included (n = 683) and the coefficient of determination rose to 75% when data was restricted to homogeneous plots (n = 381). Maps of estimated LAI using RSR showed good agreement with maps of measured LAI for the two sites.

Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta

Leaf area index (LAI) is an important measure of canopy structure that is related to biomass, carbon and energy exchange, and is an important input to ecological and climate change models. LAI can be estimated using algorithms applied to airborne and satellite imagery, with ground-based measurements of LAI being required for calibration and validation. A variety of methods exist for ground-based and remote estimation of LAI, and this can lead to confusion and uncertainty regarding selection of methods, experimental design, and instrumentation. As a contribution towards clarifying these protocols, this paper investigated and compared three optical methods and an allometric technique for ground-based estimation of LAI, and these were related to remote LAI estimates derived from the compact airborne spectrographic imager (casi) using three vegetation indices (normalized difference, weighted difference, and soil-adjusted vegetation indices, or NDVI, WDVI, and SAVI, respectively) and subpixel-scale spectral mixture analysis (SMA). The study was conducted in the Kananaskis region of Alberta in the Canadian Rocky Mountains and considered four species compositions within a montane ecological subregion: lodgepole pine, white spruce, composite deciduous (aspen and balsam poplar), and mixedwood (mixture of deciduous and lodgepole pine or white spruce). LAI data were obtained in the field using a LI-COR, Inc. LAI-2000 instrument, a tracing radiation and architecture of canopies (TRAC) system, an integrated (LAI-2000 and TRAC) method, and an allometric technique that used the ratio of sapwood basal area to leaf area. A subsample of plots was assessed with hemispherical photographs and LAI-2000 data from which similar effective leaf area index (eLAI) values were derived for two of the four species analyzed. The results highlight the importance of ensuring that samples represent the range of stand structures and canopy architecture inherent in the species group being assessed. Foliage clumping was observed to be similar in both coniferous and deciduous species and an important element to measure. LAI estimates were influenced by the field methods used to estimate LAI, species and their canopy architecture, and the form of the vegetation index or subpixel-scale mixing derived from the casi image. Of the three vegetation indices, the SAVI was the statistically strongest predictor of LAI for mixedwood species, but all were poor LAI estimators for lodgepole pine and deciduous species. The subpixel-scale scene fractions from SMA provided the best prediction of LAI for white spruce compared with the three vegetation indices. The result for white spruce provides an encouraging basis for further investigation of SMA as a sampling tool to scale from field to high-resolution airborne and satellite imagery for local to landscape-level biophysical estimation.

Investigating the use of Landsat thematic mapper data for estimation of forest leaf area index in southern Sweden

The study aims at investigating the use of Landsat thematic mapper (TM) for mapping leaf area index (LAI) in coniferous and deciduous forests in southern Sweden. LAI has been estimated in the field with optical measurements, allometric equations, and litter-trap data, and empirical relationships between LAI estimates and satellite-measured reflectances have been analysed. Several common vegetation indices and multiple regressions where estimated LAI is predicted as a function of various spectral bands are tested. The results indicate significant relationships between Landsat TM reflectances and parameters related to LAI, and the relationships are improved when separating coniferous and deciduous stands. The best relationships occur between Landsat TM data and the product of effective LAI as estimated with the LAI-2000 instrument and a needle clumping factor (LG), which explains about 80% of the variation in coniferous stands and about 50% of the variation in deciduous stands. The best single bands in coniferous stands are the middle-infrared bands (TM5 and TM7), and the best vegetation index is the moisture stress index (TM5/TM4). The best single band in deciduous stands is TM4, and the best vegetation index is the simple ratio (SR).

Irrigation strategy, nitrogen application and fungicide control in winter wheat on a sandy soil. II. Radiation interception and conversion

Data from a three factor experiment carried out during two years were used to analyse the effects of drought, nitrogen and disease on light interception (IPAR) and radiation use efficiency (RUE) in winter wheat (Triticum aestivum L.). The factors in the experiment comprised four irrigation strategies including no irrigation, three nitrogen levels providing 67, 83 and 100% of the recommended nitrogen rate, and two strategies for control of leaf diseases (with and without fungicides). Light interception was estimated from weekly measurements of crop spectral reflectance. This method was compared with estimates derived from crop area index measured by plant samples or by using the LAI2000 instrument. There was a good correspondence between the different methods before anthesis, but an overestimation of light interception with the methods using crop area index after anthesis due to an increase in non-photosynthetic active leaf area. Irrigation increased both IPAR and RUE. The relative increase in IPAR for irrigation was greater than the relative increase in RUE in the first year, whereas they were of similar size in the second year. The differences between the years could be attributed to changes in timing of the drought relative to crop ontogenesis. Increasing nitrogen rate increased IPAR, but caused a small decrease in RUE in both years. This reduction in RUE with increasing nitrogen concentration in leaves was also found to be significant when disease levels and drought effects were included in a multiple linear regression. Fungicide application increased IPAR in both years, but RUE was only significantly reduced by disease in the first year, where mildew dominated the trial. The data were also used to estimate the coefficients of partitioning of dry matter to grains before and after anthesis. About 40% of dry matter produced before anthesis and about 60% after anthesis was estimated to contribute to grain yield. The low fraction after anthesis is probably due to the fact that it was not possible to estimate changes in RUE with time, which may lead to biases in the estimation of partitioning coefficients.

An indirect method of estimating leaf area index in cordon trained spur pruned grapevines

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.