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Frequently Asked Questions

The biggest advantage of the LAI‑2200C over the LAI-2000 is the ability to use the optical sensor autonomously. The new LAI‑2250 optical sensor can log both above and below readings without the console. This is especially advantageous in tall canopy settings where you need an additional optical sensor to acquire instantaneous A readings to coincide with the B readings. The LAI‑2200C also includes integrated GPS, USB connectivity, increased memory, lighter-weight design, and a new menu driven software.

The LAI‑2200TC Tall Canopy Package gives you two optical sensors and one console. Since the optical sensor can log data autonomously, you can set up automatic logging for your above canopy A readings without the console while obtaining your B readings simultaneously. The files can be merged later to compute LAI and other canopy parameters. The "Tall Canopy Package" is designed to save people money who would otherwise need two LAI‑2200C's to do the work.

Although we use the same optical assembly head, the technology gap between the LAI‑2000 and LAI‑2200C is different enough that the two systems cannot be interchanged.

The LAI‑2200C allows you to measure the LAI from crops, grasslands, forests, hedges, and isolated trees.

The LAI‑2200C measures Gap Fraction at multiple zenith angles with a single, quick measurement. In contrast with ceptometers and linear sensors, there is no need to wait for the sun angle to change or make multiple measurements to acquire this data.

Measurements with the LAI‑2200C will be much quicker than with a line quantum sensor. A typical measurement with the LAI‑2200C takes less than one minute for a short canopy. The line sensor technique relies on direct solar radiation and necessitates waiting for the sun angle to change in order to determine canopy interceptance at several angles. Or, if you assume an extinction coefficient (leaf angle distribution), a line quantum sensor can be used at one angle. The LAI‑2200C looks at 5 angles simultaneously for each measurement.

The sample size when using the line sensor technique is limited, since the sensor only samples the portion of the canopy that lies between the sun and the sensor. With its fisheye field-of-view, the LAI‑2200C can see 360° (with no view cap). Lastly, the LAI‑2200C calculates LAI immediately after the measurement, allowing on-site inspection and verification of the data.

Leaf area is not calculated by viewing all the leaves. Rather, it is calculated from how much radiation is extinguished as it passes through the canopy. Random leaf positioning is assumed, implying a certain amount of leaf overlap. In fact, if a particular canopy had leaves positioned so that no leaf overlap were present, it would cause an error in the LAI‑2200C's computed result, because radiation is extinguished faster than the ideal in this case.

A rough rule of thumb is that plot radius (distance from the sensor location) should be 3 times the plot height. However, in dense canopies less distance may be required, because the sensor may not be able to see that far through the canopy.

View caps can be used to prevent the sensor from seeing in a particular direction, allowing readings to be made near the edge of a plot, and reducing the total plot size necessary. Another remedy for small plots is to do the analysis neglecting the outer ring. The FV2200 software supports this.

There are several considerations when determining if a canopy is too small. First, does the presence of the sensor disturb the canopy? (Are new gaps created when the sensor is pushed in?) Second, the LAI‑2200C assumes the foliage elements are small compared to the area of view of each ring. In general, the distance from the optical sensor to the nearest foliage at an angle of 30° should be at least 4 times the leaf width.

Work by Gower and Norman (1990) indicates that the LAI‑2000/2200C can be successfully used in forest settings. In conifer stands, they found that the LAI‑2000/2200C underestimated LAI by 35-40%, apparently due to the fact that the instrument is sensing projected area of shoots, rather than needles. They further found that a correction factor, which is based solely on shoot morphology and can be independently measured, appears to adequately compensate for this. Their suggested technique is to determine the ratio of projected shoot area to total needle area for the particular species being measured, and then multiply the results by this ratio.

No. It only responds to objects (foliage, etc.) that block the transmission of radiation.

Yes, but measurements should be made in the exact same places each time to remove spatial variability from the results.

Yes, assuming that the plant is isolated enough and that the leaves are small enough.

Yes, when two techniques are used. First, a view cap should be used to mask the portion of the sky that contains the sun. Second, the measurements should be corrected for scattering. While clouds can cause random errors, light scattering represents a systematic error. Fortunately, it can be dealt with by a few extra sky measurements at the time of data collection and some simple post-processing steps in FV2200, version 2.0. Some of the sky measurements for scattering correction require a diffuser cap, included with the LAI‑2200C and the 2200CLEAR upgrade kit for the LAI‑2200. GPS data is also required for scattering correction. This is provided automatically by the built-in global positioning system in the LAI‑2200C or in the LAI‑2200 with the 2200CLEAR upgrade kit.

Not directly. The LAI‑2200C is designed to measure foliage structure, which is only one of several factors determining absorption. Also, the spectral range of the sensor does not correspond to the PAR region, so it should not be used as a PAR sensor. The diffuse non-interceptance value (DIFN) calculated by the LAI‑2200C is a direct estimate of how much diffuse sky radiation gets through the canopy, and (1 - DIFN) would be the absorbed sky radiation; but all this assumes that the foliage does not scatter radiation. Also, this neglects what happens to direct beam radiation, which is a function of solar position. The direct beam absorption could be inferred, perhaps, from the mean gap fraction measurements at the five zenith angles based on diffuse radiation, but this would still neglect the contribution of scattered radiation. Another approach is to model canopy absorption based on the canopy structure (as measured with the LAI‑2200C ), the foliage reflectance and transmittance, the reflectance of the ground, and measurements of incident total PAR and the fraction thereof that is direct beam.

The console of the LAI‑2200C includes two BNC connectors where the LI‑190 Quantum Sensor can be connected for measurement of total incident PAR.

Gap fraction data at different angles potentially hold two types of information: amount of leaf area and leaf orientation distribution. See Perry et al (1988) for a discussion of how much information can be reliably extracted from gap fraction data. The LAI‑2200C calculates MTA as a measure of how the leaves are oriented.

Methods of inverting gap fraction data to get canopy structure have been used for many years. During the development of the LAI‑2000/2200C, there were a number of verification studies, as described in the work by Welles and Norman (1990) and in an application note available from LI-COR. Verification work started in summer 1988 and has continued on since then. A wide variety of canopies were used in the verification research, ranging in size from forests to prairie grass. The LAI‑2000/2200C data was compared to data from other indirect measurement techniques (fisheye photograph analysis, etc.), and to data from canopies which were harvested (100%) and measured with an electronic area meter

Other gap fraction methods of determining canopy structure include point quadrats (Warren Wilson and Reeve 1959), high-contrast fisheye photography (Anderson 1970, Bonhomme and Chartier 1972), traversing a light sensor beneath a canopy (Norman et al 1979, Lang et al 1985, Perry et al 1988), and using a linear light sensor (Walker et al 1988). The LAI‑2200C method is closest to fisheye photography. The LAI‑2200C has the advantage over photography of immediate on-site analysis, but the disadvantage of not having a picture (permanent record) on which to do a number of other types of analyses. The point quadrat technique is only suited to small canopies. The remaining techniques involve using the sun as a canopy probe. The obvious disadvantages are two: the sun must be out, and one must wait for the sun to move to get data at various angles. The LAI‑2200C gets all the angle data at once, and does not require the sun to be out. On the other hand, the LAI‑2200C requires an above canopy reference reading, whereas techniques that use the sun do not. LAI can be deduced from measurements of light attenuation at only one solar angle, using an integrating radiometer (Pierce and Running 1988). However, canopy extinction (that is, leaf angle distribution) must be assumed beforehand, and is not deduced from the measurement. An above canopy reference reading is also required.

No. The complexity of the LAI‑2250, and the unique data reduction software make it very difficult, if not impossible.


  1. Bonhomme, R. and Chartier, P. (1972). The interpretation and automatic measurement of hemispherical photographs to obtain sunlit foliage area and gap frequency. Isr. J. Agric. Res. 22:53-61.
  2. Gower, S.T., and Norman, J.M. (1990). Rapid estimation of leaf area index in forests using the LI-COR LAI‑2000. Ecology, 72(5) 1896-1900.
  3. Lang, A.R.G., Xiang, Y., and Norman, J.M. (1985). Crop structure and the penetration of direct sunlight. Agric. & For. Meteor. (35) 83-101.
  4. Perry, S.G., Fraser, A.B., Thomson, D.W., and Norman, J.M. (1988). Indirect sensing of plant canopy structure with simple radiation measurements. Agric. and For. Meteor. (42) 255-278.
  5. Pierce, L.L. and Running, S.W. 1988. Rapid estimation of coniferous forest leaf area index using a portable integrating radiometer. Ecology 69(6) 1762-1767.
  1. Walker, G.K., Blackshaw, R.E., and Dekker, J. (1988). Leaf area and competition for light between plant species using direct sunlight transmission. Weed Technology (2) 159-165.
  2. Warren Wilson, J., and Reeve, J.E. 1959. Analysis of the spatial distribution of foliage by two-dimensional point quadrats. New Phytol. (58) 92-101.
  3. Welles, J.M. (1990). Some indirect methods of estimating canopy structure. In: Instrumentation for Studying Vegetation Canopy for Remote Sensing in Optical and Thermal Regions. (eds. N.S. Goel and J.M. Norman). Remote Sensing Reviews. 5(1) pp. 31-43.
  4. Welles, J.M. and Norman, J.M. (1990). An instrument for indirect measurement of canopy architecture. Agronomy J., 83:818-825.