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Trees

, Volume 29, Issue 2, pp 355–366 | Cite as

Estimation of foliage clumping from the LAI-2000 Plant Canopy Analyzer: effect of view caps

  • Francesco Chianucci
  • Craig Macfarlane
  • Jan Pisek
  • Andrea Cutini
  • Raffaele Casa
Original Paper

Abstract

Key message

Foliage clumping can be estimated from logarithm averaging method in LAI-2000. The spatial scaling of clumping effects considered by the instrument is dependent on the sensor’s azimuthal view.

Abstract

Accurate estimates of foliage clumping index (Ω) are required to improve the retrieval of leaf area index (L) from optical instruments like LAI-2000/2200 Plant Canopy Analyzer (PCA) and digital hemispherical photography (DHP). The logarithm averaging method is often used to approximate L because clumping effects are considered at scales larger than the sensor’s field of view. However, the spatial scaling considered for logarithm averaging typically differs between PCA and DHP, resulting in different estimates of foliage clumping. Based on simulation, we demonstrated that applying restricting azimuth view caps (e.g., 45° or 10°) allows reliable estimation of Ω and more accurate estimation of L from PCA. Simulated Ω and L values were comparable to those measured using the PCA, DHP and litter traps. Linear averaging of the gap fractions across readings at a plot or site yields a concurrent estimate of effective leaf area index (L e), thus enabling the calculation of L e, L, and Ω from a single instrument fitted with view caps. Users need to be aware that the method they use for averaging gap fractions determines whether they are measuring L e or L, and PCA users need to be aware that they are applying increasingly large corrections for foliage clumping as they use more restrictive view caps, a fact that they can use to their advantage to improve estimates of L.

Keywords

Effective leaf area Hemispherical photography Leaf area index Apparent clumping index Logarithm averaging 

Notes

Author contribution statement

FC and CM: designing the experiment, running the experiment, analyzing the data, writing the paper; JP and RC: analyzing the data and writing the paper. AC: setting up experimental sites.

Acknowledgments

We thank two anonymous reviewers for helping to greatly improve the manuscript with their comments. Jon M. Welles gave constructive comments and kindly provided codes for LAI-2000 outputs calculation. The authors are indebted to Tiit Nilson for fruitful discussions and suggestions that improved the original draft of the paper. The assistance of Tessa Giannini was fundamental during field work. Francesco Chianucci was supported by the research grant “Relationships between stand structure and biodiversity in forest ecosystems—ForBIO”. Craig Macfarlane was partly supported by the Australian Supersite Network, part of the Australian Government’s Terrestrial Ecosystem Research Network (http://www.tern.org.au). Jan Pisek was supported by the Estonian Research Council grant PUT 232.

Conflict of interest

The authors declare that they have no conflict of interest

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Francesco Chianucci
    • 1
  • Craig Macfarlane
    • 2
  • Jan Pisek
    • 3
  • Andrea Cutini
    • 1
  • Raffaele Casa
    • 4
  1. 1.Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Forestry Research CentreArezzoItaly
  2. 2.CSIROWembleyAustralia
  3. 3.Tartu ObservatoryTartumaaEstonia
  4. 4.Department of Agriculture, Forests, Nature and Energy (DAFNE)University of TusciaViterboItaly

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