Direct and Indirect Estimation of Leaf Area Index, f APAR , and Net Primary Production of Terrestrial Ecosystems

Direct and Indirect Estimation of Leaf Area Index, f APAR , and Net Primary Production of... A primary objective of the Earth Observing System (EOS) is to develop and validate algorithms to estimate leaf area index ( L ), fraction of absorbed photosynthetically active radiation ( f APAR ), and net primary production (NPP) from remotely sensed products. These three products are important because they relate to or are components of the metabolism of the biosphere and can be determined for terrestrial ecosystems from satellite-borne sensors. The importance of these products in the EOS program necessitates the need to use standard methods to obtain accurate ground truth estimates of L , f APAR , and NPP that are correlated to satellite-derived estimates. The objective of this article is to review direct and indirect methods used to estimate L , f APAR , and NPP in terrestrial ecosystems. Direct estimates of L , biomass, and NPP can be obtained by harvesting individual plants, developing allometric equations, and applying these equations to all individuals in the stand. Using non-site-specific allometric equations to estimate L and foliage production can cause large errors because carbon allocation to foliage is influenced by numerous environmental and ecological factors. All of the optical instruments that indirectly estimate L actually estimate “effective” leaf area index ( L E ) and underestimate L when foliage in the canopy is nonrandomly distributed (i.e., clumped). We discuss several methods, ranging from simple to complex in terms of data needs, that can be used to correct estimates of L when foliage is clumped. Direct estimates of above-ground and below-ground net primary production (NPP A and NPP B , respectively) are laborious, expensive and can only be carried out for small plots, yet there is a great need to obtain global estimates of NPP. Process models, driven by remotely sensed input parameters, are useful tools to examine the influence of global change on the metabolism of terrestrial ecosystems, but an incomplete understanding of carbon allocation continues to hamper development of more accurate NPP models. We summarize carbon allocation patterns for major terrestrial biomes and discuss emerging allocation patterns that can be incorporated into global NPP models. One common process model, light use efficiency or epsilon model, uses remotely sensed f APAR , light use efficiency (LUE) and carbon allocation coefficients, and other meteorological data to estimates NPP. Such models require reliable estimates of LUE. We summarize the literature and provide LUE coefficients for the major biomes, being careful to correct for inconsistencies in radiation, dry matter and carbon allocation units. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Remote Sensing of Environment Elsevier

Direct and Indirect Estimation of Leaf Area Index, f APAR , and Net Primary Production of Terrestrial Ecosystems

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Publisher
Elsevier
Copyright
Copyright © 1999 Elsevier Science Inc.
ISSN
0034-4257
DOI
10.1016/S0034-4257(99)00056-5
Publisher site
See Article on Publisher Site

Abstract

A primary objective of the Earth Observing System (EOS) is to develop and validate algorithms to estimate leaf area index ( L ), fraction of absorbed photosynthetically active radiation ( f APAR ), and net primary production (NPP) from remotely sensed products. These three products are important because they relate to or are components of the metabolism of the biosphere and can be determined for terrestrial ecosystems from satellite-borne sensors. The importance of these products in the EOS program necessitates the need to use standard methods to obtain accurate ground truth estimates of L , f APAR , and NPP that are correlated to satellite-derived estimates. The objective of this article is to review direct and indirect methods used to estimate L , f APAR , and NPP in terrestrial ecosystems. Direct estimates of L , biomass, and NPP can be obtained by harvesting individual plants, developing allometric equations, and applying these equations to all individuals in the stand. Using non-site-specific allometric equations to estimate L and foliage production can cause large errors because carbon allocation to foliage is influenced by numerous environmental and ecological factors. All of the optical instruments that indirectly estimate L actually estimate “effective” leaf area index ( L E ) and underestimate L when foliage in the canopy is nonrandomly distributed (i.e., clumped). We discuss several methods, ranging from simple to complex in terms of data needs, that can be used to correct estimates of L when foliage is clumped. Direct estimates of above-ground and below-ground net primary production (NPP A and NPP B , respectively) are laborious, expensive and can only be carried out for small plots, yet there is a great need to obtain global estimates of NPP. Process models, driven by remotely sensed input parameters, are useful tools to examine the influence of global change on the metabolism of terrestrial ecosystems, but an incomplete understanding of carbon allocation continues to hamper development of more accurate NPP models. We summarize carbon allocation patterns for major terrestrial biomes and discuss emerging allocation patterns that can be incorporated into global NPP models. One common process model, light use efficiency or epsilon model, uses remotely sensed f APAR , light use efficiency (LUE) and carbon allocation coefficients, and other meteorological data to estimates NPP. Such models require reliable estimates of LUE. We summarize the literature and provide LUE coefficients for the major biomes, being careful to correct for inconsistencies in radiation, dry matter and carbon allocation units.

Journal

Remote Sensing of EnvironmentElsevier

Published: Oct 1, 1999

References

  • Defining leaf area index for non-flat leaves
    Chen, J.M.; Black, T.A.
  • Factors affecting nutrient acquisition by plants
    Clarkson, D.T.
  • Efficiency of biomass accumulation by sunflower as affected by glucose requirement of biosynthesis and leaf nitrogen content
    Flenet, F.; Kiniry, J.R.
  • Modelling light obstruction in three conifer forests using hemispherical photography and fine tree architecture
    Fournier, R.A.; Landry, R.; August, N.M.; Fedosejevs, G.; Gauthier, R.P.
  • Remote sensing of net primary production in boreal forest stands
    Goetz, S.J.; Prince, S.D.
  • Global net carbon exchange and intra-annual atmospheric CO 2 concentrations predicted by an ecosystem process model and three dimensional atmospheric transport model
    Hunt, E.R.; Piper, S.C.; Nemani, R.; Keeling, C.; Otto, R.D.; Running, S.W.
  • Production efficiency in sunflower
    Joel, G.; Gamon, J.A.; Field, C.B.
  • Characterizing the radiation regime in nonrandom forest canopies
    Kucharik, C.J.; Norman, J.M.; Gower, S.T.
  • Measurements of branch area and adjusting leaf area index indirect measurements
    Kucharik, C.J.; Norman, J.M.; Gower, S.T.
  • Measurements of leaf orientation, light distribution, and sunlit leaf area in a boreal aspen forest
    Kucharik, C.J.; Norman, J.M.; Gower, S.T.
  • A process-based boreal ecosystem productivity simulator using remote sensing inputs
    Liu, J.; Chen, J.M.; Cihlar, J.; Park, W.M.
  • Optical remote sensing of vegetation
    Myneni, R.B.; Maggion, S.; Iaquinta, J.
  • Canopy structure
    Norman, J.M.; Campbell, G.S.
  • Herbivory in forested ecosystems
    Schowalter, T.D.; Hargrove, W.W.; Crossley, D.A.

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