TY - JOUR
T1 - Spectral and chemical analysis of tropical forests
T2 - Scaling from leaf to canopy levels
AU - Asner, Gregory P.
AU - Martin, Roberta E.
N1 - Funding Information:
This work was supported by the John D. and Catherine T. MacArthur Foundation and the Carnegie Institution.
PY - 2008/10/15
Y1 - 2008/10/15
N2 - Variation in the foliar chemistry of humid tropical forests is poorly understood, and airborne imaging spectroscopy could provide useful information at leaf and canopy scales. However, variation in canopy structure affects our ability to estimate foliar properties from airborne spectrometer data, yet these structural affects remain poorly quantified. Using leaf spectral (400-2500 nm) and chemical data collected from 162 Australian tropical forest species, along with partial least squares (PLS) analysis and canopy radiative transfer modeling, we determined the strength of the relationship between canopy reflectance and foliar properties under conditions of varying canopy structure. At the leaf level, chlorophylls, carotenoids and specific leaf area (SLA) were highly correlated with leaf spectral reflectance (r = 0.90-0.91). Foliar nutrients and water were also well represented by the leaf spectra (r = 0.79-0.85). When the leaf spectra were incorporated into the canopy radiative transfer simulations with an idealistic leaf area index (LAI) = 5.0, correlations between canopy reflectance spectra and leaf properties increased in strength by 4-18%. The effects of random LAI (= 3.0-6.5) variation on the retrieval of leaf properties remained minimal, particularly for pigments and SLA (r = 0.92-0.93). In contrast, correlations between leaf nitrogen (N) and canopy reflectance estimates decreased from r = 0.87 at constant LAI = 5 to r = 0.65 with randomly varying LAI = 3.0-6.5. Progressive increases in the structural variability among simulated tree crowns had relatively little effect on pigment, SLA and water predictions. However, N and phosphorus (P) were more sensitive to canopy structural variability. Our modeling results suggest that multiple leaf chemicals and SLA can be estimated from leaf and canopy reflectance spectroscopy, and that the high-LAI canopies found in tropical forests enhance the signal via multiple scattering. Finally, the two factors we found to most negatively impact leaf chemical predictions from canopy reflectance were variation in LAI and viewing geometry, which can be managed with new airborne technologies and analytical methods.
AB - Variation in the foliar chemistry of humid tropical forests is poorly understood, and airborne imaging spectroscopy could provide useful information at leaf and canopy scales. However, variation in canopy structure affects our ability to estimate foliar properties from airborne spectrometer data, yet these structural affects remain poorly quantified. Using leaf spectral (400-2500 nm) and chemical data collected from 162 Australian tropical forest species, along with partial least squares (PLS) analysis and canopy radiative transfer modeling, we determined the strength of the relationship between canopy reflectance and foliar properties under conditions of varying canopy structure. At the leaf level, chlorophylls, carotenoids and specific leaf area (SLA) were highly correlated with leaf spectral reflectance (r = 0.90-0.91). Foliar nutrients and water were also well represented by the leaf spectra (r = 0.79-0.85). When the leaf spectra were incorporated into the canopy radiative transfer simulations with an idealistic leaf area index (LAI) = 5.0, correlations between canopy reflectance spectra and leaf properties increased in strength by 4-18%. The effects of random LAI (= 3.0-6.5) variation on the retrieval of leaf properties remained minimal, particularly for pigments and SLA (r = 0.92-0.93). In contrast, correlations between leaf nitrogen (N) and canopy reflectance estimates decreased from r = 0.87 at constant LAI = 5 to r = 0.65 with randomly varying LAI = 3.0-6.5. Progressive increases in the structural variability among simulated tree crowns had relatively little effect on pigment, SLA and water predictions. However, N and phosphorus (P) were more sensitive to canopy structural variability. Our modeling results suggest that multiple leaf chemicals and SLA can be estimated from leaf and canopy reflectance spectroscopy, and that the high-LAI canopies found in tropical forests enhance the signal via multiple scattering. Finally, the two factors we found to most negatively impact leaf chemical predictions from canopy reflectance were variation in LAI and viewing geometry, which can be managed with new airborne technologies and analytical methods.
KW - Canopy chemistry
KW - Canopy structure
KW - Hyperspectral
KW - Imaging spectroscopy
KW - Partial least squares
KW - Radiative transfer
KW - Tropical forest
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U2 - 10.1016/j.rse.2008.07.003
DO - 10.1016/j.rse.2008.07.003
M3 - Article
AN - SCOPUS:50849144917
SN - 0034-4257
VL - 112
SP - 3958
EP - 3970
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
IS - 10
ER -