© 2003 Heron Publishing—Victoria, Canada
Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data
Nicholas C. Coops (1, 2), Christine Stone (3), Darius S. Culvenor (1), Laurie A. Chisholm (4) and Ray N. Merton (5)
1. CSIRO Forestry and Forest Products, Private Bag 10, Clayton South, Victoria 3169, Australia / 2. Author to whom correspondence should be addressed (nicholas.coops@csiro.au) / 3. Research and Development Division, State Forests of NSW, P.O. Box 100, Beecroft, NSW 2119, Australia / 4. School of Geoscience, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia / 5. Centre for Remote Sensing and GIS, University of New South Wales, Sydney, NSW, Australia / Received January 14, 2002; accepted June 29, 2002; published online December 2, 2002
Summary
The physiological status of forest canopy foliage is influenced by a range of factors that affect leaf pigment content and
function. Recently, several indices have been developed from remotely sensed data that attempt to provide robust estimates
of leaf chlorophyll content. These indices have been developed from either hand-held spectroradiometer spectra or high spectral
resolution (or hyperspectral) imagery. We determined if two previously published indices (Datt 1999), which were specifically
developed to predict chlorophyll content in eucalypt vegetation by remote sensing at the leaf scale, can be extrapolated accurately
to the canopy. We derived the two indices from hand-held spectroradiometer data of eucalypt leaves exhibiting a range of insect
damage symptoms. We also derived the indices from spectra obtained from high spectral and spatial resolution Compact Airborne
Spectrographic Imager 2 (CASI-2) imagery to determine if reasonable estimates at a scale of < 1 m can be achieved. One of
the indices (R850/R710 index, where R is reflectance) derived from hand-held spectroradiometer data showed a moderate correlation with relative leaf chlorophyll
content (r = 0.59, P < 0.05) for all dominant eucalypt species in the study area. The R850/R710 index derived from CASI-2 imagery yielded slightly lower correlations over the entire data set (r = 0.42, P < 0.05), but correlations for individual species were high (r = 0.77, P < 0.05). A scaling analysis indicated that the R850/R710 index was strongly affected by soil and water cover types when pixels were mixed, but appeared to be invariant to changes
in proportions of understory, which may limit its application.
Keywords:
CASI, forest health, hyperspectral, remote sensing.
