High-resolution laboratory spectrophotometer and Airborne Imaging Spectrometer (AIS) data were used to analyze forest leaf and canopy chemistry. Fundamental stretching frequencies of organic bonds in the visible, near infrared and short-wave infrared are indicative of concentrations and total content of nitrogen, phosphorous, starch and sugar. Laboratory spectrophotometer measurements showed very strong negative correlations with nitrogen (measured using wet chemistry) in the visible wavelengths. Strong correlations with green wet canopy weight in the atmospheric water absorption windows were observed in the AIS data. A fairly strong negative correlation between the AIS data at 1500 nm and total nitrogen and nitrogen concentration was evident. This relationship corresponds very closely to protein absorption features near 1500 nm

Acevedo, W.

Matson, P.

Peterson, D. L.

Spanner, M. A.

English

NASA Technical Reports Server

N86-11633 
HIGH RESOLUTION SPECTROMETRY OF LEAF AND CANOPY CHEMISTRY 
FOR BIOGEOCHEMICAL CYCLING 
MICHAEL A. SPANNER, Technico1or Government Service~, 
NASA/Ames Research Center, MoffE!tt Field, CA, USA; DAVID L. 
PETERSON, NASA/Ames Research Center, Moffett Field, CA, USAl 
WILLIAM ACEVEDO, Technico1or Government Services, NASA/Ames 
Research Center, Moffett Field, CA, USAl PAMELA MATSON, 
NASA/Ames Research Center, Moffett Field, CA, USA. 
ABSTRACT 
Higp- resolution laboratory spectrophotometer and 
Airborne Imaging Spectrometer (AIS) data were used to 
anaiyze forest leaf ane canopy chemistry. Fundamental 
stretching frequencies of organic bonds in the visible, near 
infrared and short - wave infrared are indicative of -
concentrations and total content of nitrogen, phosphorous, 
starch and sugar. Laboratory spectrophotometer measurements 
showed very strong negative correlations with nitrogen 
(measured using wet chemistry) in the visible wavelengths. 
Strong correlations with green wet canopy weight in the 
atmospheric water absorption windows were observed in the 
AIS data. A fairly strong negative correlation between the 
AIS data at 1500 nm and total nitrogen and nitrogen 
concentration was evident. This relationship corresponds 
very closely ~o protein absorption features near 1500 nm. 
INTRODUCTION 
Remote sensing data are being used to study and to 
model processes in the biogeochemical cycling of carbon, 
nitrogen, and phosphorus for 'forest ecosystems. Based on 
recent insights (Melillo and Gosz, 1983) r~garding nutrient 
availability and its interaction with the biochemical 
content of the canopy, a process level model (Fownes and 
Aber, 1985, this volume) is being developed. This model 
predicts produc~ivity, gas exchange, nutrient 
transformations and fluxes using information about climate 
and the biochemical content of the canopy. The three canopy 
variables under investigation u$ing remote sensing are leaf 
area index (LAI) , foliar biomass, and biochemical 
composition. This paper describes preliminary analysis 
using a laboratory 'spectrophotometer and the' Airborne 
Imaging Spectrometer to determine leaf and, canopy 
biochemical composition. 
92 
https://ntrs.nasa.gov/search.jsp?R=19860002166 2020-03-23T06:30:18+00:00Z
BACKGROUND 
Various organic compounds present in foliage absorb 
infrared (IR) radiation in a manner analogous to the 
mineralogical features used in geology. The absorption 
features . correspond to the fundamental stretching 
frequencies of organic bonds. The harmonics and overtones 
of these fundamentals are often found in the visible, near 
infrared and short - wave infrared. Unlike feature 
identification used for mineralogical discrimination, the 
same organic compounds are gener~lly always present in all 
vegetation types, but in different concentrations and total 
contents. Thus, a primary goal of infrared spectroscopy for 
plants should be quantification of these contents rather 
than discrimination of specific features. These organic 
compounds are of equal importance to nutrient cycling 
because they are composed of the key nutrients (carbon, 
nitrogen, phosphorous, etc.) that are required for plant 
growth. 
Nitrogen is bound up in leaves primarily in various 
proteins, enzymes, amino acids, cho10rophy11s, alkaloids, 
and cyanogenic compounds. The absorption features for the 
proteins and ch1orophy11s are shown in Figures 1-a and 1-b, 
respectively. Nitrogen concentration usually varies between 
0.5 to 3 percent by weight. Phosphorus content is typically 
lower than nitrogen (less than one percent) and is bound up 
in phospholipids, ATP, and other organic molecules. Carbon 
is ubiquitous in organic material; the forms most important 
to nutrient cycling are structural carbon (lignin and 
cellulose) and mobile carbon (starches (Figure 1-d) and 
sugars). Important features for lignin occur at 1148 and 
1685 nm, and for cellulose at 2100 nm. Water is abundant in 
leaves and its spectrum is shown in Figure 1-c. The role of 
other constituents of leaves (oils, carotenoids, cuticular 
waxes) may not be as significant for ~utrient cycling, but 
the fact that they also absorb IR radiation and may not 
co-vary with the other compounds, means that they contribute 
to the overall, IR signature of the leaf and introduce 
variation in the reflected radiation. 
Together with the multiple scattering properties of 
leaf structural interfaces, the biochemical constituents of 
leaves determine their infrared absorption characteristics 
in proportion to their concentration. Thus, at anyone 
wavelength, the reflected radiation will be a composite 
dominated by the strength of the absorption feature of each 
compound so that multiple wavelengths are required to 
estimate anyone constituent while accounting for the 
interference of other compounds. A goal of this research is 
to determine these predictive wavelength regions. 
93 
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Figure 1. Absorption spectra for four organic 
compounds in the visible and shortwave 
radiation regions 
CDRRELATJDN 
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Figure 2. Corre1ogram for percent nitrogen 
versus to~a1 hemispherical. reflectance 
for ground needles from seedlings 
of Tsuga mertensiana measured in a 
laboratory spectrophotometer 
94 
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LABORATORY TECHNIQUES AND RESULTS 
Our research is attempting to understand spectra of 
forest leaves and canopies as we proceed from laboratory to 
field to airborne spectroscopic techniques. Presented here 
are laboratory analyses of seedlings of Mountain hemlock 
(Tsuga mertensiana) grown in a phytotron under several 
treatments to vary the canopy chemistry. The treatments 
were: a control; fertilized with N, P, S; sugar addition; 
and fertilized and shaded. These seedlings were part of 
research by Dr. Matson who provided freeze-dried, ground 
leaf samples from each treatment for spectral analysis. 
These samples were analyzed in a wet chemical lab to 
determine the nitrogen, phosphorus, starch, and sugar 
content to correlate with the spectra. The ten samples were 
spectrally measured in a Perkin-Elmer spectrophotometer for 
percent reflectance betw~en 400 and 2600 nm. 
Correlation coefficients were calculated for each 
wavelength agaiHst the chemical analyses and are displayed 
as a correlogram. An example for percent nitrogen is shown 
in Figure 2. As expected; strong inverse correlations exist 
in the visible region due to the strong absorption effects 
of chlorophyll and associated proteins. Positive 
correlations are due most likely to other compounds which 
vary inversely with nitrogen (starch in this case) which 
corresponds to the correlation at about 2100 nm. Another 
absorption feature relating to protein begins to appear at 
about 2180 nm, but increasing instrument noise, small sample 
size, and small absolute differences in reflectance at these 
wavelengths may be obscuring this information. 
We are in the process of investigating the use of 
smoothing fuctions and derivatives to identify and measure 
concentrations at specific spectral regions which may 
overcome some of these difficulties. The peak at about 1450 
to 1500 nm is probably due to the presence of water 
reabsorbed by the samples during handling which masks the 
protein feature, thereby modifying the correlogram near 1500 
nm and above. Similar correlograms were calculated (not 
shown) for phosphorous, starch and sugar, and indicate an 
inverse relationship between starch and nitrogen. The 
presence of a number of posj~ive and negative peaks in the 
correlograms can be used to investigate multiple linear 
regressions for each constituent. This work is in progress 
and the present interpretations are still tentative due to 
the early stage of our investigations. 
AIRBORNE IMAGING SPECTROMETER DATA ANALYSIS 
The Airborne Imaging Spectrometer onboard a C-130 
aircraft acquired imagery over Blackhawk Island, Wisconsin 
on September 9, 1984. The AIS data were acquired in grating 
positions 0-3 (vegetation mode), covering wavelengths from 
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LEAF AREA INDEX 
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800 900 1000 1100 1200 1300 1400 1500 1600 1100 1800 1900 2000 2100 
WAVELENGTH (NM) 
96 
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100 900 1000 1100 1200 1300 1400 1500 1600 1700 1100 1,00 2000 2100 
F;gures 3(a) to 3(d). 
WAVELENGTH (NM) 
Correlograms for greea wet canopy weight 
(tons/hectare), leaf area index (orte-sided), 
nitrogen concentration (mg/cm2) and total 
nitrogen (kg/hectare) of the Blackhawk 
Island plots measured by the Airborne 
Imaging Spectrometer. 
97 
855 to 2036 nanometers. The spatial resolution of these 
data was approximately ten meters. No preprocessing 
algorithms were applied to the AIS data. There are four 
atmospheric water absorption regions within the vegetation 
grating position. Minor ones are centered at ~94 nm and 
1.13 nm, with major ones centered at 1.4 nm and 1.9 nm. The 
~IS data are of fairly good quality, with minor vertical 
striping in some bands. 
Analysis of the AIS data was performed on a VAX 11-780 
using IDIMS image processing software and software modified 
and developed specifically for the analysis of AIS data. 
The location of the six Deciduous Forest sites on Blackhawk 
Island (Fownes and Aber , 1985, this volume) were delineated 
on the AIS digital imagery using an interactive display. A 
two-by-two pixel region for each site was extracted and the 
mean and standard devi~tion for the 128 channels were 
calculated and plotted. A residual image was generated by 
defining a three-pixel wide transect along a fertility 
gradient across Blackhawk Island. The mean reflectance for 
each channel along the gradient was calculated and 
subtracted from the raw reflectance for the Blackhawk Island 
AIS scene. The residual reflectance was plotted for each of 
the six sites. Locations of low reflectance displayed 
negative residuals and areas of high reflectance had 
positive residuals. The residual plots allowed for improved 
discrimination of the six sites. A visual assessment of the 
fertility gradient was performed using the residual image. 
The correlogram program calculated the correlation 
coefficients for each of the measured canopy parameters of 
the six sites at each independent AIS wavelength. The 
canopy parameters analyzed were green wet canopy weight 
(tons/hectare), total nitrogen (kg/hectare), nitrogen 
concentraton (mg/cm ), and leaf area index (one-sided). The 
correlograms are presented in Figures 3a-3d. 
AIS RESULTS AND DISCUSSION 
Very strong correlation was observed between green wet 
canopy weight and AIS data at wavelengths other than the 
atmospheric absorption bands. Correlations exceeded .85 for 
many of these wavelengths, indicating the sensitivity of the 
AIS data to total mass (water and foliage) of the canopy. 
As expected, these relationships' did not exist in the 
atmospheric water absorption bands. The correlation occurs 
across a broad range of wavelengths indicating relatively 
slowly varying absorption. 
There were no wavelengths that displayed high 
correlations to leaf area index. This was not surprising 
because wavelengths on the AIS are not the same as those 
used for leaf area index estimation. Leaf area index 
estimations generally make use of ratios or transforms of 
98 
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red ($63-.69pm) and near infrared (.76-.90~m) portions of 
the electromagnetic spectrum. The Airborne Visible Infrared 
Im~ging Spectrometer (AVIRIS) will provide spectral 
information in these shorter wave-",'~gths and should be of 
significant value for leaf area index determinations when 
these data become available and are analyzed as ratios. 
Analysis of the total nitrogen and nitrogen 
concentration corre10grams reveals that there are strong 
negative correlations near 1500 nm, corresponding to a 
strong protein absorption feature at that wavelength. This 
result is very encouraging and shows the promise of a high 
spectral resolution imaging spectrometer. Another important 
protein absorption feature exists at 2180 nm; 
unfortunately, this wavelength is out of the range of the 
vegetation mode grating position of the AIS instrument. 
Another observation from the corre10grams is that when 
comparing the green wet canopy weight corre1ogram with the 
leaf nitrogen plot, different information from each plot 
emerges. The AIS is sensitive to specific canopy parameters 
at different wavelengths, providing unique information at 
each wavelength. At wavelengths between 1500 and 1600 nm 
especially, the plots trend in opposite directions. These 
dissimilar trends can be used to investigate multiple linear 
regressions for each constituent. 
We plan to expand our research efforts in Wisconsin 
next summer. We hope to obtain 20-25 plots with additional 
canopy information including canopy lignin. We are very 
encouraged by these preliminary results and we are excited 
about upcoming analyses of high spectral resolution remote 
sensing data. 
REFERENCES 
Danks, S.M., E.H. Evans, and P.A. Whittaker, 1983, 
Photosynthetiq System~~ Structure, Function and 
Assembly, p. 37, John Wiley and Sons, New York. -
Fownes, J. H. and J.D. Aber, 1985, "Forest Canopy 
Chemistry From Blackhawk Island", Wisconsin, JPL 
Airborne Imaging Spectrometer Data Analysis Workshop, 
This Volume, Pasadena, California. 
Melillo, J.M. and J. R. Gosz, 1983, Interactions of 
Biogeochemical Cycles in Forest Ecosystems, Chapter 6, 
The Major Biogeochemical Cycles and Their Interactions, 
SCOPE 21, Bolin and Cook (ed.), pp. 177-221, John 
Wiley and Sons, New York. 
Rotolo, P., 1979, Near Infrared Reflectance Instrumentation, 
Cereal Foods World, 24:94,~98. 
99 


High Resolution Spectrometry of Leaf and Canopy Chemistry for Biochemical Cycling

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