The goal of this work is to develop non-destructive techniques that can conveniently, rapidly and accurately assess crop physiological status and objectively evaluate plant responses to environmental factors, both natural and anthropogenic. High spectral resolution reflectance and absorption spectra of different and unrelated plant species were analyzed to determine spectral variability and information content in the visible and near-infrared spectrum at leaf and canopy levels. Techniques were developed to quantitatively retrieve chlorophyll, carotenoid and anthocyanin content from reflectance in a wide range of pigment content and composition.
Techniques for vegetation fraction retrieval those based on channels in visible range of the spectrum were developed and validated. Despite the fact that the reflectance contrast among the visible channels is much smaller than between the visible and near infrared, the sensitivity to moderate to high values of vegetation fraction is much higher than for NDVI and the error in vegetation fraction prediction did not exceed 10 per cent

Gitelson, Anatoly A.

Gritz, U.

Merzlyak, M. N.

Stark, R.

Zur, Y.

English

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University of Nebraska - Lincoln 
DigitalCommons@University of Nebraska - Lincoln 
Papers in Natural Resources Natural Resources, School of 
2001 
NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR 
ESTIMATION OF VEGETATION STATUS 
Anatoly A. Gitelson 
University of Nebraska at Lincoln, agitelson2@unl.edu 
M. N. Merzlyak 
Moscow State University 
Y. Zur 
University of Negev 
R. Stark 
University of Negev 
U. Gritz 
University of Negev 
Follow this and additional works at: https://digitalcommons.unl.edu/natrespapers 
 Part of the Natural Resources and Conservation Commons 
Gitelson, Anatoly A.; Merzlyak, M. N.; Zur, Y.; Stark, R.; and Gritz, U., "NON-DESTRUCTIVE AND REMOTE 
SENSING TECHNIQUES FOR ESTIMATION OF VEGETATION STATUS" (2001). Papers in Natural 
Resources. 273. 
https://digitalcommons.unl.edu/natrespapers/273 
This Article is brought to you for free and open access by the Natural Resources, School of at 
DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Papers in Natural Resources 
by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. 
205
NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATION
OF VEGETATION STATUS
A. A. GITELSON
School of Natural Resource Sciences, University of Nebraska-Lincoln,
113 Nebraska Hall, Lincoln, NE 68588-0517, USA
E-mail: gitelson@calmit.unl.edu
M. N. MERZLYAK
Department of Cell Physiology & Immunology, Faculty of Biology, Moscow State University,
Moscow, Russia
Y. ZUR, R. STARK, U. GRITZ
Department of Geological and Environmental Sciences, Ben-Gurion, University of the Negev,
Israel
ABSTRACT
The goal of this work is to develop non-destructive techniques that can conveniently, rapidly
and accurately assess crop physiological status and objectively evaluate plant responses to
environmental factors, both natural and anthropogenic. High spectral resolution reflectance
and absorption spectra of different and unrelated plant species were analyzed to determine
spectral variability and information content in the visible and near-infrared spectrum at leaf
and canopy levels. Techniques were developed to quantitatively retrieve chlorophyll,
carotenoid and anthocyanin content from reflectance in a wide range of pigment content and
composition.
Techniques for vegetation fraction retrieval those based on channels in visible range of the
spectrum were developed and validated. Despite the fact that the reflectance contrast among
the visible channels is much smaller than between the visible and near infrared, the sensitivity
to moderate to high values of vegetation fraction is much higher than for NDVI and the error
in vegetation fraction prediction did not exceed 10 per cent.
Leaf pigment content estimation
Optical properties of the leaves of several plant species in a wide range of chlorophyll (Chl),
carotenoid (Car) and anthocyanin (Anth) contents have been investigated (Gitelson and
Merzlyak, 1997; Zur et al., 2000; Gitelson et al., 2001a) in order to develop techniques for
non-destructive estimation of pigment content and composition. It was found that the
reflectance in spectral band near 700 nm was sensitive to Chl content only, whereas
reflectance around 550 nm was sensitive to both Chl and Anth content, and near 500-520 nm
was sensitive to both Car and Chl content. The technique was developed to remove Chl effect
from reflectance near 550 nm and 500-520 nm. Algorithms for Chl, Car and Anth contents
estimating were devised and, finally, validated by few independent data sets.
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.
206
(R700)
-1 = 1.68*10-3Chl+ 0.0249
R2 = 0.9512, STD = 3.7 nmol/cm2
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 10 20 30 40 50 60
Chlorophyll content, nmol/cm2
(R
70
0)-
1
Anth-free 
Anth 2.9 to 100 nmol/cm2
FIGURE 1. Inverse reflectance at 700 nm vs. Chl content for Anth-containing and Anth-free
leaves.
Chlorophylls. Reflectance in spectral bands near 550 nm and 700 nm was found to be
sensitive to Chl content (Gitelson and Merzlyak, 1994; 1996; Blackmer et al., 1994;
Lichtenthaler et al., 1996; Scheppers et al., 1996; Gamon and Surfus, 1999). For many
unrelated plant species, inverse reflectance (R550)-1 and (R700)-1 was a precise measure of Chl,
and the reflectance ratios in near infrared range (RNIR) to those in the green (R550) and red
edge (R700) regions, RNIR/R550 and RNIR/R700, were linearly proportional to Chl content
(determination coefficient r2 = 0.95; root-mean square variation < 4 nmol/cm2) for Chl ranged
from 3 to 75 nmol/cm2 (Gitelson and Merzlyak, 1997). In this study, we investigated the
sensitivity of these indices to Anth content. Absorption by Anth in vivo at 550 nm (Gitelson et
al., 2001a) prevents to use the index RNIR/R550 for Chl estimation in Anth-containing leaves.
Nevertheless, it has been found that reciprocal reflectance at 700 nm (R700)-1 remained
linearly proportional to Chl content in leaves with Anth content ranged from 0.3 to 100
nmol/cm2 and Car content from 3 to 18 nmol/cm2 (Fig. 1). Thus, for Chl assessment in Anth-
free leaves, we suggest using reflectance ratios RNIR/R550 and RNIR/R700. Inverse reflectance
(R700)-1 or ratio RNIR/R700 can be employed for Chl estimation in leaves with a wide range of
Chl, Car, and Anth variation.
Carotenoids. Car and Chl have overlapping absorption bands in the blue range of the spectrum,
making it difficult to distinguish between them by remote sensing techniques (Merzlyak et al.,
1999). To find spectral range that is sensitive to Car content, absorption and reflectance spectra
of leaves in a wide range of Car (1 to 18 nmol/cm2) and Chl (0.1 to 75 nmol/cm2) content were
studied. The standard deviation (STD) of absorbance spectra, normalized to Chl absorption
maximum at 670 nm, peaks at 520 nm; this peak is attributed to Car absorption (Zur et al., 2000).
The determination coefficient of the relationship ‘Reflectance vs. Car’ also shows prominent
peak in the range 500-520 nm. The technique was devise to remove Chl effect on reflectance in
this spectral region and the index for non-destructive Car estimating was developed. The
Carotenoids Reflectance Indices in the forms
CRI550 = (R510)-1-(R550)-1 and CRI700 = (R510)-1-(R700)-1
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.
207
were found to be proportional to Car (r2 = 0.93, an estimation error of Car < 2 nmol/cm2) and
almost insensitive to Chl content (Fig. 2).
FIGURE 2. Index for carotenoids estimation plotted versus Car and Chl content
Anthocyanins. Comparing absorption spectra of anthocyanin-containing and anthocyanin-free
leaves with the same chlorophyll content, absorption spectra of anthocyanin in intact leaves
were derived. The main spectral feature of anthocyanin absorption in vivo was a peak around
550 nm which magnitude was closely related to anthocyanin content (Fig. 3). A technique
was developed to subtract Chl contribution to reflectance in this spectral region and
quantitatively non- destructively retrieve Anth content from reflectance in a wide range of
pigment content and composition (Gitelson et al., 2001a). Anthocyanin Reflectance Index in
the form
ARI = (R550)-1-(R700)-1
allowed an accurate estimation of anthocyanin accumulation (STD within 3.9 nmol/cm2),
even in minute amounts, in intact stressed and senescing leaves (Fig. 4).
Vegetation fraction and density estimation
The decreased reflectance in the NIR, occurring at or near the midseason of a growing crop,
can be a limiting factor in the use of that spectral region for estimating of vegetation fraction
(VF). In order to evaluate the information content inherent in reflectance spectra and devise a
technique for remote estimation of vegetation fraction, spectral behavior of reflectance and
absorption of a wheat canopy with vegetation fraction ranged from 0 to 100% were studied in
visible and near-infrared ranges of the spectrum. The MODIS blue (459-479 nm), green (545-
565 nm), and red (620-670 nm) channels as well as MERIS red edge channel (695-705 nm)
were used in developed Visible Atmospherically Resistant Indices (VARI)
VARIgreen = (Rgreen-Rred)/(Rgreen+Rred-Rblue)
and
VARI700 = (R700-1.7*Rred+0.7*Rblue)/(R700+2.3*Rred-1.3*Rblue)
0
0.01
0.02
0.03
0.04
0 2 4 6 8 10 12 14 16 18
Carotenoids Content, nmol/cm2
C
ar
ot
en
oi
ds
 R
ef
le
ct
an
ce
 In
de
x
0
0.01
0.02
0.03
0.04
0 10 20 30 40 50 60
Chlorophyll Content, nmol/cm2
Chlorophyll
Carotenoids, r2= 0.94
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.
208
0
10
20
30
40
50
60
450 500 550 600 650
Wavelength, nm
A
nt
ho
cy
an
in
 a
bs
or
pt
io
n,
 p
er
 c
en
t
2.9
6.4
9.1
22.9
Anthocyanin = 39.1 nmol/cm2
Maple
0
0.05
0.1
0.15
0.2
0 5 10 15 20 25 30 35 40 45 50
Anthocyanin content, nmol/cm2
(R
55
0)-
1 -
(R
70
0)
-1
, (
%
)-1
r2 = 0.91, STD = 5.1 nmol/cm2, n=51
FIGURE 3. Anthocyanin absorption retrieved
from absorption spectra of leaves with equal
Chl content and different Anth content
FIGURE 4. Index for anthocyanin estimation
plotted versus anthocyanin content
The indices were found to be minimally sensitive to atmospheric effects allowing estimation
of VF with an error of less than 10% in a wide range of atmospheric optical thickness
(Gitelson et al., 1999; 2001b).
Another technique for vegetation fraction estimation was proposed (Gitelson et al., 2000;
Stark et al., 2000). It was found that reflectance of the wheat with 100% vegetation fraction,
despite various canopy structures and pigment contents, forms a vegetation line defined by
close linear relationships reflectances R700 vs. R550 and R670 vs. R500. The position and
orientation of the lines in two-dimensional spectral space were repeatable for four types of
wheat during two years of observations. Soils of very different types and wetness form soil
lines in the R700 vs. R550 and R670 vs. R500 spectral spaces. The soil lines have also proven to
be repeatable over the course of two years of data collection. Two-dimensional spectral space,
as defined and constrained by soil and vegetation lines, includes all possible canopy
reflectances with VF ranging from 0 to 100%. We suggest using the location of reflectance in
these spectral spaces as a quantitative measure of VF. Predicted VF was proportional to
measured VF with root-mean square variation of predicted values from measured of less than
10%. For the independent data set (cornfields in Nebraska), excellent correspondence between
predicted and actually measured vegetation fraction values was found.
Despite the fact that the reflectance contrast among the visible channels is much smaller than
between the visible and NIR, the sensitivity of both techniques to moderate to high values of
VF was much higher than for NDVI. Suggested techniques will complement the widely used
NDVI, ARVI, SAVI, and GARI (Gitelson et al., 1996), which is based on the green and the
NIR bands. Therefore, we propose using only the visible range of the spectrum to
quantitatively estimate vegetation fraction, and we are interested in applying the algorithms to
new satellite technologies including the high spectral and radiometric resolution achieved in
the recently launched SeaWiFS, MODIS, ASTER, MISR, and near future space systems such
as HYPERION and MERIS.
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.
209
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80 100
Vegetation fraction, per cent
V
eg
et
at
io
n 
In
di
ce
s
NDVI
(Rgreen-Rred)/(Rgreen+Rred-Rblue)
FIGURE 5. NDVI and newly developed vegetation index (Rgreen-Rred)/(Rgreen+Rred-Rblue)
versus vegetation fraction for wheat canopy
REFERENCES
Blackmer, T.M., Schepers, J.S. and Varvel, G.E. (1994) Light reflectance compared with
other nitrogen stress measurements in corn leaves, Agron. J. 86:934-938.
Gamon, J.A., Surfus, J.S. (1999) Assessing leaf pigment content and activity with a
reflectometer. New Phytol. 143:105-117.
Gitelson, A.A. and Merzlyak, M.N. (1994a) Quantitative estimation of chlorophyll-a using
reflectance spectra: Experiments with autumn chestnut and maple leaves. J. Photochem.
Photobiol. B: Biol. 22: 247-252.
Gitelson, A., Merzlyak, M.N. (1994b) Spectral reflectance changes associated with autumn
senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral
features and relation to chlorophyll estimation. J. Plant Physiol. 143:286-292.
Gitelson, A., Merzlyak, M.N. (1996) Signature analysis of leaf reflectance spectra: algorithm
development for remote sensing of chlorophyll. J. Plant Physiol., 148:494-500.
Gitelson, A., Kaufman, Y.Z., Merzlyak, M. (1996) Use of a green channel in remote sensing
of global vegetation from EOS-MODIS. Remote Sens. Environ. 58: 289-298.
Gitelson, A., Merzlyak, M.N. (1997) Remote estimation of chlorophyll content in higher plant
leaves. Int. J. Remote Sens. 18, 291-298.
Gitelson, A.A., Stark, R. Kaufman, Y.Z., Rundquist, D. (1999) A Technique for remote
estimation of percent vegetation fraction, In Proc. the International Symposium on
Spectral Sensing Research, Systems and Sensors for the New Millennium, Int. Society
for Photogrammetry & Remote Sensing, Oct. 31-Nov. 4, 1999, Las Vegas NV, pp.191-
201.
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.
210
Gitelson, A., Grits, U., Stark, R., Rundquist, D., Kaufman, Y.Z. (2000) Novel algorithms for
remote estimation of vegetation fraction, In Proc. Second Int. Geospatial Information in
Agriculture and Forestry Conference, Florida, 10-12 Jan. 2000, Vol. 2, pp. 1-8.
Gitelson, A., Merzlyak, M. N., Chivkunova, O. (2001a) Optical properties and non-
destructive estimation of anthocyanin content in plant leaves. Photochem. Photobiol.
(forthcoming).
Gitelson, A.A., Kaufman, Y.Z., Stark, R., Rundquist, D. (2001b) Novel algorithms for remote
estimation of vegetation fraction. Submitted to Rem. Sens. Environ.
Lichtenthaler, H.K., Gitelson, A.A., Lang, M. (1996) Non-destructive determination of
chlorophyll content of leaves of a green and an aurea mutant of tobacco by reflectance
measurements, J. Plant Physiol. 148: 483-493.
Merzlyak, M.N., Gitelson, A.A., Chivkunova, O.B., Rakitin, V.Y. (1999) Non-destructive
optical detection of pigment changes during leaf senescence and fruit ripening, Physiol.
Plant. 106: 135-141.
Schepers, J.S., Blackmer, T.M., Wilhelm, W.W., Resende, M. (1996) Transmittance and
reflectance measurements of corn leaves from plants with different nitrogen and water
supply, J. Plant Physiol. 148:523-529.
Schepers, J.S., Blackmer, T.M., Francis, D.D. (1998) Chlorophyll meter method for
estimating nitrogen content in plant tissue, in Handbook of Reference Methods for Plant
Analysis, Y.P. Kalra (ed.), pp. 129-135
Stark, R., Gitelson, A. Grits, U., Rundquist, D., Kaufman, Y.Z. (2000) New technique for
remote estimation of vegetation fraction: principles, algorithms and validation. Aspects
Appl. Biol. 60: 241-246.
Zur, Y., Gitelson, A.A., Chivkunova, O.B., Merzlyak, M.N. (2000) The Spectral contribution
of carotenoids to light absorption and reflectance in green leaves. In Proc. Second Int.
Geospatial Information in Agriculture and Forestry Conference, Florida, 10-12 Jan.
2000, Vol. 2, pp. 17-23.
Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, 
Montpelier, France, 2001. Grenier & Blackmore, editors.


NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATION OF VEGETATION STATUS

DigitalCommons@University of Nebraska

University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Papers in Natural Resources Natural Resources, School of 2001 NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATION OF VEGETATION STATUS Anatoly A. Gitelson University of Nebraska at Lincoln, agitelson2@unl.edu M. N. Merzlyak Moscow State University Y. Zur University of Negev R. Stark University of Negev U. Gritz University of Negev Follow this and additional works at: https://digitalcommons.unl.edu/natrespapers  Part of the Natural Resources and Conservation Commons Gitelson, Anatoly A.; Merzlyak, M. N.; Zur, Y.; Stark, R.; and Gritz, U., "NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATION OF VEGETATION STATUS" (2001). Papers in Natural Resources. 273. https://digitalcommons.unl.edu/natrespapers/273 This Article is brought to you for free and open access by the Natural Resources, School of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Papers in Natural Resources by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. 205NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATIONOF VEGETATION STATUSA. A. GITELSONSchool of Natural Resource Sciences, University of Nebraska-Lincoln,113 Nebraska Hall, Lincoln, NE 68588-0517, USAE-mail: gitelson@calmit.unl.eduM. N. MERZLYAKDepartment of Cell Physiology & Immunology, Faculty of Biology, Moscow State University,Moscow, RussiaY. ZUR, R. STARK, U. GRITZDepartment of Geological and Environmental Sciences, Ben-Gurion, University of the Negev,IsraelABSTRACTThe goal of this work is to develop non-destructive techniques that can conveniently, rapidlyand accurately assess crop physiological status and objectively evaluate plant responses toenvironmental factors, both natural and anthropogenic. High spectral resolution reflectanceand absorption spectra of different and unrelated plant species were analyzed to determinespectral variability and information content in the visible and near-infrared spectrum at leafand canopy levels. Techniques were developed to quantitatively retrieve chlorophyll,carotenoid and anthocyanin content from reflectance in a wide range of pigment content andcomposition.Techniques for vegetation fraction retrieval those based on channels in visible range of thespectrum were developed and validated. Despite the fact that the reflectance contrast amongthe visible channels is much smaller than between the visible and near infrared, the sensitivityto moderate to high values of vegetation fraction is much higher than for NDVI and the errorin vegetation fraction prediction did not exceed 10 per cent.Leaf pigment content estimationOptical properties of the leaves of several plant species in a wide range of chlorophyll (Chl),carotenoid (Car) and anthocyanin (Anth) contents have been investigated (Gitelson andMerzlyak, 1997; Zur et al., 2000; Gitelson et al., 2001a) in order to develop techniques fornon-destructive estimation of pigment content and composition. It was found that thereflectance in spectral band near 700 nm was sensitive to Chl content only, whereasreflectance around 550 nm was sensitive to both Chl and Anth content, and near 500-520 nmwas sensitive to both Car and Chl content. The technique was developed to remove Chl effectfrom reflectance near 550 nm and 500-520 nm. Algorithms for Chl, Car and Anth contentsestimating were devised and, finally, validated by few independent data sets.Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, Montpelier, France, 2001. Grenier & Blackmore, editors.206(R700)-1 = 1.68*10-3Chl+ 0.0249R2 = 0.9512, STD = 3.7 nmol/cm200.020.040.060.080.10.120.140 10 20 30 40 50 60Chlorophyll content, nmol/cm2(R700)-1Anth-free Anth 2.9 to 100 nmol/cm2FIGURE 1. Inverse reflectance at 700 nm vs. Chl content for Anth-containing and Anth-freeleaves.Chlorophylls. Reflectance in spectral bands near 550 nm and 700 nm was found to besensitive to Chl content (Gitelson and Merzlyak, 1994; 1996; Blackmer et al., 1994;Lichtenthaler et al., 1996; Scheppers et al., 1996; Gamon and Surfus, 1999). For manyunrelated plant species, inverse reflectance (R550)-1 and (R700)-1 was a precise measure of Chl,and the reflectance ratios in near infrared range (RNIR) to those in the green (R550) and rededge (R700) regions, RNIR/R550 and RNIR/R700, were linearly proportional to Chl content(determination coefficient r2 = 0.95; root-mean square variation < 4 nmol/cm2) for Chl rangedfrom 3 to 75 nmol/cm2 (Gitelson and Merzlyak, 1997). In this study, we investigated thesensitivity of these indices to Anth content. Absorption by Anth in vivo at 550 nm (Gitelson etal., 2001a) prevents to use the index RNIR/R550 for Chl estimation in Anth-containing leaves.Nevertheless, it has been found that reciprocal reflectance at 700 nm (R700)-1 remainedlinearly proportional to Chl content in leaves with Anth content ranged from 0.3 to 100nmol/cm2 and Car content from 3 to 18 nmol/cm2 (Fig. 1). Thus, for Chl assessment in Anth-free leaves, we suggest using reflectance ratios RNIR/R550 and RNIR/R700. Inverse reflectance(R700)-1 or ratio RNIR/R700 can be employed for Chl estimation in leaves with a wide range ofChl, Car, and Anth variation.Carotenoids. Car and Chl have overlapping absorption bands in the blue range of the spectrum,making it difficult to distinguish between them by remote sensing techniques (Merzlyak et al.,1999). To find spectral range that is sensitive to Car content, absorption and reflectance spectraof leaves in a wide range of Car (1 to 18 nmol/cm2) and Chl (0.1 to 75 nmol/cm2) content werestudied. The standard deviation (STD) of absorbance spectra, normalized to Chl absorptionmaximum at 670 nm, peaks at 520 nm; this peak is attributed to Car absorption (Zur et al., 2000).The determination coefficient of the relationship ‘Reflectance vs. Car’ also shows prominentpeak in the range 500-520 nm. The technique was devise to remove Chl effect on reflectance inthis spectral region and the index for non-destructive Car estimating was developed. TheCarotenoids Reflectance Indices in the formsCRI550 = (R510)-1-(R550)-1 and CRI700 = (R510)-1-(R700)-1Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, Montpelier, France, 2001. Grenier & Blackmore, editors.207were found to be proportional to Car (r2 = 0.93, an estimation error of Car < 2 nmol/cm2) andalmost insensitive to Chl content (Fig. 2).FIGURE 2. Index for carotenoids estimation plotted versus Car and Chl contentAnthocyanins. Comparing absorption spectra of anthocyanin-containing and anthocyanin-freeleaves with the same chlorophyll content, absorption spectra of anthocyanin in intact leaveswere derived. The main spectral feature of anthocyanin absorption in vivo was a peak around550 nm which magnitude was closely related to anthocyanin content (Fig. 3). A techniquewas developed to subtract Chl contribution to reflectance in this spectral region andquantitatively non- destructively retrieve Anth content from reflectance in a wide range ofpigment content and composition (Gitelson et al., 2001a). Anthocyanin Reflectance Index inthe formARI = (R550)-1-(R700)-1allowed an accurate estimation of anthocyanin accumulation (STD within 3.9 nmol/cm2),even in minute amounts, in intact stressed and senescing leaves (Fig. 4).Vegetation fraction and density estimationThe decreased reflectance in the NIR, occurring at or near the midseason of a growing crop,can be a limiting factor in the use of that spectral region for estimating of vegetation fraction(VF). In order to evaluate the information content inherent in reflectance spectra and devise atechnique for remote estimation of vegetation fraction, spectral behavior of reflectance andabsorption of a wheat canopy with vegetation fraction ranged from 0 to 100% were studied invisible and near-infrared ranges of the spectrum. The MODIS blue (459-479 nm), green (545-565 nm), and red (620-670 nm) channels as well as MERIS red edge channel (695-705 nm)were used in developed Visible Atmospherically Resistant Indices (VARI)VARIgreen = (Rgreen-Rred)/(Rgreen+Rred-Rblue)andVARI700 = (R700-1.7*Rred+0.7*Rblue)/(R700+2.3*Rred-1.3*Rblue)00.010.020.030.040 2 4 6 8 10 12 14 16 18Carotenoids Content, nmol/cm2Carotenoids Reflectance Index00.010.020.030.040 10 20 30 40 50 60Chlorophyll Content, nmol/cm2ChlorophyllCarotenoids, r2= 0.94Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, Montpelier, France, 2001. Grenier & Blackmore, editors.2080102030405060450 500 550 600 650Wavelength, nmAnthocyanin absorption, per cent2.96.49.122.9Anthocyanin = 39.1 nmol/cm2Maple00.050.10.150.20 5 10 15 20 25 30 35 40 45 50Anthocyanin content, nmol/cm2(R550)-1 -(R700)-1, (%)-1r2 = 0.91, STD = 5.1 nmol/cm2, n=51FIGURE 3. Anthocyanin absorption retrievedfrom absorption spectra of leaves with equalChl content and different Anth contentFIGURE 4. Index for anthocyanin estimationplotted versus anthocyanin contentThe indices were found to be minimally sensitive to atmospheric effects allowing estimationof VF with an error of less than 10% in a wide range of atmospheric optical thickness(Gitelson et al., 1999; 2001b).Another technique for vegetation fraction estimation was proposed (Gitelson et al., 2000;Stark et al., 2000). It was found that reflectance of the wheat with 100% vegetation fraction,despite various canopy structures and pigment contents, forms a vegetation line defined byclose linear relationships reflectances R700 vs. R550 and R670 vs. R500. The position andorientation of the lines in two-dimensional spectral space were repeatable for four types ofwheat during two years of observations. Soils of very different types and wetness form soillines in the R700 vs. R550 and R670 vs. R500 spectral spaces. The soil lines have also proven tobe repeatable over the course of two years of data collection. Two-dimensional spectral space,as defined and constrained by soil and vegetation lines, includes all possible canopyreflectances with VF ranging from 0 to 100%. We suggest using the location of reflectance inthese spectral spaces as a quantitative measure of VF. Predicted VF was proportional tomeasured VF with root-mean square variation of predicted values from measured of less than10%. For the independent data set (cornfields in Nebraska), excellent correspondence betweenpredicted and actually measured vegetation fraction values was found.Despite the fact that the reflectance contrast among the visible channels is much smaller thanbetween the visible and NIR, the sensitivity of both techniques to moderate to high values ofVF was much higher than for NDVI. Suggested techniques will complement the widely usedNDVI, ARVI, SAVI, and GARI (Gitelson et al., 1996), which is based on the green and theNIR bands. Therefore, we propose using only the visible range of the spectrum toquantitatively estimate vegetation fraction, and we are interested in applying the algorithms tonew satellite technologies including the high spectral and radiometric resolution achieved inthe recently launched SeaWiFS, MODIS, ASTER, MISR, and near future space systems suchas HYPERION and MERIS.Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, Montpelier, France, 2001. Grenier & Blackmore, editors.209-0.4-0.200.20.40.60.810 20 40 60 80 100Vegetation fraction, per centVegetation IndicesNDVI(Rgreen-Rred)/(Rgreen+Rred-Rblue)FIGURE 5. NDVI and newly developed vegetation index (Rgreen-Rred)/(Rgreen+Rred-Rblue)versus vegetation fraction for wheat canopyREFERENCESBlackmer, T.M., Schepers, J.S. and Varvel, G.E. (1994) Light reflectance compared withother nitrogen stress measurements in corn leaves, Agron. J. 86:934-938.Gamon, J.A., Surfus, J.S. (1999) Assessing leaf pigment content and activity with areflectometer. New Phytol. 143:105-117.Gitelson, A.A. and Merzlyak, M.N. (1994a) Quantitative estimation of chlorophyll-a usingreflectance spectra: Experiments with autumn chestnut and maple leaves. J. Photochem.Photobiol. B: Biol. 22: 247-252.Gitelson, A., Merzlyak, M.N. (1994b) Spectral reflectance changes associated with autumnsenescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectralfeatures and relation to chlorophyll estimation. J. Plant Physiol. 143:286-292.Gitelson, A., Merzlyak, M.N. (1996) Signature analysis of leaf reflectance spectra: algorithmdevelopment for remote sensing of chlorophyll. J. Plant Physiol., 148:494-500.Gitelson, A., Kaufman, Y.Z., Merzlyak, M. (1996) Use of a green channel in remote sensingof global vegetation from EOS-MODIS. Remote Sens. Environ. 58: 289-298.Gitelson, A., Merzlyak, M.N. (1997) Remote estimation of chlorophyll content in higher plantleaves. Int. J. Remote Sens. 18, 291-298.Gitelson, A.A., Stark, R. Kaufman, Y.Z., Rundquist, D. (1999) A Technique for remoteestimation of percent vegetation fraction, In Proc. the International Symposium onSpectral Sensing Research, Systems and Sensors for the New Millennium, Int. Societyfor Photogrammetry & Remote Sensing, Oct. 31-Nov. 4, 1999, Las Vegas NV, pp.191-201.Gitelson, Merzlyak, Zur, Stark & Gritz in the Proceedings of the 3rd European Conference on Precision Agriculture, Montpelier, France, 2001. Grenier & Blackmore, editors.210Gitelson, A., Grits, U., Stark, R., Rundquist, D., Kaufman, Y.Z. (2000) Novel algorithms forremote estimation of vegetation fraction, In Proc. Second Int. Geospatial Information inAgriculture and Forestry Conference, Florida, 10-12 Jan. 2000, Vol. 2, pp. 1-8.Gitelson, A., Merzlyak, M. N., Chivkunova, O. (2001a) Optical properties and non-destructive estimation of anthocyanin content in plant leaves. Photochem. Photobiol.(forthcoming).Gitelson, A.A., Kaufman, Y.Z., Stark, R., Rundquist, D. (2001b) Novel algorithms for remoteestimation of vegetation fraction. Submitted to Rem. Sens. Environ.Lichtenthaler, H.K., Gitelson, A.A., Lang, M. (1996) Non-destructive determination ofchlorophyll content of leaves of a green and an aurea mutant of tobacco by reflectancemeasurements, J. Plant Physiol. 148: 483-493.Merzlyak, M.N., Gitelson, A.A., Chivkunova, O.B., Rakitin, V.Y. (1999) Non-destructiveoptical detection of pigment changes during leaf senescence and fruit ripening, Physiol.Plant. 106: 135-141.Schepers, J.S., Blackmer, T.M., Wilhelm, W.W., Resende, M. (1996) Transmittance andreflectance measurements of corn leaves from plants with different nitrogen and watersupply, J. Plant Physiol. 148:523-529.Schepers, J.S., Blackmer, T.M., Francis, D.D. (1998) Chlorophyll meter method forestimating nitrogen content in plant tissue, in Handbook of Reference Methods for PlantAnalysis, Y.P. 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NON-DESTRUCTIVE AND REMOTE SENSING TECHNIQUES FOR ESTIMATION OF VEGETATION STATUS

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