Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density

Baumgardner, M. F.

Cipra, J. E.

Stoner, E. R.

English

NASA Technical Reports Server

Determining Density of
Maize Canopy: Airborne
Mu | Aral Sefrwer
The Applications of Remote
Purdie University
West Lafayette, Indiana
https://ntrs.nasa.gov/search.jsp?R=19730007698 2020-03-23T08:08:02+00:00Z
Title:
Determining Density of Maize Canopy:
II. Airborne Multispectral Scanner Data1
by
E. R. Stoner
M. F. B aumg ardne r
and
J. E. Cisra2
1Journal Paper Mo. 4930, Purdue University Agricultural
Experiment Station, Contributed by the Laboratory for
Applications of Remote Sensing and Department of Agronomy,
West Lafayette, Indiana 47907. Supported by: NASA
Grant NGL 15-005-112.
2Peace Corps, Brazil; Associate Professor, Department of
Agronomy, and Research Agronomist.
ABSTRACT
Multispectral scanner data were collected in two
flights over a light colored soil background cover plot
at an altitude of 305 m. Energy in eleven reflective wave-
length bands from 0.45 to 2.6 pm was recorded by the
scanner. Four growth stages of maize (Zea mays L.) were
present at the time of each overflight, giving a wide range
of canopy densities for each flight date. Leaf area index
measurements were taken from tHe twelve subplots at the
time of each overflight, and were used as a measure of
canopy density.
Ratio techniques were used to relate uncalibrated
scanner response to leaf area index. The ratios of scanner
data values for the 0.72 to 0.92 pro wavelength band over
the 0.61 to 0.70 ym wavelength band were calculated for
each plot. The ratios related very well to leaf area
index for a given flight date but could not be generalized
between data from different flights because of uncertainty
in scanner response on different dates.,. The results indi-
cated that spectral data from maize canopies could be of
value in determining canopy density.
Additional Key Words; ground cover, leaf area index,
remote sensing.
•'4*.
INTRODUCTION
Airborne multispectral scanner data provide an
axtended view of the reflective properties of plant cano-
pies. Information may be,obtained in the wavelength range
from 0.4 ym to 2.6 ym in this manner. Comparisons of
scanner data in various discrete wavelength bands or chan-
nels of the multispectral scanner allow for investigation
of the spectral differences between various plant canopy
covers.i
Kristof and Baumgardner (1970, personal communication)
found that a decrease in radiation in the visible and ani »i
increase in radiation in the reflective infrared region
0( curred in comparing multispectral scanner data over crop
canopies from April to late June. Disregarding complica-
tions of row structure and direction which may produce a
Hs|tove pipe effect" (LARS, 1968) in maize canopies, the
crease in ground cover could be detected by establishing
a ratio of the relative reflectance in the chlorophyll
absorption band to the relative reflectance in the near
infrared.
Ii Kristof and Baumgardner (1970, personal communication)
used the ratio of relative reflectance in the 0.58 to 0.62
ym band to the relative reflectance in the 0.80 to 1.00 ym
band to observe increases in ground cover. Considerations
of the reflectance properties of green vegetation (Hoffer
and Johannsen, 1969; Gates et al., 1965; Knipling, 1970;
Myers et al., 1966; Myers, 1970) and that of soil '
(Baumgardner et al., 1970; Hoffer and Johinnsen, 1969;
Cipra et al., 1971; bowers and Hanks, 196S; Condit, 1970)
would seem to favor a ratio of these two wavelength regions
for characterizing canopy density.
Chlorophyll absorbs at 0.65 iim in the visible wave-
lengths, and it is reasonable to assume that as a crop
canopy becomes more dense it would absorb more strongly
(and hence, reflect less) in this region. The 0.72 to 1.3
* -
ym wavelength range is the region in which little absorp-
tion takes place in green vegetation and in which almost
all incident light is transmitted or reflected (Hoffer and
#
Johannsen, 1969). Multiple leaf layer experiments have
shown that reflectance in this 0.72 to 1.3 ym wavelength
region increases with increasing leaf layers (Myers et al.,
1966). Therefore, the reflectance of a crop canopy may be
expected to increase in the 0.72 to 1.3 ym wavelength range
as canopy density increases. Soil reflectance generally
increases slightly in going from the red wavelength region
to the near infrared wavelength region, the amount of
increase for a particular soil depending mainly on the
soil moisture content.
. With the increased reflectance in the near infrared
and the increased chlorophyll absorption with increasing .
crop cover, this ratio (chlorophyll absorption band over
the near .infrared band) would decrease with increasing
crop canopy. For a given crop and soil type an estimate
of the canopy density could possibly be made from the value
of the ratio of the relative reflectance from two channels
of a multispectral scanner.
MATERIALS AND METHODS
Plot design and layout were described by Stoner (1972,
Multispectral determination of vegetative cover in corn crop
canopies, M.S. Thesis, Purdue University, W. Lafayette,
Indiana). A set of 12 ground-cover plots were laid out
near the Purdue University Agronomy Farm's Weather Station
on a light colored, Russell silt loam soil. The Pioneer
3369A maize variety was planted in three replications on
four planting dates.
Two flight missions by the University of Michigan's
airborne multispectral scanner were used in this study.
» .
The flight «'r.th *** both missions was a north-south flight-
line directly over the Purdue University Agronomy Farm's
Weather Station. Maize plots of various ground covers
planted on a Russell silt loam soil were located in the
flight path in close proximity to the weather station.
July 12 and July 21, 1971 were the dates for the two
scanner overflights. The July 12 flight was at 1401 hours
EST while the July 21 flight was at 1305 hours EST. Both
overflights were at an altitude of 305 m and both took
place on clear, cloud-free days.
The University of Michigan's multispectral scanner
collected spectral data in the 0.46 to 2.50 ym reflective
wavelength range. Table 1 lists the 11 channels of reflec-
tive data collected by the University of Michigan scanner
and the corresponding wavelength bands. The aircraft
scanner data were recorded in analog form and converted to
a digital format for analysis by the LARSYS processing
system (LARS, 1968 and 1970). The two flightlines of
interest were digitized at a sample rate of 450 samples
per scan line of data. This meant that every scan line of
analog scanner data was sampled in the digitization process
Each resolution unit represented an area about 1m by 1m on
the ground.
The approximate area of the Russell plots was deter-
mined from the display of the digitized scanner data on
the LARS Digital Video Display Unit. This area was then
clustered (Wacker and Landgrebe, 1970) and the exact loca-
tion of the individual Russell plots was determined from
the resulting cluster array map. Each subplot was slightly
larger than 4 by 4 ground resolution units or data points.
A square block of four data points was selected from the
northeast portion of each subplot in order to estimate
any shadowing effects from bordering subplots. Statistics
on mean scanner data values were then obtained from these
data blocks for all of the subplots on both dates of
scanner overflights.
. 8
The wavelength band configuration of the University of
Michigan scanner was changed from that used in previous
years. The chlorophyll absorption band for this study fell
in the 0.61 to 0.70 jim wavelength range of channel 7. Two
near infrared wavelength bands were now available in the
region of high reflectance of green vegetation: t^he 0.72
to 0.92 urn wavelength band of channel 8, and 1.0 to 1.4 ym
wavelength band of channel 9.
Ratios of scanner data values were calculated by
dividing the scanner data values from channels 8 or 9 by
the scanner data values from channel 7 (hereafter referred
to as the ratios of channels 8/7 or 9/7). These ratios
*
were then plotted against leaf area index, as measured at
the time of the overflights. Stepwise multiple regression
analysis was run on the data to see if either of the two
ratios of near infrared to red wavelength scanner data
response could be related to leaf area index (the ratios
were reversed from those mentioned in previous studies for
ease in data manipulation).
RESULTS AND DISCUSSION
The ratios of scanner data values in channels 9/7
for the July 12 and July 21 flight dates were plotted
against leaf area index (Figure 1). The points seemed
to indicate that a rather good relationship existed
between the ratio of scanner data in channels 9/7 and LAI.
A stepwise multiple regression analysis indicated that
96.81 of the variation about the mean LAI could be explain-
*
ed by the second order regression equation, Y * 1.0751 -
2.8756X + 1.944X2, where X is equal to the ratio of scanner
data values in channels 9/7. This indicated that ratios
»
of multispectral scanner data may, as hoped for, be related
to some ground based measurement of canopy density. The
ratios of scanner data values for both dates compared quite
well even without any calibration of scanner response
between the two dates.
It was expected that the ratios of scanner data values
in channels 8/7 should also show a good relationship with
LAI. The ratios of scanner data values in channels 8/7
for the July 12 and July 21 flight dates were plotted in
Figure 2. It was obvious that two separate relationships
'existed for the two multispectral scanner flights. Step-
wise multiple regression analysis indicated that 98.lt of
the variation of LAI could be explained by the second order
A
regression equation, Y * -0.48754 * 1.26899X2, where X
equals the ratio of scanner data values in channels 8/7 .
for the July 12 scanner flight. For the July 21 scanner
flight a linear relationship was indicated which was able
to account for 93.0* of the variation in LAI. The regres-
sion equation for July 21 was Y - -2.46111 «• 2.18245X,
where X equals the ratio of scanner data values in channels
8/7 for the July 21 scanner flight.
A relationship did seem to'exist between the ratio of
scanner data values in channels 8/7 and, LAI, but the same
relationship did not hold between flight dates. Apparently
a change had taken place between July 12 and July 21 in
the way in which the multispectral scanner was recording
data in channel.8. This indicated the need for calibrated
scanner data for comparisons over time (between flight
dates).
11
SUMMARY AND CONCLUSIONS
Multispectral scanner data from maize canopies provide
more quantitative spectral information on canopy density
tan does photography. Ratios of uncalibrated scanner data
can be used within a given scanner mission to estimate
changes in vegetative cover as measured by leaf area index.
The peak reflectance wavelengths for green vegetation (0.72
to 1.3 jim) and the region of strong chlorophyll absorption
(0.65 nm) seem to provide the best information on changing
ground cover. .
Regression equations can be evolved relating leaf
»
area index in maize canopies to the ratios of scanner data
values from channels 8 and 9 (0.72 to 0.92 ym and 1.0 to
1.4 ym). These relationships are strong within a given
scanner flight, but can only be extended between flight
dates when the investigator is certain that there were no
changes in scanner system gain settings between flights.
LITERATURE CITED
1. Baumgardner, M. P., S. J. Kristof, C. J. Johannsen, and
A. L. Zachary, 1969. Effects of organic matter on the
multispectral properties of soils. Proc. of the Indians
Acad. of Sci. 79:413-422.
2. Bowers, S. A., and R. J. Hanks. 1965. Reflectance of
radiant energy from soils. Soil Sci. 100(2):130-1S8.
3. Cipra, J. B., M. F. Baumgardner, E. R. Sterner, and R.
B. MacDonald. 1971. Measuring radiance characteris-
tics of soil with a field spectroradiometer. Soil Sci.
S,oc. Amer, Proc. 35:1014-1017.
4. Condit, H. R. 1970. The spectral reflectance of
American soils. Photogrammetrie Engineering. 36:955-
966.
5. Gates, D. M., H. F. Keegan, J. C. Schleter, and V. R.
Weidner. 1965. Spectral properties of plants. Appliec
Optics. 4:11-20.
6. Hoffer, R. M., and C. J. Johannsen. 1969. Ecological
principles in spectral signature analysis. In Remote
Sensing in Ecology. Univ. of Georgia Press, P.
Johnson (ed.), Athens, GA. pp. 1-16.
7. Knipling, B. B. 1970. Physical and physiological
basis for the reflectance of visible and near-infrared
radiation from vegetation. Remote Sensing of
Environment. 1:155-160.
8. Laboratory for Agricultural Remote Sensing (LARS).
1968. Remote Multispectral Sensing in Agriculture.
Vol. Ill (Annual Report). Purdue Univ. Exp. Sta. Res.
Bull. 844, pp. 53-58.
9. Laboratory for Agricultural Remote Sensing (LARS).
1970. Remote Multispectral Sensing in Agriculture.
Vol. IV (Annual Report). Purdue Univ. Agr. Exp. Sta.
Res. Bull. 873. pp. 80-86'.
10. Myers, V. I., C. L. Wiegand, M. D. Heilman, and J. R.
Thomas. 1966. Remote Sensing in soil and water con-
servation research. Proceedings of the Fourth
Symposium on Remote Sensing of Environment. Univ. of
Mich., Ann Arbor, MI. pp. 801-813.
11. Myers, V. I. 1970. Soil, water, and plant relations.
In Remote Sensing with Special Reference to Agriculture
and Forestry. National Academy of Sciences, J. R.
Shay (ed.), Washington, D. C. pp. 253-297.
12. Wacker, A. G., and D. A. Landgrebe. 1970. Boundaries
in multispectral imagery by clustering. Proceedings
of the Ninth IEEE Symposium on Adaptive Processes XI.
pp. 4.1-4.8.
TABLE 1. THE 11 REFLECTIVE
WAVELENGTH BANDS
CHANNELS AND CORRESPONDING
FOR THE UNIVERSITY OF MICHIGAN
MULT I SPECTRAL SCANNER.
Limits of Spectral Bands
Channel
1
2
3
4
S
6
7
8
9
10
11
Lower
0.46
0.48
0.50
0.52
0.54
0.58
0.61
0.72
1.00
1.50
2.00
Upper
0.49
0.51
0.54
0.57
0.60
0.65
0.70
0.92
1.40
1.80
2.60
(pro)
Wavelength Region
visible
visible
visible
visible
visible
visible
visible
near infrared
near infrared
near infrared
near infrared
<
_J
X
0)
TJ
~ 2
a
0
T
0 = July 12 Flight
X=July 21 Flight
i -
Y=I.075I-2.8756X+ I.9442X2
w «_*• /Channel 9 \
where X = Ratio (—• —)\Chonnel 7 /
R2«0.968
Ratio /Scanner data value in channel 9V Scanner data value in channel 7
Figure 1. Leaf area index versus the ratio of scanner data
values in channels 9/7 for two flight dates.
X
0>
_c
o
w.
<
o
a>
= July 12 Flight
X= July 21 Flight
0,
Y« -0.48754-H.26899X2
where X= Ratio
. /Channel 8 \
10
 \Channel 7/
R2 = 0.981
Y=-2.46!I(H-2.I8245X
Channel
where X= Ratio ({hanne|
R2 = 0.930
Ratio Scanner data value in channelScanner data value in channel
Figure 2. Leaf area index versus the ratio of scanner data
values in channels 8/7 for two flight dates.


Determining density of maize canopy. 2: Airborne multispectral scanner data

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