The view angle effect in LANDSAT 2 imagery was investigated. The LANDSAT multispectral scanner scans over a range of view angles of -5.78 to 5.78 degrees. The view angle effect, which is caused by differing view angles, could be studied by comparing data collected at different view angles over a fixed location at a fixed time. Since such LANDSAT data is not available, consecutive day acquisition data were used as a substitute: they were collected over the same geographical location, acquired 24 hours apart, with a view angle change of 7 to 8 degrees at a latitude of 35 to 45 degrees. It is shown that there is approximately a 5% reduction in the average sensor response on the second-day acquisitions as compared with the first-day acquisitions, and that the view angle effect differs field to field and crop to crop. On false infrared color pictures the view angle effect causes changes primarily in brightness and to a lesser degree in color (hue and saturation). An implication is that caution must be taken when images with different view angles are combined for classification and a signature extension technique needs to take the view angle effect into account

Engvall, J. L.

Kaneko, T.

English

NASA Technical Reports Server

N78-14542
VIEW ANGLE EFFECT IN LANDSAT IMAGERY*
Toyohisa Kaneko
IBM Corporation
Federal Systems Division
Houston, Texas 77058
and
John L. Engvall
National Aeronautics and Space Administration
Johnson Space Center
Houston, Texas 77058
ABSTRACT
The objective of this paper is to investigate the view angle effect in LANDSAT
II imagery. The LANDSAT multi-spectral scanner scans over a range of view
angles of -5.78 to 5.78 degrees. The view angle effect, which is caused by
differing view angles, could be studied by comparing data collected at different
view angles over a fixed location at a fixed time. Since such LANDSAT data is
not available, consecutive day acquisition data were used as a substitute: they
were collected over the same geographical location, acquired 24 hours apart,
with a view angle change of 7 to 8 degrees at a latitude of 35 to 45 degrees.
The study will show that there is approximately a 5% reduction in the average
sensor response on the second-day acquisitions as compared with the first-day
acquisitions, and that the view angle effect differs field to field and crop to
crop. On false infrared color pictures the view angle effect causes changes
primarily in brightness and to a lesser degree in color (hue and saturation).
An implication of this study is that caution must be taken when images with
different view angles are combined for classification and a signature extension
technique needs to take the view angle effect into account.
I. INTRODUCTION
A multi-spectral scanner (MSS) measures the ground radiance by varying its view
angle across the flight path of its carrier. Sensor outputs are dependent upon,
among other things, the instantaneous view angle corresponding to each output.
The effect caused by differing view angles is called the view angle effect or
the scan angle effect. The objective of this papper is to investigate the view
angle effect in the LANDSAT II MSS**. The LANDSAT MSS scans a swath of 185km
width on the ground from a height of 920km, so the view angle varies between
-5.78 and 5.78 degrees.
Some of the previous work on view angle effect are reported in the following.
Reflection properties of natural objects such as clay, sand, soil, and grass
turf at varying view angles and zenith angles were studied by Coulson et al.
Cl,23 in the laboratory environment. Smedes et a_l.C3D investigated the view
angle effect in the imagery acquired over the Yellowstone National Park area by
an airborne 12-channel scanner whose view angle varies from approximately minus
40 degrees to plus 40 degrees. They introduced a normalized scan-angle function
in order to reduce the view angle effect. Their results indicate that the view
angle effect is larger near the nadir (zero degrees) than at the larger view
angles.
This paper documents an investigation of the view angle effect in the LANDSAT
MSS based on analysis of its imagery. This task could be performed by com-
paring data collected at different view angles over a fixed location at a fixed
*This work was done under NASA contract NAS9-14350.
** Note that the results of this investigation are applicable to the LANDSAT I
data because the two MSS's are identically designed.
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https://ntrs.nasa.gov/search.jsp?R=19780006599 2020-03-22T05:46:25+00:00Z
time. However, such LANDSAT data is not available. Consecutive-day acquisi-
tion data were used as substitutes. Due to the LANDSAT orbit a certain portion
of a LANDSAT full frame (185km by 185km on the ground) is also seen in a frame
acquired on the next day C4,53.Total view angle changes between consecutive-day
acquisitions, which depend upon the latitudes of the ground area, are in the
range of seven to eight degrees at latitudes of 35 to 45 degrees. Little at-
tention to the view angle effect in the LANDSAT MSS has been paid in the past,
possibly due to a common belief that such a small view angle variation would
not affect the imagery. In this paper it will be shown that the effect is
larger than expected. Moreover an attempt will be made to assess its rough
order of magnitude.
II. MEASUREMENTS
One hundred and one consecutive-day acquisition pairs of LANDSAT subframes were
used in this study. Each subframe consists of 117 scan lines by 196 pixels,
covering an area of 9.0km by 10.8km on the ground. Among these frames there are
35 pairs of consecutive-day acquisition pairs which are 18 days (or one LANDSAT
cyclic period with respect to the ground) apart (e.g. acquisitions on May 2, 3,
20, and 21). All the images are agricultural scenes from the United States and
were acquired between April and August. The sun angles corresponding to the
data are between 35 and 60 degrees. All images were screened visually and con-
tain neither clouds nor visible haze.
The geometric registration of the imagery was assessed using a specially devel-
oped IMAGE REGISTRATION PROGRAMC6] for all acquisitions of the same location.
The computed misregistration measurements (Ax,Ay) were rounded to the nearest
integers and a simple shifting correction for misregistration was applied by
these integer values along the scan line (Y direction) and/or the pixel direc-
tion (X direction). To further reduce the effect of misregistration, each
frame (117 by 196) was smoothed by averaging and rounding the values in five
scan line by five pixel areas, resulting in a 23 by 39 matrix.
Then scatter plots were made in the following manner. After the smoothing and
rounding mentioned above are performed, two 23 by 39 integer matrices for the
first-day and second-day acquisitions are obtained. A counter array, dimen-
sioned 90 by 90 is defined and initialized to zero. The counters in the array
are then incremented based on the values of geographically corresponding en-
tries in the two matrices. If an entry pair for the first-day and the second-
day acquisitions are 50 and 45, for instance, then the content of the counter
at (50, 45) is incremented by one. This procedure is carried out for all 897
entry pairs from the two matrices. The final content of the counter array
constitutes a scatter plot of the data. Resulting scatter plots are displayed
as follows: the maximum counter value is found1 and the range from 0 to the max-
imum is divided into 10 equal ranges, which are denoted by ., 1, 2, ..., 9 in
ascending order and are used in representing the scatter plot on a line printer.
Blanks are used to represent null contents.
Since the LANDSAT MSS has four channels, four scatter plots were made for each
consecutive-day acquisition pair. However, only the results for channel 3 will
be shown because (1) all the four plots are fairly similar, (2) the effect of
atmospheric conditions such as haze in channel 3 imagery is less than in chan-
nels 1 or 2, and (3) the effect of soil moisture in channel 3 imagery is less
than in channel 4 imagery.
Figures l(a), (b), and (c) show scatter plots made from three pairs of consecu-
tive-day imagery on June 20 and 21, July 8 and 9, and July 26 and 27, respec-
tively, from an area of 9.0km by 10.8km in Idaho. (It is extremely rare to have
six straight acquisitions without clouds.) The diagonal line indicated by a
series of '+' represents the y=x line. A scatter plot should be interpreted as
follows: Consider x=50, for instance, in Figure l.(a). The range in y is from
44 to 49. So areas with count 50 in the first-day acquisition imagery had
changed to counts of from 44 to 49 on the next day. It is reasoned that this
scattering is primarily due to the view angle effect.
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Prom these scatter plots it is observed that the majority of points are below
the y=x line. That is, sensor outputs are generally smaller on the second day.
This observation was confirmed by examining the 101 consecutive-day acquisitions
mentioned earlier. Figure 2 shows a scatter plot where the x and y axes repre-
sent the entire subframe means on the first day and the second day, respectively.
The least square solution y=.95x was obtained. In other words there is a re-
duction of 5% in average sensor outputs from the first day to the second day
acquisition. The following is a possible explanation of this phenomenon.
On the first of the two days the sensor and the sun are both on the same side
of the area that is common in consecutive-day imagery (see Figure 3(a)) so that
the sunny side of standing objects is seen from the MSS. On the otherhand, on
the second of the two days the sensor and the sun are on opposite sides of the
common area (see Figure 3(b)) so that more of the shady side of standing objects
is seen. If'this explanation is correct, the view angle effect will be depen-
dent upon such factors as shapes of objects, leaf orientation, spaces and
materials between objects as well as sun angles.
Therefore the view angle effect for spaced standing objects such as trees and
corn plants is reasoned to be different than that for objects with smooth sur-
faces such as lakes and soil. This is illustrated in an example shown in
Figure 4.
The scatter plot is made from acquisitions on August 6 and 7 from an area in
the state of North Dakota. There are 6 large lakes, which cover approximately
5% of the entire area. Generally, counts below 25 are from these lakes. It is
seen that counts from the lakes increased on the second day while those from
other objects decreased slightly. It is generally observed that counts from
lakes tend to increase on the second day which is consistent with expectations
because of mirror image reflectance of the sun off the water.
To study the behavior of each field, 20 fields were defined on the acquisitions
used in Figures l(a), (b), and (c) (see Figure 5). Temporal trajectories of
ten fields are shown in Figures 6 (a), (b) , where x and y axes represent the
field means of channels 2 and 3, respectively. (The trajectories for the re-
maining 10 fields were not plotted because they overlap with the above.) It is
seen that temporal trajectories make zigzag motions when acquisitions with dif-
ferent view angles are mixed. This means that signatures are dependent upon
view angles. Therefore caution is recommended when acquisitions with different
view angles are mixed for any signature extension schemes.
On Figures 6(a) and 6(b) it is also observed that the trajectory on the second
day moves toward the origin as expected due to lower values in both channels.
This trend was also observed in channels 1 and 4 imagery. In other words, the
change between consecutive day acquisitions is roughly proportioned in all
channels. If false color infrared films are made for consecutive day acquisi-
tion pairs, they will look similar in color (hue and saturation) but differ
slightly in brightness. After channel-to-channel ratio processing discussed by
Smedes et 3.1.C3D images would be generally free from the view angle effect.
III. DISCUSSIONS
There are other possible causes to explain differences observed between con-
secutive day acquisitions. They include:
(1) Effect due to precipitation - rain (possibly shower) may fall during
a period of 24 hours.
(2) Effect due to moisture change - sunshine and wind may dehydrate soil
and vegetation, altering reflectance.
(3) Effect of leaf orientation change due to wind.
(4) Effect due to scene change by irrigation, plowing and harvesting.
(5) Sensor noise and misregistration.
The degree of effects brought by these causes, except 5, differs from plant to
plant or field to field. When a large number of cases are considered, all the
above causes seem to act in a random fashion with zero bias. It seems to be a
fair conclusion to say that the average of 5% reduction observed from the
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first-day to the second-day acquisition can be attributed solely to the view
angle effect. For a particular consecutive acquisition pair we are unable to
assess the relative magnitude of the view angle effect to the above effects
although we believe the view angle effect is dominant.
However the above does not imply the existence of uniformly applicable view
angle correction functions. As was seen in Figures l(a), (b), and (c), the
magnitude of the random unpredictable variability is generally larger than that
of the predictable variability (i.e. 5% reduction). Also as are seen in Figures
4, 5(a), and 5(b), the differences between consecutive day acquisition pairs
are dependent upon types of fields and vegetation. Therefore it can be said
that there are no uniformly applicable view angle correction functions for the
view angle range of plus 3 to 4 degrees to minus 3 to 4 degrees. This is not
contradictory to the result of Smedes et al. £3], because the view angles of .
their MSS changed plus 40 degree to minus 40 degree. A view angle correction
function can be used to grossly normalize imagery data for such a large view
angle change.
REFERENCES
(1) K. L. Coulson, G. M. Bouricius, and E. L. Gray, "Optical Reflection
Properties of Natural Surfaces", J. of Geophysical Research, Vol. 70,
No. 18, September 15, 1965, pp 4601-4611.
(2) K. L. Coulson, "Effects of Reflection Properties of Natural Surfaces in
Aerial Reconnaissance", Applied Optics, Vol. 5, No. 6, June 1966,
pp 905-917.
(3) H. W. Smedes, M. M. Spencer and F. J. Thomson, "Preprocessing of Multi-
spectral Data and Simulation of ERTS Data Channels to Make Computer
Terrain Maps of A Yellowstone National Park Test Site", Proceedings of
the Seventh International Symposium on Remote Sensing of Environment,
published by Environmental Research Institute of Michigan, University of
Michigan, 17-21 May, 1971, pp 2073-2094.
(4) "Data Users Handbook - NASA Earth Resources Technology Satellite", NASA
Goddard Space Flight Center, No. 71SD4249, Nov. 17, 1972.
(5) "ERTS Reference Manual/ERTS-2", Space Division, General Electric, Valley
Forge Space Center.
(6) T. Kaneko, "Evaluation of LANDSAT Image Registration Accuracy", Photo-
grammetric Engineering and Remote Sensing, Vol. 42, No. 10, October 1976,
pp. 1285-1299.
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Figure l(a)
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Figure l(b)
Figure l(c)
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Figure l(a) Scatter plot where x and y
represent means over 5 scan
line and 5 pixel areas on
the channel 3 imagery
acquired on June 20, and
June 21, respectively.
Figure 1(b) Scatter plot where x and y
represent means over 5 scan
line and 5 pixel areas on
the channel 3 imagery
acquired on July 8 and July
9, respectively.
Figure 1(c) Scatter plot where x and y
represent means over 5 scan
line and 5 pixel areas on
• the channel 3 imagery
acquired on July 26, and
July 27, respectively.
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10 20 30 40 50 I
SUBFRAME MEANS (FIRST DAY ACQUISITIONS!
Figure 2 Scatter plot showing a 5% re-
duction in average sensor
response on the second-day
acquisitions as compared with
the first day acquisitions.
Figure 3(a)
Figure 3(a)
Figure 3(b)
Figure 3 (b)
Geometry of the sun,
ground objects (trees),
and the MSS for first-
day acquisitions.
Geometry of the sun,
ground objects (trees),
and the MSS for second-
day acquisitions.
Figure 4 Scatter plot made from a
consecutive-day acquisi-
tion pair where 6 lakes
constitute approximately
5% of the total subframe
area. Note that counts
below 25 are from these
lakes.
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Figure 5 Channel 2 imagery of the subframe area used
for Figures 1 (a) , (b) , and (c) with 20
fields overlayed.
Figure 6(a) Figure 6(b)
30 X »0 SO
Figures 6(a) and (b) Temporal trajectories of ten fields (1 = June 20,
I1 = June 21, 2 = July 8 , 2 ' = July 9, 3 = July 26,
and 3' = July 27).
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View angle effect in LANDSAT imagery

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