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Eagleman, J. R.

Hardy, N.

Parashar, S.

English

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Detection of Moisture and Moisture Related
Phenomena from Skylab
Joe R. Eagleman
Principal Investigator
(E74-10684) DETECTION OF OISTRE AND N74-30676OISTgRE RELATED PHENOMENA FROMj SKYLAB36
Monthly Progress Report, Jul. 1974
(Kansas Univ. Center for Research, Inc.)Unclas17 p HC $4.00 U nclas
CSCL 08H G3/13 00684
Monthly Progress Report, July, 1974
Atmospheric Science Laboratory
Center For Research, Inc.
University of Kansas
https://ntrs.nasa.gov/search.jsp?R=19740022563 2020-03-23T04:29:19+00:00Z
Detection of Moisture and Moisture Related
Phenomena from Skylab
Joe R. Eagleman
Principal Investigator
Norman Hardy and Surendra Parashar
Graduate Research Assistants
Atmospheric Science Laboratory
Space Technology Center
Center for Research, Inc.
University of Kansas in
Lawrence, Kansas -66045
Clayton D. Forbes, Technical Monitor
Principal Investigations
Management Office
Lyndon B. Johnson Space Center
Houston, Texas 77058
EREP NO.540-A2 March 19, 1973 'to August 31, 1974
Contract Number NAS 9-13273
COMPENSATIONS OF RADIOMETRIC
DATA FOR CLOUD COVER
An attempt is being made to compensate the radiometric
antenna temperature as measured by S193 for the areas where
cloud cover occurred. It was shown by Wu (1973) that the
effect of cloud cover depends on the density and the type
of the cloud. An analysis of the amount and type of clouds
over the individual S193 footprints has been completed for
the June 5.pass over Texas, Figure 1, as described in the
May progress report. Cloud cover varied from none to al-
most 100% heavy cloud cover as extracted from the S190A
photography. The influence of cloud cover on the S194
radiometric temperatures are probably negligable, but
should slightly increase the correlation of the'S193 data
with soil moisture content. For the cases where cloud
cover exists , corrections can-be made by modification to
developed methodology, Wu (1973) or by the techniques
described by Benoit (1968).
EFFECT OF ANTENNA PATTERN
An attempt is being made to find the effect of anten-
na pattern of S194 L-band radiometer on the antenna temp-
erature measurement. The S194 sensor has a 150 half-
power beam width. This implies that 50% of the energy re-
ceived by the antenna will be received in the 150 solid
pyramid centered about the vertical axis. The antenna
2.<
MOPEN WATER TEXAS SITE S-193 6/5/73
E LIGHT CLOUDS
HEAVY CLOUDS
Gogo0 40
18 20 22 36 48 62
64 88 112. L14 140 168
212 214 226 250 286 288
312 314 338 358 381 396
398 426 430 440 442
Fiqure 1
will receive over 90% of the energy available in the field
of view in a 360 solid pyramid. Both of these angles are
contained in the primary lobe of the antenna. The 360
angle will encompass a swath width of approximately 144 nmi
at the 234 nmi orbital altitude. The radiometer antenna
temperature recorded by the sensor will be influenced to a
greater extent.by the brightness of the material contained
within the 150 beam width.
The sampling of the radiant energy received by the
antenna was done at a rate to ensure a minimum of 97%
ground coverage overlap. The distance on the ground be-
tween the centers of two consecutive resolution cells is
about 2 nmi. Because of such a small distance, the dif-
ference.in the radiometric antenna temperature between
two consecutive cells may be due to random fluctuations
due to noise rather than to any changes in ground emis-
sion. Thus, for a meaningful analysis, it is important
to establish the effect of antenna pattern to show at what
distance ground effects begin to predominate over those of
the noise.
An attempt is being made to find out what type of
ground variation, as a function of time, is required to
produce the radiometric data. If g(t) is the ground
temperature as a function of time (i.e. surface brightness
temperature as a function of distance or time), a(t), the
antenna pattern as a function of time, and w(t) as some
4< 3
type of window function or distorting factor, then the data
d(t) (radiometric measurement as a function of time) is
given by:
d(t) = a(t) * [g(t)w(t)]
where * implies convolution. Taking the Fourier transform
of above we find:
D(f) = A(f) [G(f) , W(f)]
G(f) * W(f) = H(f) = D(f)/A(f)
where g(t) is the inverse Fourier transform of G(f). An
attempt shall be made to see ifit. i-spossible to obtain
a better g(t) for S194 radiometer by suitable choice of
w(t). A similar attempt shall be made in finding the
effect of S193 antenna pattern.
VEGETATION AND LAND USE
In order to understand the contribution of vegetation
to Skylab measurements, recent research has also been dir-
ected toward the preparation of a vegetation, land-use
type map of the western Texas site. This map is being pre-
pared from the S190A and S190B vertical color photography
and from ground truth photographs taken during the soil
moisture sampling missions. To date, only the map rep-
resenting the June 5, 1973 test area has been completed
(Figure 2). Table I describes in some detail vegetation
characteristics of each category on the map.
5<4
6 5
4a4 a56
8¢ 8
3SS
33 4-
Figure 2 . Vegetation type map of the June 5, 1973 Texas test site. Numbers
refer to map categories and are referenced to Table .
TABLE I
Texas Test Site
June 197
Vegetation-Land Use
Map UNESCO Description
Category Formula
1 V-D-2b Dominantly bare ground, some emer-
gent shoots of cotton and grain
sorghum less than 5 cm in height.
la V-D-2b Same as above; variations due to
soil type differences.
2 V-C-3c Short grassland; dominant gram-
inoid growth forms are less than
50 cm tall. Woody synusia of
shrubs covering less than 10% of
the area.
3 V-C-6a Short grass communities practic-
ally without woody synusia.
4 V-B-3c Medium tall grassland; dominant
graminoid growth forms are 50 cm
to 2 m tall; woody synusia of
broad leaf deciduous shrubs cover-
ing 10%46-iless.
4a V-B-3c(1) Same as above, but total plant
coverage per;unit area is sig-
nificantly less.
5 V-D-2b(2) Mainly anual low forb communities
less than 1 m tall.
6 V-B-3c(2) Medium tall grassland; dominant
graminoid growth forms are 50 cm
to 2 m tall; woody synusia of
broad leaf deciduous shrubs cover-
ing 10-40%
7 III-C-2a Xeromorphic (sub-desert) shrubland
without succulents. Open stands
of shrubs with various xerophytic
adaptions. Mainly less than 2
meters tall.
7<
TABLE I (cont.)
Map UNESCO Description
Category Formula
8 III-B-3a(1) Temperate deciduous shrubland.
Moderately dense scrub with
more or less continuous grass
under story. Shrubs 2 to 3 m
tall. Grass less than 50 cm tall.
9 III-B-3a(2) Temperate deciduous shrublen.
Essentially the same as category
8, but the percentage of shrub
coverage is lower and individual
plants are more widely separated.
9a III-B-3a(3) Same as above, but much less
total vegetative cover, i.e., more
bare soil.
S Bare saline soils, often found in
dry channel or depressions.
W Water.
U Urban.
8<
The vegetation of the test area is classified according
to the methods established in the International Classification
and Mapping of Vegetation (UNESCO, 1973). The categories
used in the classification are units of vegetation, including
both zonal formations and the more important and extensive
azonal and modified formations. The system is based upon
vegetation physiognomic rather than floristic considerations
and considering the nature of the Skylab project to which it
is applied, this is quite appropriate.
Supplementary terms referring to climate;. soil and land-
forms are included in the names and occasionally in the def-
initions, where they help the identification of a given unit.
Although most units are defined physiognomically, they broad-
ly indicate environmental conditions.
Considering the specific details, the classification
is :divided into five major categories: (i) Closed Forest,
(ii) Woodland, (iii) Scrub, (iv) Dwarf-Scrub and Related
Communities, (v) Herbaceous Vegetation.
Figure 3 is the same map except that those S193 foot-
prints for which soil moisture data are available have been
superimposed on the land-use, vegetation categories. The
relative amouhts of each vegetation type within each foot-
print are given in Table II. The percentage of each type
of vegetation within each footprint was determined by
utilizing a Hewlett-Packard calculator-digitizer system.
This simply involves entering a numerical integration
9C8
46& 1
1L7 5
4 8-
07
5 4
3 3 14
3114
o4o
Figure 3 . Vegetation type map of the June 5, 1973 Texas test site showing
the relative position of the S193 footprints for which soil moisture
information is available. The footprint numbers correspond to those
of Table I .
TABLE II
Footprint Map Percent
Number Category Coverage
18 1 100
20 1 100
22 1 100
36 S 4
W 8.2
1 87.8
48 1 48.6
4 51.4
62 1 29.1
4 70.9
64 1 82.2
4 17.8
88 1 96.4
4 3.6
112 4a 60.2
6 39.8
114 1 20.7
4a 68.7
6 10.6
140 6 11.9
cloud 88.1
168 1 7.5
6 19.6
cloud 72.9
212 1 30.2
cloud 69.8
214 1 11.2
6 88.2
226 1 88.0
la 12.0
250 1 86.4
la 13.6
286 1 23.9
8 76.1
11<
program into the programable calculator which allows contin-
uous sampling by the digitizer. Digitizing is done on a sen-
sitive surface in order that continuous coordinates can be
read off and fed into the calculator. When the digitizer is
returned to the starting point, a display appears which re-
presents the enclosed area. This is then readily convertible
to square miles, kilometers or any appropriate aerial meas-
urement or simply to percent coverage as has been done in
this case.
Since the area was classified from satellite photo-
graphy, areas under heavy clouds have not been classified;
therefore, the map is incomplete with respect to the total
test strip. Although they are not complete at this time,
similar maps are being produced for the other data sets in
Texas and Kansas.
In addition to plotting the S193 footprints on these
maps, S194 footprints were plotted and categorized in pre-
paration for further analysis of the contribution of veg-
etation to the S194 measurements, Figure 4. The footprint
was taken to be a circle of 60 nautical miles in diameter.
Table III lists the footprint numbers, categories with-
in each footprint and percentage of each footprint occupied
by each category. The key to the categories is to be found
in Table I
As in the case of the S193, not all footprints for the
pass have been considered. This is due to the fact that
13I
TABLE III
Footprint Categories Percent Footprint -- Categories Percent
Number Present Coverage Number Present Corag
1 3 2.49 7 s 0.21
3s 0.96 U 1.06
1 82.7294 W 0.15
2 12.93
s 0.26 8 1 88.1675U 0.63 2 5.13
3 0.2832 1 83.2419 .
2 11.65 4 2.573 2.23 4a 2.39
6 0.033s 0.84 6 0.03
s 0.998 U .06
U' 1.05 s 0.21W 0.15
3 1 83.30 9 1 86.4938
2 11.95 8
3 2.21 2 3.56
3s 03 0.283s 0.72 4 2.57
s 0.72 4a 4.42
4 0.49 5 0.29
4a 0.16 6 -. 0.96
U 1.06 s 0.21
U 1.064 1 82.6800 W 0.15.06
2 11.66 0.15
3 2.21 10 1 82.8588
s 0.49 2 2.31
W 0.1513 3 0.283
U 1.06 4 2.57
4 1.47 4a 7.92
4a 0.28 5 0.50
6 2.13
5 1 13.00 s 0.2121 .8s 0.21
2 10.68 U 1.063 1.54 W 0.15
4 2.57
4a 0.512 11 1 77.8931
s 0.49 2 1.50
U 1..06 3 0.2831
W 0.15 4 2.57
4a 11.67
6 1 84.6419 .6
2 '9.53 5 0.76
3 1.06 6 3.78
4 2.57 7 0.384 2.57 U 1.06
4a 0.77 s 1.21
s 0.21 W 0.15
U 1.06 0.15
W 0.15 12 1 73.4000
1 87.2119 2 0.63
7 1 87.002119 3 0.04
2 7.00 4 2.57
3 0.53 4a 14.8857
4 2.57 4a5 014.88
4a 1.27 5 0.88
13<
TABLE III (cont.)
Footprint Categories Percent Footprint Categories Percent
-Number Present Coverage Number Present Coverage
12 6 5.80 17 1 41.4269
7 0.38 2 2.76
U 1.06 4 3.65
s 0.,21 4a 21.80
W 0.15 6 21.14
7 1.50
13 1 65.52 S 0.15
2 2.76 W 0.13
4 2.57 C 7.43
4a 17.79
5, 0.88 18 1 40.1644
6 7.61 2 0.09
7 0.57 4 3.65
S 0.21 4a 19.92
U 106 6 23.54
W0.15 7 1.50
Cloud 0.88 9 _0.57
W 0.16
14 1 60.4119 C 10.40
2 2.76
4 2.57 19 1 35.225
4a 20.07 4 3.54
5 0.61 4a 18.83
6 8.79 6 26.03
7 0.91 7 1.50
d 0.21 9 1.60
U 0.96 W 0.16
W 0.15 C 13.12
C 2.57
20 1 35.1013
15 1 59.6688 4 2.59
2 2.76 4a 17.48
4 2.57 6 27.00
4a 17.33 7 1.50
5 0.40 9 1.30
6 11.03 W 0.16
7 1.22 C 14.87
S 0221
U 0.25 21 1 32.3206
W 0.15 4 1.42
C 4.41 4a 16.10
6 29.69
16 1 64.7681 7 1.59
. 2 2.76 9 2.44
4 3.65 W 0.16
4a 21.58 C 16.37
5 0.10
6 17.04 22 1 30.2006
7 1.22 la 0.36
W 0.13 4 1.33
S 0.21 4a 14.95
C 6.55 6 32.9575
14<
TABLE III(cont.)
Footprint Categories Percent
Number Present Coverage
22 1 30.2006
la 0.36
4 1.33
4a 14.95
6 32.5975
7 1.25
9 2.62
W 0.16
C 16.5406
23 1 28.0350
la 1.08
4 0.27
4a 14.2419
6 33.7525
7 0.96
8 0.11
W 0.16
C 17.4475
9 3.66
24 1 26.7919
la 1.96
4a 12.7113
6 34.6931
7 0.66
8 0.82
9 4.14
W 0.16
C 18.0650
25 1 24.8231
la 3.0825
4a 10.1244
6 37.1956
8 1.87
9 4.1481
W 0.16
C 18.59
15<
the S190B data base is partially cloud covered. Further
information will be filled in from other sources such as
ERTS photography,however, to complete the classification.
REFERENCES
Benoit, Andre, "Signal Attenuation Due to Neutral Oxy-
gen and Water Vapor, Rain and Clouds", The Micro-
wave Journal, vol. 11, no.11, pp. 73-80, November,
1968.
International Classification and Mapping of Vegeta-
tion';UNESCO, Paris, 1973, 93pp..
Wu, Steve, "The Meteorological Effects on Microwave ap-
parent Temperatures Looking Downward over a Smooth
Sea", The University of Kansas Center for Research,
Inc., Lawrence, Kansas, 1973. (NAS-CR-2325)
15


Detection of moisture and moisture related phenomena from Skylab

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