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Title
Remote sensing for resources development and environmental management
Author
Damen, M. C. J.

arly indepen-
thonormal set
calculated by
Jering, 1963)
's representa-
egetation and
s from satel-
' standardized
extracted for
îlues together
re stored for
the present
3 MSS data.
3 data
ne test sites
site temporal
rghum and sun
planting date
ariability in
ected by local
ces.
of MSS data
compensate for
tal count and
difference
ed from EROS
nship:
(1)
i be converted
(2)
2
Sr. are given
trome et al.,
1 values of
min-^'min)
max-R'min)
MAIZE
315 0 50 100 150 200 250 300 350
I960 1981
JULIAN OATE
SORGHUM
Compensation for station-to-station differences was
carried out by means of a linear transformation of
the MSS data using the calculated values of A and B.
4.2.1.2 Compensation for satellite-to-satellite
differences
The method and values prepared by Parris and Rice
referred to above were used (Rice et al., 1983).
4.2.2 The Tasseled cap Transformation for the study
area.
JULIAN OATE
The application of the Gram-Schmidt process to the
data corrected as described in 4.2.1.1 and 3.3.2
above produces the required set of orthogonal unit
vectors.
The matrix of the Tasseled cap transformation for
the Grootvlei test site was found to be
SUNFLOWER
315 0 50 100 150 200 250 300 350
1980 1981
JULIAN OATE
0.30
-0.36
-0.26
(Turner, 1986) and
in 3.3.3.
0.38 0.34
-0.80 0.37
-0.77 0.58
SBI, GVI and YVI
0.69
0.30
0.05
were defined as
4.3 Vegetation indices
Figure 5. Temporal Plots of Growth Stages of Field
Samples within WRS 182-79.
Table 4. Range of Absolute Radiances (Anon, 1976 and
Strome, 1975)
EROS
CCRS
R
max
R
min
R'
max
R'
min
LANDSAT
1
MSS
4
2.48
0
3.00
0.0
MSS
5
2.00
0
2.00
0.0
MSS
6
1.76
0
1.75
0.0
MSS
7
not calibrated
not calibrated
LANDSAT
2
MSS
4
2.63
0.08
3.00
0.0
MSS
5
1.76
0.06
2.00
0.0
MSS
6
1.52
0.06
1.75
0.0
MSS
7
3.91
0.11
4.00
0.0
LANDSAT
3
MSS
4
2.50
0.04
2.50
0.0
MSS
5
2.00
0.03
2.00
0.0
MSS
6
1.65
0.03
1.75
0.0
MSS
7
4.50
0.03
4.00
0.0
The calculated values of A and B are given in Table 5.
Table 5. Coefficients of Linear Transformation for
SRSC 8-bit data to EROS 7/6 bit data
A
B
LANDSAT
1
MSS 4
0.61
0.00
MSS 5
0.50
0.00
MSS 6
0.25
0.00
MSS 7
not calibrated
LANDSAT
2
MSS 4
0.59
-4.02
MSS 5
0.57
-4.36
MSS 6
0.60
-5.26
MSS 7
0.26
-1.85
LANDSAT
3
MSS 4
0.51
-2.06
MSS 5
0.51
-2.06
MSS 6
0.51
-2.06
MSS 7
0.51
-2.06
Sample wheat test sites were formed by concatenation
of known samples from wheat fields representative of
WRS 182-79 (Malan and Turner, 1984). A temporal plot
of the VI and NVI is given in Fig. 6.
5. DISCUSSION OF THE RESULTS
The coefficients of the matrix of the Tasseled cap
transformation obtained in the present work were
found to differ significantly from those obtained by
Kauth and Thomas for MSS data representative of the
US Corn Belt. Although the Tasseled cap transforma
tion does indeed exploit the structure of the MSS
data to produce independent indices SBI and GVI, the
orientations of the distribution of the bispectral
plots appear to be dependent on geographic location.
This study has therefore illustrated that even when
the MSS data is reduced to the same standard condi
tions applied by Kauth and Thomas for the US Corn
Belt, the coefficients of the Tasseled cap transfor
mation are different for US and South African condi
tions. However, the concepts evolved by Kauth and
Thomas would still appear to be directly applicable
to agricultural MSS data collected for the South
African Highveld.
The vegetation indices, as shown in Fig. 6, form
two distinct sets representing the wheat and non
wheat cover types. Seasonal variations seem to be
significant and may be correlated with the quantity
and timing of rain and the growth stage of the
wheat. The single observation for the 1982 season
seems anomalous in two respects: The maximum index
is greater than for the other two seasons and the
division between wheat and non-wheat is less pro
nounced. These significant variations may be due to
higher rainfall during October 1982 (1627 mm) than in
1981 (316 mm) and 1983 (1266 mm).
5.1 Future developments
The generation of the temporal profiles of the spec
tral and ground reference data sets for each field
and an analysis of these data in terms of the spec
tral separability of the crops, the influence of the
planting date, row direction, etc. on the vegetation
indices, the spatial variability of vegetation in
dices for similar crops within a LANDSAT scene, and