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taneous, consistent multiple angle measurements. Finally, there have been
attempts to use the polarization difference (PD; the difference between the
vertical and the horizontal brightness temperature i.e.,
T
B
T
B
) for soil
moisture retrieval. As described by Njoku et al. (2000), an advantage of
this approach is that it normalizes out the physical temperature. How-
ever, because it does not use physically based equations, the retrieval ulti-
mately relies on calibration. The polarization difference approach has been
explored in a number of studies. These investigations did not involve actual
soil moisture but rather related indices.
−
Microwave Polarization Difference Index and Vegetation
Parameters
Th
e microwave polarization difference index (MPDI), an alternative to the
po
larization difference, is expressed as:
[94],
c
(
T
B
T
B
)/(
T
B
T
B
)
=
−
+
MPDI
[7.4]
Line
——
-2.0
——
Norm
PgEn
where
c
is a scaling factor. Tucker (1989) and Tucker and Choudhury
(1987) have attempted to exploit high-frequency passive microwave re-
mote sensing in monitoring drought. They used 37-GHz polarization dif-
ference data collected by the scanning multifrequency microwave radiome-
ter (SMMR). At this frequency the brightness temperature is dominated
by vegetation effects and, in particular, vegetation water content. It was
hypothesized that these observations could enhance products based on the
normalized difference vegetation index (NDVI; chapters 5 and 6). Compar-
isons were made between the PD and NDVI for several study areas during
periods of drought and nondrought. It was observed that the PD was very
sensitive to changes in the NDVI at lower NDVI levels. However, as NDVI
increased, the PD saturated at a low value. The polarization difference ap-
proaches zero as vegetation level increases.
Teng et al. (1995) summarized much of the work that has been done to
relate microwave polarization information to the NDVI. They found the
PD to be more sensitive to vegetation cover in regions of sparse vegeta-
tion and to NDVI in densely vegetated regions. These authors further used
satellite 37-GHz PD data over the U.S. Midwest and found that drought
years could be differentiated from normal years during the preplanting and
early stages of crop growth. At a point in the growth cycle through harvest
there was little information contained in the PD between years or months.
The type of crop also had an influence on the potential information avail-
able using the PD. They concluded that NDVI provides more information
on vegetation conditions; however, the PD provides unique information
during periods when the NDVI is not useful.
Teng et al. (1995) concluded that PD and NDVI data are complementary
for drought analyses. They noted that in some situations (the 1988 drought
in the U.S. Midwest in particular) the NDVI can detect drought early in the
season for severely affected regions. However, other regions that are not
[94],
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