Agriculture Reference
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(HH) radar which is adapted to soil moisture estimation, enabled both soil
moisture and LAI of wheat canopies to be estimated. The availability of L
band would further increase the potential to estimate soil moisture under
denser canopies.
La
rge-Scale Monitoring Using Scatterometers
Compared to SAR, the number of scientific studies investigating the poten-
tial of scatterometers for soil moisture and vegetation retrieval is limited.
Most likely this is due to the low spatial resolution of scatterometers (tens
of kilometers), which restricts their use to regional applications. Still, con-
siderable progress has been made, and scatterometer-derived soil moisture
data, which reflect the atmosphere-related, large-scale component of the
soil moisture field (Vinnikov et al., 1999), have already been used as input
to crop models to assess drought-induced yield reductions. Here we only re-
view work done with the C-band (VV) scatterometer onboard ERS-1/2 but
recognize that there have been impressive first studies using the Ku-band
scatterometers onboard the QuikScat and Midori-2 satellites launched in
1999 and 2002, respectively.
Many of the initial ERS scatterometer studies focused on the retrieval
of vegetation parameters because a substantial agreement between back-
scatter and global vegetation index maps has been observed (Frison and
Mougin, 1996). Consequently, several models capable of separating soil
moisture from vegetation effects have been developed and applied to back-
scatter time series. Surface roughness is less of a problem for the analysis of
scatterometer time series given that, at regional scales, it can be considered
to be time invariant. In recent years attention has shifted more and more
to the retrieval of soil moisture given the greater than anticipated sensi-
tivity of the C-band scatterometer to soil moisture. For example, applica-
tion of the model developed by Woodhouse and Hoekman (2000) over a
Mediterranean region (Spain) did not properly recover the seasonal vege-
tation signal but provided soil surface reflectivity values in agreement with
the monthly precipitation records.
A soil moisture retrieval technique based on a change detection ap-
proach has been developed by Wagner et al. (1999b). The method is ca-
pable of separating the effects of soil moisture and vegetation phenology
by exploiting the information content provided by the multiple-viewing
capabilities of the ERS scatterometer. By comparing instantaneous ERS
scatterometer measurements to the lowest and highest backscatter values
in the ERS scatterometer time series, a relative measure of the moisture
content of the surface soil layer (
<
5 cm) is obtained. The algorithm has
been tested over different climatic regions with success, and the multiyear
soil moisture data were derived from remotely sensed data (Wagner and
Scipal, 2000; Scipal et al., 2002). The data set is available to other research
groups on request and can be viewed on a Web site (IPF, 2003).
Microwaves sense only the first few centimeters of the soil, but for agri-
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