In: Wagner W., Sz£kely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, ¡APRS, Vol. XXXVIII, Part 7B
Figure 1: Location of La Tejería experimental watershed
mVmeas [vol%]
50 r
[dB]
feb 27 mar 06 mar 23 mar 30 apr 02
Date
Figure 3: Normalized backscatter coefficients (cf) obtained at
different acquisition dates in 2003
40
30
20
I
10
I
i
I
feb 27 mar 06
mar 23 mar 30 apr 02
Date
Figure 2: Soil moisture contents (mv mcas ) measured at different
acquisition dates in 2003
2.1 Study site and data
The studied watershed, La Tejería, is situated in the north of Spain
(Figure 1), has a humid, submediterranean climate and consists of
clayey and silty clay loam textures. It is almost completely cul
tivated, with an emerging cereal crop covering most of the fields
during the experimental period (February - April 2003). A more
detailed description of the study site is given by Alvarez-Mozos
et al. (2006).
For each acquisition day, field average soil moisture contents were
calculated for fifteen seedbed fields based on measurements with
a Time Domain Reflectometry (TDR) instrument with 11 cm
probes (Figure 2). For a detailed description of the sampling
method we refer to Álvarez-Mozos et al. (2006).
Next, five C-band, HH polarized RADARS AT-1 SGF scenes were
acquired over the experimental region during spring 2003, at low
incidence angles (13°-29°). This configuration has proved to
be particularly well suited for soil moisture research over ce
real canopies (Ulaby et al., 1982b; Biftu and Gan, 1999; Mat-
tia et al., 2003b). The images have a range resolution of 20 m or
24 m and an azimuth resolution of 27 m, from which field average
backscatter coefficients were calculated. Furthermore, in order to
reduce the effect of the local incidence angle on the backscatter
coefficients, these coefficients were normalized correspondent to
a reference incidence angle, according to Lambert’s law for op
tics (Ulaby et al., 1982b; Van Der Velde and Su, 2009):
o
0
o-1
COS 2 -#ref
COS 2 9
(1)
ence incidence angle [°], in this case chosen to be 23° and 9 is the
local incidence angle [°], The resulting field average backscatter
values are shown for every acquisition date in Figure 3.
2.2 Integral Eqation model
The single scattering approximation of the Integral Equation
Model (IEM) (Fung et al., 1992; Fung, 1994) is the most widely
used scattering model for bare soil surfaces (Moran et al., 2004).
It allows for the calculation of backscatter coefficients based on
bare soil surface roughness parameters, soil dielectric constant,
local incidence angle, wave polarisation and frequency. The IEM
describes surface roughness by three complementary parameters:
rms height (s), correlation length (l), and an autocorrelation func
tion. Davidson et al. (2000) and Callens et al. (2006) demon
strated that for smooth to medium rough agricultural bare fields
this autocorrelation function is best represented by an exponential
function.
The conversion of the dielectric constant to the corresponding soil
moisture content is performed by means of the four-component
dielectric mixing model of Dobson et al. (1985), for which the
residual and saturated soil moisture content used
throughout this study are set to 3 vol% and 45 vol% respectively.
It is expected that the emerging crops on the fields influence the
results of the inversion of the IEM, since this was developed for
bare soil conditions. However, the canopies were only weakly
developed and the incidence angles were low, which are reasons
to believe that the effect of the vegetation is minimal (Ulaby et
al., 1982b; Maffia et al., 2003b). Furthermore, simulations by
Lievens et al. (2010) using a water cloud model (Attema and
Ulaby, 1978; Prévôt et al., 1993) indicated that the attenuation
of the backscatter by the cereal canopy was to a large extent com
pensated by a direct canopy contribution. This led to insignifi
cant vegetation corrections within the relative radiometric accu
racy of the RADARSAT observations, i.e. +/-1 dB (Srivastava et
al., 1999). Therefore this study will not take into account a pos
sible influence of the crop cover on the backscattered signal.
2.3 Effective roughness
The idea of using effective roughness parameters was first intro
duced by Su et al. (1997). The effective roughness parameters are
estimated using backscatter and soil moisture observations. They
replace in situ measurements of soil surface roughness for the re
trieval of soil moisture content from successive SAR images.
where cr,° n is the linear normalized backscatter coefficient [-], of In case of the IEM, two effective roughness parameters need to
is the linear measured backscatter coefficient [-], 6W is the refer- be defined: rms height (s) and correlation length (/). Lievens
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