The RMS errors calculated on the dataset over the rough-
ness estimates represent on the other hand 2.8cm, whereas
with the DUBOIS-model we reached 0.36cm. This overes-
timation is present for all the L-bands.
To determine the backscattering values expected by (Oh et
al., 1992) and compare them to the effectively measured re-
turns, we introduced the soil moisture and roughness mea-
surement into the equations (2) then derived the cross-
sections o2,, 02, and oÿ,. The L-HH band cross-sections
derived with the TDR-measurement approach better our
backscatter coefficients (RMS error= 1.68dB) then those
derived with the gravimetric measurements (RMS error=
1.98dB). However, the measured L-VV and L-HV backscat-
ter coefficients lie nearer from those derived with the 0—4
cm layer measurements. It would bring to the conclusion
that the L-band carried by the E-SAR penetrates more the
soil surface in HH-polarization than in VV and HV.
To sum up, the model from OH has to be ameliorated signifi-
cantly for the roughness estimation and it has to be cleared
why the radar backscatter coefficients reach and exceed
the value 1, even for bare soils.
As mentioned above, at the first date the E-SAR sensor
flew twice over the watershed, measuring in the L-band. It
is known from literature, that the radar look direction rela-
tive to the row direction strongly affects the returned wave.
This observation could be made in one of the two L-bands,
especially in HH-polarization, each time the look direction
was perpendicular to row direction. This phenomenon di-
rectly affects the radar cross-sections and is not taken into
account in both models.
5 CONCLUSION
In this paper we presented our first results of a confronta-
tion between the radar backscattering and hydrological pa-
rameters like soil moisture and surface roughness. The dif-
ferent regression analyses show that no direct and system-
atic correlations with soil moisture measurements emerge
from our datasets. So, it is necessary to use a more com-
plex approach in applying two inversion models. Thereby,
we found a better sensitivity for soil moisture estimation us-
ing the empirical approach of (Oh et al., 1992) than using
the approach of (Dubois et al., 1995). The opposite ten-
dency was observed for the estimation of surface rough-
ness, which is widely better using the Dubois-model. There-
fore, both models need further examination and refinement
to be acceptable in the case of a catchment area where
relief and agricultural fields play a predominant role.
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